Methods and systems for detecting an organ or a tissue impacted by a cancer or a disease, disorder or condition

Abstract

Disclosed herein are methods and systems of determining a cancer status or an organ health status of a subject, the method comprising: obtaining a biological sample obtained or derived from the subject; enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells and / or progenitor cells; extracting nucleic acids from the enriched population of cells; assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, and / or an exomic profile of the subject; computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, and / or the exomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status or the organ health status of the subject, wherein the cancer status or the organ health status comprises a presence or an absence of an organ and / or a tissue impacted by the cancer or impacted by a disease, disorder, or condition.

Description

[0001] WSGR Docket No. 63688-708.601

[0002] METHODS AND SYSTEMS FOR DETECTING AN ORGAN OR A TISSUE IMPACTED BY A CANCER OR A DISEASE, DISORDER OR CONDITION

[0003] CROSS REFERENCE TO RELATED APPLICATIONS

[0004] [1] This application claims the benefit of Indian Patent Application No. 202411070278 filed on September 17, 2024, and Indian Patent Application No. 202511028966 filed on March 27, 2025, the entirety of each is incorporated herein by reference.

[0005] BACKGROUND

[0006] [2] The diagnosis and / or detection of a cancer in a subject is a challenging task. Current methods for diagnosing cancers may involve a combination of screening tests, such as for example, Pap (Papanicolaou) tests, Prostate-Specific Antigen (PSA) tests, mammograms, colonoscopy, and low-dose CT scans. Additional methods may include radiological and nuclear medicine-based non-invasive modalities, such as for example, X-ray scans, computed tomography (CT) scans, an ultrasonography, magnetic resonance imaging (MRI), and positron emission tomography (PET) scan using, for example, fluorodeoxyglucose (FDG)-PET, prostatespecific membrane antigen positron tomography (PSMA PET), etc., followed by a minimally invasive or invasive (e.g., surgical) biopsy and histopathological examination to determine the identity and stage of the cancer and / or tumor. There are hazards associated with invasive tests, including the spread of cancer cells to nearby tissues and / or organs, discomfort experienced by the subject (e.g., patient), and the potential for infections in the subject. Contents in a biological sample can be detected using liquid biopsy techniques, which are less invasive and alternative methods as compared to surgical biopsies. However, there exists challenges in the sensitivity and specificity with these non-invasive tests, as well as questions regarding the usefulness and value of the limited information that they provide. The accuracy of existing cancer diagnosis tests varies and may result in false positives culminating in over-diagnosis. Repeated surgical biopsies from organs can be difficult. On the other hand, liquid biopsy provides a holistic picture over innumerable time points with respect to limited loss of accuracy e.g., sensitivity and specificity. From the perspective of non-cancer diseases, disorders and conditions, various plasma / serum biochemistry tests can be indicated in the clinical setting. These tests may be unable to provide pharmacogenomic and pharmacotranscriptomic responses to existing medications, as well as predictive analytics for future recommendations from a drug perspective. Thus, clinicians are bound to trial and error and empirical knowledge for clinical decision makings without robust scientific backing in many scenarios. Liquid biopsy can potentially circumvent these issues, thus, leading to significant clinical diagnosis, prognosis and therapy management. WSGR Docket No. 63688-708.601

[0007] SUMMARY

[0008] [3] In an aspect, the present disclosure provides methods of determining a cancer status of a subject, the method comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells or progenitor cells; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or an absence of a cancer in an organ or a tissue. In some embodiments, the stem cells comprise cancer stem cells, very small embryonic-like stem cells, or pluripotent stem cells. In some embodiments, the progenitor cells comprise tissue committed progenitor cells. In some embodiments, the biological sample comprises a blood sample, a fraction of the blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample. In some embodiments, the biological sample comprises the blood sample. In some embodiments, the biological sample comprises the fraction of the blood sample. In some embodiments, the biological sample comprises the plasma sample. In some embodiments, the biological sample comprises the serum sample. In some embodiments, the subject is suspected of having the cancer. In some embodiments, the subject is not suspected of having cancer. In some embodiments, the cancer status comprises a presence or an absence of the cancer. In some embodiments, the cancer comprises breast cancer, liver cancer, ovarian cancer, lung cancer, leukemia, lymphoma, renal cancer, bladder cancer, brain cancer, head and neck cancer, prostate cancer, pancreatic cancer, cervical cancer, colon cancer, testicular cancer, thyroid cancer, bile duct cancer, or esophageal cancer. In some embodiments, the cancer comprises stage 0 cancer, stage I cancer, stage II cancer, stage III cancer, or stage IV cancer. In some embodiments, the extracted nucleic acids comprise deoxyribonucleic acid (DNA). In some embodiments, the extracted nucleic acids comprise ribonucleic acid (RNA). In some embodiments, the RNA comprises messenger RNA (mRNA), transfer RNA (tRNA), or ribosomal RNA (rRNA). In some embodiments, the enriching the population of cells comprises performing a cell sorting assay. In some embodiments, the cell sorting assay divides the population of cells into one or more subpopulations. In some embodiments, the one or more subpopulations of cells comprise cancer stem cells, very small embryonic-like stem cells, pluripotent stem cells, or tissue committed progenitor cells. In some embodiments, the cell sorting assay comprises flow cytometry, density gradient centrifugation, magnetic activated cell sorting (MACs), molecular WSGR Docket No. 63688-708.601 coated beads, cell separation technology, single cell RNA sequencing, a cell culturing assay, a cell plasmid assay, or a combination thereof. In some embodiments, assaying the extracted nucleic acids comprises sequencing the extracted nucleic acids. In some embodiments, the sequencing comprises next generation sequencing (NGS). In some embodiments, the sequencing comprises whole transcriptome sequencing, whole genome sequencing, or whole exome sequencing. In some embodiments, the sequencing comprises pyrosequencing, RNA sequencing, sequencing by synthesis (SBS), or nanopore sequencing. In some embodiments, the transcriptomic profile of the subject comprises one or more cancer-associated genes. In some embodiments, the genomic profile of the subject comprises one or more cancer-associated genes. In some embodiments, the exomic profile of the subject comprises one or more cancer- associated genes. In some embodiments, the computer processing further comprises determining a transcriptome assessment score from the transcriptomic profile of the subject, wherein the determining the transcriptome assessment score comprises: (i) identifying at least one control sample from at least one control subject; and (ii) determining one or more differentially expressed genes (DEGs) relative to the at least one control sample. In some embodiments, the identifying at least one control sample is based at least in part on an age of the at least one control subject, a gender of the at least one control subject, a total million reads (TMR) of the at least one control sample, a RNA Integrity Number (RIN) of the at least one control sample, an absence of comorbidities or diseases in the at least one control subject, or a combination thereof. In some embodiments, the age of the at least one control subject is within 10 years of an age of the subject. In some embodiments, the gender of the at least one control subject is the same as a gender of the subject. In some embodiments, the TMR of the at least one control sample is within 10 million reads of a TMR obtained from the biological sample. In some embodiments, the RIN of the at least one control sample is at least 7. In some embodiments, the one or more DEGs comprises one or more genes in one or more pathways in cancer or one or more cancer gene panels. In some embodiments, the one or more pathways in cancer comprises component pathways comprising p53 signaling pathway, Ras signaling pathway, Calcium signaling pathway, cAMP signaling pathway, Hippo signaling pathway, JAK-STAT signaling pathway, MAPK signaling pathway, mTOR signaling pathway, Notch signaling pathway, PI3K-Akt signaling pathway, TGF-beta signaling pathway, VEGF signaling pathway, Wnt signaling pathway, or a combination thereof. In some embodiments, the one or more cancer gene panels comprises at least one biomarker comprising metabolic markers, inflammatory markers, metastatic markers, DNA repair genes, proto oncogenes, frequently mutated genes, cancer stem cell markers, epigenetic regulator genes, cell cycle genes, immune regulators, cancer diagnostic markers, tumor suppressor genes, immune checkpoints, or a combination thereof. In some WSGR Docket No. 63688-708.601 embodiments, the determining the transcriptome assessment score comprises assigning a risk threshold to a DEG of the one or more DEGs. In some embodiments, the determining the transcriptome assessment score further comprises assigning a pathway in cancer risk category to a cancer pathway of the one or more cancer pathways, based at least in part on the risk threshold of the DEG in the one or more cancer pathways, assigning a PIC component pathway risk category based at least in part on the risk threshold of the DEG, wherein the one or more DEGs is in the one or more PIC component pathways, and assigning a cancer gene panel risk category to a cancer gene panel of the one or more cancer gene panels, based at least in part on the risk threshold of the DEG in the one or more cancer gene panels. In some embodiments, the risk category is selected from the group consisting of a high risk, a moderate risk, a low risk, and a negligible risk. In some embodiments, the determining the transcriptome assessment score comprises (I) determining a pathway in cancer risk score based at least in part on the risk category of the one or more cancer pathways, (II) determining a PIC component pathway risk category based at least in part on the risk category of the one or more PIC component pathways, and (III) determining a cancer gene panel risk score based at least in part on the risk category of the one or more cancer gene panels, or a combination of (I), (II), and (III). In some embodiments, the determining the cancer pathway risk score comprises determining a weighted sum of each risk category of the one or more pathways in cancer, determining the component pathway risk score comprises determining a weighted sum of each risk category of the one or more PIC component pathways, and wherein determining the cancer gene panel risk score comprises determining a weighted sum of the one or more cancer gene panels. In some embodiments, the determining the transcriptome assessment score comprises determining a weighted sum of the pathway in cancer risk score, component pathway risk score, and the cancer gene panel risk score. In some embodiments, the determining the transcriptome assessment score comprises using of a machine learning model to obtain a whole transcriptome score, wherein the whole transcriptome score is based at least in part on Fragments Per Kilobase of transcript per Million mapped reads (FPKM) from the transcriptomic profile of the subject. In some embodiments, the machine learning model comprises a trained machine learning algorithm. In some embodiments, the trained machine learning algorithm is selected from the group consisting of K-Neighbors Classifier, NuSVC, Multi-Layer Perceptron (MLP) Classifier, Decision Tree Classifier, Random Forest Classifier, Logistic Regression, Gaussian Naive Bayes (NB) Classifier, Linear Discriminant Analysis, Quadratic Discriminant Analysis, and Support Vector Classifier (SVC). In some embodiments, the whole transcriptome score is based at least in part on a set of gene expression levels comprising all genes detected, a second set of gene expression levels comprising cancer pathway genes, and a third set of gene expression levels WSGR Docket No. 63688-708.601 comprising signaling pathway genes. In some embodiments, the whole transcriptome score is based on determining a classification of the subject by the machine learning model, wherein the classification is selected from the group consisting of a control, a control indeterminant, a cancer survivor, a cancer subject on treatment, a cancer subject that is treatment naive, and cancer treatment naive indeterminant. In some embodiments, the classification of control indicates that the subject never had the cancer. In some embodiments, the classification of control indeterminate indicates that the subject does not have the cancer but comprises some other pathology that is not the cancer. In some embodiments, the classification of the cancer survivor indicates that the subject had the cancer and completed a cancer treatment more than 6 months prior and is PET negative. In some embodiments, the classification of the cancer subject on treatment indicates that the subject is or within 6 months since undergoing a cancer treatment. In some embodiments, the classification of the cancer treatment naive indicates that the subject is cancer treatment naive. In some embodiments, the classification of the cancer treatment naive indeterminant indicates that the subject has the cancer and is cancer treatment naive. In some embodiments, the computer processing comprises determining an exome assessment score from the exomic profile of the subject, wherein the determining the exome assessment score comprises: extracting at least one feature from the exomic profile of the subject; and applying at least one trained machine learning algorithm to the at least one feature to classify the subject into a category of one or more categories. In some embodiments, the at least one feature comprises a count of A, T, G, C, AT, and GC; a count of guanine rich DNA fragments; a count of insertion and deletions; a count of single base substitutions; a count of double base substitutions; or a combination thereof. In some embodiments, the one or more categories comprises a control, a control indeterminant, a cancer survivor, a cancer subject on treatment, a cancer treatment naive, or a cancer treatment naive indeterminant. In some embodiments, the at least one trained machine learning algorithm is selected from the group consisting of K-Neighbors Classifier, NuSVC, Multi-Layer Perceptron (MLP) Classifier, Decision Tree Classifier, Random Forest Classifier, Logistic Regression, Gaussian Naive Bayes (NB) Classifier, Linear Discriminant Analysis, Quadratic Discriminant Analysis, and Support Vector Classifier (SVC). In some embodiments, the applying the at least one trained machine learning algorithm further comprises scaling a prediction value of the category based on a range of prediction values for the one or more categories. In some embodiments, the computer processing comprises analyzing at least one somatic mutation from the exomic profile of the subject. In some embodiments, the analyzing the at least one somatic mutation comprises identifying a somatic mutation having a variant allele frequency of less than 0.1%. In some embodiments, the analyzing the at least one somatic mutation comprises identifying a somatic WSGR Docket No. 63688-708.601 mutation associated with the cancer. In some embodiments, the computer processing comprises analyzing at least one germline mutation from the exomic profile of the subject. In some embodiments, the analyzing the at least one germline mutation comprises identifying a germline mutation having a variant allele frequency of at least 0.5%. In some embodiments, the analyzing the at least one germline mutation comprises identifying a germline mutation associated with the cancer. In some embodiments, the method further comprises determining an organ or a tissue impacted by the cancer. In some embodiments, the organ or the tissue impacted by the cancer comprises one or more tumors. In some embodiments, the organ or the tissue impacted by the cancer does not comprise a tumor. In some embodiments, the tumor is a malignant tumor or a benign tumor. In some embodiments, the tissue impacted by the cancer comprises one or more tissues impacted by the cancer. In some embodiments, the organ or the tissue impacted by the cancer comprises an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, a bone marrow, testis, a liver, a kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, or a lymphoid organ. In some embodiments, the cancer status comprises a cancer remission status. In some embodiments, the cancer status comprises a cancer recurrence status. In some embodiments, the cancer status comprises a risk of the subject having the cancer. In some embodiments, the method further comprises determining the risk of the subject having the cancer with an accuracy of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more. In some embodiments, the method further comprises determining the risk of the subject having the cancer with a sensitivity of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more. In some embodiments, the method further comprises identifying the subject as having an elevated risk of having the cancer. In some embodiments, the method further comprises identifying the subject as not having an elevated risk of having the cancer. In some embodiments, the method further comprises, responsive to the cancer status determined in f), administering a treatment to the subject, thereby treating the cancer. In some embodiments, the method further comprises, responsive to an organ or a tissue health of the organs or tissues, as determined as part of the cancer status determined in f), administering a treatment to the subject, thereby treating the cancer. In some embodiments, the treatment comprises surgical resection, chemotherapy, targeted therapy, systemic therapy, radiation therapy, immunotherapy, or a combination thereof. In some embodiments, the cancer status comprises the absence of the cancer. In some embodiments, the absence of the cancer is determined at least in part by a presence of one or more non-cancerous conditions. In some embodiments, the non-cancerous conditions comprise a liver condition, a brain condition, a breast condition, a lung condition, a WSGR Docket No. 63688-708.601 prostate condition, a bladder condition, a kidney condition, a bone condition, a pancreas condition, a stomach condition, a skin condition, an ovary condition, or a colon condition. In some embodiments, the method further comprises, responsive to the absence of the cancer, modifying a treatment to the subject. In some embodiments, the modifying the treatment comprises modifying a treatment dose of the treatment.

[0009] [4] In an aspect, the present disclosure provides methods of determining a health status of an organ or a tissue of a subject, the method comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells or progenitor cells; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the health status of the organ or the tissue of the subject. In some embodiments, the computer processing further comprises: (i) identifying at least one control sample from at least one control subject; and (ii) determining one or more differentially expressed genes (DEGs) relative to the at least one control sample. In some embodiments, the identifying the at least one control sample is based at least in part an age of the at least one control subject, a gender of the at least one control subject, a total million reads (TMR) of the at least one control sample, a RNA Integrity Number (RIN) of the at least one control sample, an absence of comorbidities or diseases in the at least one control subject, or a combination thereof. In some embodiments, the age of the at least one control subject is within 10 years of an age of the subject. In some embodiments, the gender of the at least one control subject is the same as a gender of the subject. In some embodiments, the TMR of the at least one control sample is within 10 million reads of a TMR obtained from the biological sample. In some embodiments, the RIN of the at least one control sample is at least 7. In some embodiments, the computer processing comprises analyzing the one or more DEGs, wherein the one or more DEGs is in one or more gene panels for dysregulation of cell function. In some embodiments, the one or more gene panels comprises a gene panel for epigenetic dysregulation, a gene panel for genetic dysregulation, a gene panel for pathway dysregulation, a gene panel for disease-based dysregulation, or a combination thereof. In some embodiments, the gene panel for disease-based dysregulation comprises genes associated with diabetes, endometriosis, neurodegeneration, Alzheimer’s disease, lung disease, hepatitis, or psoriasis. In some embodiments, the computer processing comprises assigning a risk category to each gene panel of the one or more gene panels. In some embodiments, the computer processing comprises WSGR Docket No. 63688-708.601 determining an adverse dysregulation of an organ or disease pathway based at least in part on the risk category of each gene panel. In some embodiments, the computer processing comprises determining one or more adversely dysregulated genes in the one or more gene panels. In some embodiments, the determining the one or more adversely dysregulated genes in the one or more gene panels comprises assigning one or more risk thresholds to the one or more adversely dysregulated genes. In some embodiments, the computer processing comprises determining an adverse dysregulation of an organ or disease pathway based at least in part on the one or more risk thresholds. In some embodiments, the determining the health status of the organ or the tissue of the subject is based at least in part on the determining the adverse dysregulation. In some embodiments, the determining in f) comprises detecting a presence or an absence of a non- cancerous condition. In some embodiments, the non-cancerous condition comprises a liver condition, a brain condition, a breast condition, a lung condition, a prostate condition, a bladder condition, a kidney condition, a bone condition, a pancreas condition, a stomach condition, a skin condition, an ovary condition or a colon condition. In some embodiments, the determining in f) comprises detecting an absence of a cancer in the organ or the tissue of the subject.

[0010] [5] In an aspect, the present disclosure provides methods of determining an effect of a therapeutic on a subject, the method comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point; b) enriching a first population of cells in the first biological sample, wherein the first population of cells comprises stem cells or progenitor cells; c) extracting first nucleic acids from the enriched first population of cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject or a first exomic profile of the subject; e) administering the therapeutic to the subject; f) obtaining a second biological sample obtained or derived from the subject at a second time point subsequent to the administering; g) enriching a second population of cells in the second biological sample, wherein the second population of cells comprises stem cells or progenitor cells; h) extracting second nucleic acids from the enriched second population of cells; i) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; j) computer processing (1) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject, and (2) the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject; and k) determining, based at least in part on the computer processing, the effect of the therapeutic on the subject. In some embodiments, determining the effect of the therapeutic on the subject comprises determining a cancer status of the subject or a health condition of the WSGR Docket No. 63688-708.601 subject. In some embodiments, the stem cells comprise cancer stem cells, very small embryonic- like stem cells, or pluripotent stem cells. In some embodiments, the progenitor cells comprise tissue committed progenitor cells. In some embodiments, the enriching the first population of cells and the second population of cells comprises performing a cell sorting assay. In some embodiments, the cell sorting assay divides the population of cells into one or more subpopulations of cells. In some embodiments, the one or more subpopulations of cells comprise cancer stem cells, very small embryonic-like stem cells, pluripotent stem cells, or tissue committed progenitor cells. In some embodiments, the cell sorting assay comprises flow cytometry, density gradient centrifugation, magnetic activated cell sorting (MACs), use of molecular coated beads, cell separation technology, single cell RNA sequencing, a cell culturing assay, or a cell plasmid assay.

[0011] [6] In an aspect, the present disclosure provides methods of assessing an effect of a therapeutic, the method comprising: a) assaying a first expression profile of a first biological sample obtained or derived from a subject at a first time point to thereby produce a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; b) administering the therapeutic to the subject; c) assaying a second expression profile of a second biological sample obtained or derived from the subject at a second time point subsequent to the administering the therapeutic of b) to thereby produce a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; d) comparing, using at least a computer, the first and second transcriptomic profiles of the subject, genomic profiles of the subject, or exomic profiles of the subject; and e) assessing the effect of the therapeutic based at least in part of the comparing. In some embodiments, the therapeutic comprises a treatment for a cancer. In some embodiments, the therapeutic comprises a treatment for a health condition. In some embodiments, the biological sample comprises a blood sample, a fraction of the blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample. In some embodiments, the biological sample comprises the blood sample. In some embodiments, the biological sample comprises the fraction of the blood sample. In some embodiments, the biological sample comprises the plasma sample. In some embodiments, the biological sample comprises the serum sample. In some embodiments, the subject is suspected of having a cancer. In some embodiments, the cancer comprises breast cancer, liver cancer, ovarian cancer, lung cancer, renal cancer, leukemia, lymphoma, bladder cancer, prostate cancer, pancreatic cancer, cervical cancer, color cancer, testicular cancer, thyroid cancer, bile duct cancer, or esophageal cancer. In some embodiments, the cancer comprises stage 0 cancer, stage I cancer, stage II cancer, stage III cancer, or stage IV cancer. WSGR Docket No. 63688-708.601

[0012] [7] In an aspect, the present disclosure provides methods of determining a cancer status of a subject, the method comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; j) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; k) enriching a third population of stem cells or progenitor cells in the third biological sample; 1) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; m) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; n) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject; and o) determining, based at least in part on the computer processing, the cancer status of the subject. In some embodiments, the second time point is at least 15 days subsequent to the first time point. In some embodiments, the second time point is less than 4 months subsequent to the first time point. In some embodiments, the third time point is at least 15 days subsequent to the second time point. In some embodiments, the third time point is less than 4 months subsequent to the second time point. In some embodiments, the subject is a cancer survivor.

[0013] [8] In an aspect, the present disclosure provides methods of determining a cancer status of a subject, the method comprising: a) obtaining a first biological sample obtained or derived from WSGR Docket No. 63688-708.601 the subject at a first time point, wherein the subject comprises a cancer negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; j) enriching a third population of stem cells or progenitor cells in the third biological sample; k) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; 1) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; m) averaging (i) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, (ii) the second genomic profile of the subject, or the second exomic profile of the subject and (iii) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; n) obtaining a fourth biological sample obtained or derived from the subject at a fourth time point that is subsequent to the first, second, and third time points; o) enriching a fourth population of stem cells or progenitor cells in the fourth biological sample; p) extracting fourth nucleic acids from the enriched fourth population of stem cells or progenitor cells; q) assaying the extracted third nucleic acids to generate at least one of a fourth transcriptomic profile of the subject, a fourth genomic profile of the subject, or a fourth exomic profile of the subject; r) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the fourth transcriptomic profile of the subject, the fourth genomic profile of the subject, or the fourth exomic profile of the subject; and s) determining, based at least in part on the computer processing, the cancer status of the subject. In some embodiments, the subject is a cancer survivor. WSGR Docket No. 63688-708.601

[0014] [9] In an aspect, the present disclosure provides compositions comprising the any one of the therapeutics disclosed herein.

[0015]

[0010] In an aspect, the present disclosure provides kits comprising: (a) any one of the compositions disclosed herein; and (b) instructions for use of the composition according to any one of methods disclosed herein.

[0016]

[0011] In an aspect, the present disclosure provides non-transitory computer-readable memory storing one or more instructions executable by one or more processors, that when executed by the one or more processors cause the one or more processors to perform processing comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of stem cells or progenitor cells in the biological sample; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or absence of cancer in an organ or a tissue.

[0017]

[0012] In an aspect, the present disclosure provides computer systems for determining a cancer status of a subject, the system comprising: a) a non-transitory memory; and b) a processor in communication with the non-transitory memory, the processor configured to execute the following operations in order to effectuate a method comprising the operations of: i. obtaining a biological sample obtained or derived from the subject; ii. enriching a population of stem cells or progenitor cells in the biological sample; iii. extracting nucleic acids from the enriched population of stem cells or progenitor cells; iv. assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; v. computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and vi. determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or absence of cancer in an organ or a tissue.

[0018]

[0013] In an aspect, the present disclosure provides a non-transitory computer-readable memory storing one or more instructions executable by one or more processors, that when executed by the one or more processors cause the one or more processors to perform processing comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the WSGR Docket No. 63688-708.601 enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, or a baseline exomic profile; j) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; k) enriching a third population of stem cells or progenitor cells in the third biological sample; 1) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; m) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; n) computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject; and o) determining, based at least in part on the computer processing, the cancer status of the subject.

[0014] In an aspect, the present disclosure provides computer systems for determining a cancer status of a subject, the system comprising: a) a non-transitory memory; and b) a processor in communication with the non-transitory memory, the processor configured to execute the following operations in order to effectuate a method comprising the operations of obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; enriching a first population of stem cells or progenitor cells in the first biological sample; extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile, a first genomic profile, or a first exomic profile of the subject; obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; enriching a second population of stem cells or progenitor cells in the second biological sample; extracting second nucleic acids WSGR Docket No. 63688-708.601 from the enriched second population of stem cells or progenitor cells; assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile, a second genomic profile, or a second exomic profile of the subject; averaging the at least one of the first transcriptomic profile, the first genomic profile, or the first exomic profile of the subject with the at least one of the second transcriptomic profile, the second genomic profile, or the second exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, or a baseline exomic profile; obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; enriching a third population of stem cells or progenitor cells in the third biological sample; extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile, a third genomic profile, or a third exomic profile of the subject; computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile, the third genomic profile, or the third exomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status of the subject.

[0015] In an aspect, the present disclosure provides methods of determining a health condition of a subject, the method comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells or progenitor cells; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the health condition of the subject, wherein the health condition comprises a presence or an absence of an organ or a tissue impacted by the health condition. In some embodiments, the stem cells comprise very small embryonic-like stem cells, or pluripotent stem cells. In some embodiments, the progenitor cells comprise tissue committed progenitor cells. In some embodiments, the biological sample comprises a blood sample, a fraction of the blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample. In some embodiments, the biological sample comprises the blood sample. In some embodiments, the biological sample comprises the fraction of the blood sample. In some embodiments, the biological sample comprises the plasma sample. In some embodiments, the biological sample comprises the serum sample. In some embodiments, the subject is suspected of having the health condition. In some embodiments, the subject is not suspected of having the WSGR Docket No. 63688-708.601 health condition. In some embodiments, the health condition comprises a presence or an absence of the health condition. In some embodiments, the health condition comprises a cardiac health condition, a neurodevelopmental disease, diabetes, or endometriosis. In some embodiments, the health condition comprises the cardiac health condition. In some embodiments, the health condition comprises the neurodevelopmental disease. In some embodiments, the health condition comprises the diabetes. In some embodiments, the health condition comprises the endometriosis. In some embodiments, the health condition comprises a pancreatic health condition, a lung health condition, an upper respiratory tract health condition, a bone health condition, a bone marrow health condition, a testicular health condition, a liver health condition, a renal health condition, a skin health condition, an ovarian health condition, a breast health condition, a urinary bladder health condition, a gastrointestinal health condition, a small intestine health condition, an esophageal health condition, a salivary gland health condition, a stomach health condition, a brain health condition, a neurodegenerative health condition, a prostate health condition, a lymphatic system health condition, an adrenal gland health condition, a parathyroid health condition, a pituitary health condition, an eye health condition, a endometrial health condition, a gall bladder health condition, a tongue health condition, a thyroid health condition, a hair health condition, a nail health condition, a lipid-related health condition, an auto-immune health condition, a cardiac health condition, a blood health condition, a colon health condition, a bowel health condition, a uterus health condition, a biliary tract health condition, a central nervous system (CNS) health condition, a spinal cord health condition, a larynx health condition, a gastroesophageal health condition, a peripheral nervous system (PNS) health condition, a tooth health condition, a cartilage health condition, a reproductive system health condition, a duodenum health condition, a nasopharynx health condition, an appendix health condition, a cervical health condition, a lymph node health condition, a neuromuscular system health condition, a thymus health condition, an immunity health condition, a penile health condition, an adrenal cortex health condition, a fallopian tube health condition, a uveal health condition, a ciliary body health condition, a sweat gland health condition, a placenta health condition, a sebaceous gland health condition, a nasal health condition, a gonad health condition, an endocrine health condition, or an ear health condition. In some embodiments, the extracted nucleic acids comprise deoxyribonucleic acid (DNA). In some embodiments, the extracted nucleic acids comprise ribonucleic acid (RNA). In some embodiments, the method further comprises enriching the population of cells. In some embodiments, enriching the population of cells comprises performing a cell sorting assay. In some embodiments, the cell sorting assay divides the population of cells into one or more subpopulations. In some embodiments, the one or more subpopulations of cells comprise very WSGR Docket No. 63688-708.601 small embryonic-like stem cells, pluripotent stem cells, or tissue committed progenitor cells. In some embodiments, the cell sorting assay comprises flow cytometry, density gradient centrifugation, magnetic activated cell sorting (MACs), molecular coated beads, cell separation technology, single cell RNA sequencing, a cell culturing assay, a cell plasmid assay, or a combination thereof. In some embodiments, assaying the extracted nucleic acids comprises sequencing the extracted nucleic acids. In some embodiments, the sequencing comprises next generation sequencing (NGS). In some embodiments, the sequencing comprises whole transcriptome sequencing, whole genome sequencing, or whole exome sequencing. In some embodiments, the sequencing comprises pyrosequencing, RNA sequencing, sequencing by synthesis (SBS), or nanopore sequencing. In some embodiments, the transcriptomic profile of the subject comprises one or more genes associated with the health condition. In some embodiments, the genomic profile of the subject comprises one or more genes associated with the health condition. In some embodiments, the exomic profile of the subject comprises one or more genes associated with the health condition. In some embodiments, the computer processing comprises comparing the transcriptomic profile of the subject to a reference transcriptomic control. In some embodiments, the computer processing comprises comparing the genomic profile of the subject to a reference genomic control. In some embodiments, the computer processing comprises comparing the exomic profile of the subject to a reference exomic control. In some embodiments, the computer processing comprises analyzing one or more pathways. In some embodiments, the one or more pathways comprise p53 signaling pathway, Ras signaling pathway, Calcium signaling pathway, cAMP signaling pathway, Hippo signaling pathway, JAK- STAT signaling pathway, MAPK signaling pathway, mTOR signaling pathway, Notch signaling pathway, PI3K-Akt signaling pathway, TGF-beta signaling pathway, VEGF signaling pathway, Wnt signaling pathway, or a combination thereof. In some embodiments, the one or more pathways comprise health condition-associated pathways. In some embodiments, the one or more health-condition associated pathways comprises a urea pathway, a cytochrome p450 drug metabolism pathway, a surfactant pathway, a proteoglycan pathways, a collagen synthesis pathway, a keratan sulfate pathway, a uric acid synthesis pathway, a glycan biosynthesis pathway, an insulin pathway, a glucagon synthesis pathway, an insulin resistance pathway, a hemoglobin pathway, a ceramide pathway, a phosphatidylcholine pathway, a myelin synthesis pathway, a melanin synthesis pathway, a dermatan sulfate pathway, an androgen biosynthesis pathway, a progesterone synthesis pathway, an estrogen synthesis pathway, a testosterone metabolism pathway, a thyroid hormone synthesis pathway, a fatty acid metabolism pathway, an adrenaline pathway, a cortisol synthesis pathway, a hyaluronan synthesis pathway, a chondroitin sulfate metabolism pathway, or a creatinine pathway, or a combination thereof. In some WSGR Docket No. 63688-708.601 embodiments, the method further comprises determining one or more upregulated genes and one or more downregulated genes in the one or more pathways. In some embodiments, the one or more upregulated genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes. In some embodiments, the one or more downregulated genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes. In some embodiments, the method further comprises comparing the one or more upregulated genes and the one or more downregulated genes to a reference biological sample obtained or derived from a subject known not to have the health condition. In some embodiments, the method further comprises determining one or more adverse genes and one or more non-adverse genes in the one or more pathways. In some embodiments, the one or more adverse genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes. In some embodiments, the one or more non-adverse genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, WSGR Docket No. 63688-708.601 about 75,000 genes, or about 100,000 genes. In some embodiments, the method further comprises comparing the one or more adverse genes and the one or more non-adverse genes to a reference biological sample obtained or derived from a subject known not to have the health condition. In some embodiments, the computer processing comprises use of a machine learning model. In some embodiments, the machine learning model comprises use of a trained machine learning algorithm. In some embodiments, the organ or the tissue impacted by the health condition comprises an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, a bone marrow, testis, a liver, a kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, or a lymphoid organ. In some embodiments, the health condition comprises a risk of the subject having the health condition. In some embodiments, the method further comprises determining the risk of the subject having the health condition with an accuracy of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more. In some embodiments, the method further comprises determining the risk of the subject having the health condition with a sensitivity of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more. In some embodiments, the method further comprises identifying the subject as having an elevated risk of having the health condition. In some embodiments, the method further comprises identifying the subject as not having an elevated risk of having the health condition. In some embodiments, the method further comprises, responsive to the health condition determined in f), administering a treatment to the subject thereby treating the cancer. In some embodiments, the treatment comprises surgical resection, chemotherapy, targeted therapy, systemic therapy, radiation therapy, immunotherapy, or a combination thereof. In some embodiments, the method further comprises, responsive to the absence of the health condition, modifying a treatment to the subject. In some embodiments, the modifying the treatment comprises modifying a treatment dose of the treatment.

[0019]

[0016] In an aspect, the present disclosure provides methods of determining a health condition of a subject, the method comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a health condition negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from WSGR Docket No. 63688-708.601 the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; j) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; k) enriching a third population of stem cells or progenitor cells in the third biological sample; 1) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; m) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; n) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject; and o) determining, based at least in part on the computer processing, the health condition of the subject.

[0020]

[0017] In an aspect, the present disclosure provides methods of determining a health condition of a subject, the method comprising; a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a health condition negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; j) enriching a third population of stem cells or progenitor cells in the third biological sample; k) extracting third nucleic acids from the enriched WSGR Docket No. 63688-708.601 third population of stem cells or progenitor cells; 1) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; m) averaging (i) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, (ii) the second genomic profile of the subject, or the second exomic profile of the subject and (iii) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; n) obtaining a fourth biological sample obtained or derived from the subject at a fourth time point that is subsequent to the first, second, and third time points; o) enriching a fourth population of stem cells or progenitor cells in the fourth biological sample; p) extracting fourth nucleic acids from the enriched fourth population of stem cells or progenitor cells; q) assaying the extracted third nucleic acids to generate at least one of a fourth transcriptomic profile of the subject, a fourth genomic profile of the subject, or a fourth exomic profile of the subject; r) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the fourth transcriptomic profile of the subject, the fourth genomic profile of the subject, or the fourth exomic profile of the subject; and s) determining, based at least in part on the computer processing, the health condition of the subject.

[0021] INCORPORATION BY REFERENCE

[0022]

[0018] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

[0023] BRIEF DESCRIPTION OF THE DRAWINGS

[0024]

[0019] FIG. 1 shows a computer system that is programmed or otherwise configured to implement methods provided herein.

[0025]

[0020] FIG. 2 shows an example of a blood processing workflow used in the methods and systems herein.

[0026]

[0021] FIG. 3 shows an example of a cell gating workflow used in the methods and systems herein.

[0027]

[0022] FIG. 4 shows an example of a workflow used in the methods and systems herein.

[0028]

[0023] FIG. 5 shows an example of a diagram illustrating an example workflow used in the method and systems herein. WSGR Docket No. 63688-708.601

[0029]

[0024] FIG. 6 shows a graph illustrating a comparison between FSC-A (x 1000) (x-axis) and SSC- A (xlOOO) (y-axis). 2-8p cells, Cells of interest (COI) were captured using size-based gating.

[0030]

[0025] FIG. 7 shows a graph illustrating CD45-Vio Blue-A (x-axis) and toct4-R-PE-A (y-axis). The graph in FIG. 7 was derived from a COI population. tOCT4 positive stained cells constitute 0.01% of the whole population and the remaining 99.99% include the cancer stem cells (CSCs), very small embryonic like stem cells (VSELs), progenitor cells and mature cells.

[0031]

[0026] FIG. 8A shows an example of a first representation of 12 pathways in cancer. This first representation is unmarked, showing the pathways and the connections between the genes.

[0032]

[0027] FIG. 8B shows an example of a second representation of 12 pathways in cancer. This second representation is marked with red and green genes, and is an example of what a subject’s pathways analysis may look like. Green genes are genes that may be either upregulated or downregulated, but in a non-adverse fashion. Red genes are genes that may be upregulated or downregulated, but in a manner that is adverse to the subject.

[0033]

[0028] FIGs. 9A-9B show an example of a workflow used in the methods and systems used herein.

[0034]

[0029] FIG. 10A shows an example of a flow diagram showing pathways in cancer.

[0035]

[0030] FIG. 10B shows an example of a flow diagram showing pathways in non-cancer.

[0036]

[0031] FIG. 11 shows an example of a control selection workflow used in the methods and systems herein.

[0037]

[0032] FIG. 12 shows an example of a workflow used in the method and systems herein.

[0038]

[0033] FIG. 13 shows an example of a workflow for gene panel development used in the methods and systems herein.

[0039]

[0034] FIG. 14 shows an example of a workflow used in the methods and systems here.

[0040]

[0035] FIG. 15A shows an example of a flow diagram showing pathways in insulin secretion in a diabetic subject.

[0041]

[0036] FIG. 15B shows an example of a flow diagram showing pathways in insulin secretion in a pre-diabetic subject.

[0042]

[0037] FIG. 15C shows an example of a flow diagram showing pathways in insulin secretion in a control subject.

[0043]

[0038] FIG. 16A shows an example of a flow diagram showing pathways in Alzheimer’s Disease (AD) in a control subject without AD.

[0044]

[0039] FIG. 16B shows an example of a flow diagram showing pathways in AD in a subject with AD.

[0045]

[0040] FIG. 17A shows an example of a flow diagram showing pathways in lipids and atherosclerosis in a control subject that does not have atherosclerosis. WSGR Docket No. 63688-708.601

[0046]

[0041] FIG. 17B shows an example of a flow diagram showing pathways in lipids and atherosclerosis in a subject having a risk of atherosclerosis or high cholesterol levels.

[0047]

[0042] FIG. 17C shows an example of a flow diagram showing pathways in lipids and atherosclerosis in a subject having coronary artery disease.

[0048]

[0043] FIG. 18A shows an example of a flow diagram showing pathways in non-alcoholic fatty liver disease in a control subject that does not have non-alcoholic fatty liver disease.

[0049]

[0044] FIG. 18B shows an example of a flow diagram showing pathways in non-alcoholic fatty liver disease in a subject having mild fatty liver.

[0050]

[0045] FIG. 19A shows an example of a flow diagram showing pathways in cancer in a control subject.

[0051]

[0046] FIG. 19B shows an example of a flow diagram showing pathways in cancer in a cancer subject that is treatment naive.

[0052]

[0047] FIG. 19C shows an example of a flow diagram showing pathways in cancer in a cancer subject that is on treatment.

[0053]

[0048] FIG. 19D shows an example of a flow diagram showing pathways in cancer in a subject that is a cancer survivor.

[0054]

[0049] FIG. 20A shows an example of a flow diagram showing pathways in neurodegeneration (multiple diseases) in a subject that has absence of neurodegeneration (NDD).

[0055]

[0050] FIG. 20B shows an example of a flow diagram showing pathways in neurodegeneration (multiple diseases) in a subject that has a risk of neurodegeneration.

[0056]

[0051] FIG. 20C shows an example of a flow diagram showing pathways in neurodegeneration (multiple diseases) in a subject that has a presence of neurodegeneration.

[0057]

[0052] FIG. 21A shows an example of a flow diagram showing a pathway in cancer (PIC) of a subject in April 2024 (day of surgery).

[0058]

[0053] FIG. 21B shows an example of a flow diagram showing PIC of a subject in July 2024 (2.5 months after the April 2024 surgery).

[0059]

[0054] FIG. 22A shows a table illustrating adversely dysregulated genes and non-adversely dysregulated genes, as well as risk classifications.

[0060]

[0055] FIG. 22B shows a pathway analysis of adversely dysregulated genes and non-adversely dysregulated genes in 13 pathways, as well as a change in risk profile.

[0061]

[0056] FIG. 22C shows a gene panel analysis of adversely dysregulated genes and non-adversely dysregulated genes in 13 gene panels, as well as a change in risk profile.

[0062]

[0057] FIG. 22D shows a graph illustrating a correlation between genes.

[0063]

[0058] FIG. 22E shows an organ-specific cancer panel analysis of adversely dysregulated genes and non-adversely dysregulated genes in 5 gene panels, as well as a change in risk profile. WSGR Docket No. 63688-708.601

[0064]

[0059] FIG. 23 shows example of graphs including combined ROC curves for cancer gene panels and combined ROC curves for component pathways.

[0065] DETAILED DESCRIPTION

[0066]

[0060] Methods and systems disclosed herein relate to the detection of a cancer status of a subject. In some embodiments, a cancer status may include a cancer or a non-cancer (e.g., a non- cancerous disease or condition). In some embodiments, the methods and systems disclosed herein relate to detection of a cancer status comprising a blood-based biopsy test, also referred to herein as “B3” or “Blood Based Biopsy.”

[0067]

[0061] Genetic testing may be able to assist in the detection or diagnosis of a multitude of diseases, disorders, or conditions. Existing genetic blood tests may be focused on deoxyribonucleic acid (DNA) analysis. As such, these genetic blood tests may be limited to showing somatic and germline predispositions for a disease rather than a current status of the disease. In addition, ribonucleic acid (RNA) analysis may be predominantly conducted on tissue samples. While RNA analysis may be able to show a current status of a disease, it may be limited to the specific tissue or organ from which the sample is derived. Further, tissue sample may be obtained via invasive methods that may not be repeated regularly or that are traumatic to obtain. Further, both RNA and DNA analysis techniques may be time consuming and expensive to conduct. These techniques, singularly or in combination, are limited in their ability to detect the current status of a disease and / or the health status of one or more organs.

[0068]

[0062] In one aspect, provided herein are methods of determining a cancer status of a subject, the method comprising: obtaining a biological sample obtained or derived from the subject; enriching a population of stem cells and / or progenitor cells in the biological sample; extracting nucleic acids from the enriched population of stem cells and / or progenitor cells; assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, and / or an exomic profile of a subject; computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, and / or the exomic profile of a subject; and determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or an absence of an organ or a tissue impacted by the cancer.

[0069]

[0063] In another aspect, provided herein are methods of determining a health status of an organ or a tissue of a subject, the method comprising: obtaining a biological sample obtained or derived from the subject; enriching a population of cells in the biological sample, wherein the population of cells comprises one or more of stem cells and / or progenitor cells; extracting nucleic acids from the enriched population of cells; assaying the extracted nucleic acids to generate at least WSGR Docket No. 63688-708.601 one of a transcriptomic profile of the subject, a genomic profile of the subject, and / or an exomic profile of the subject; computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, and / or the exomic profile of the subject; and determining based at least in part on the computer processing, the health status of the organ or the tissue of the subject.

[0070]

[0064] In another aspect, provided herein are methods of determining a cancer status of a subject, the method comprising: obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; enriching a first population of stem cells and / or progenitor cells in the first biological sample; extracting first nucleic acids from the enriched first population of stem cells and / or progenitor cells; assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile, a first genomic profile, and / or a first exomic profile of the subject; obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; enriching a second population of stem cells and / or progenitor cells in the second biological sample; extracting second nucleic acids from the enriched second population of stem cells and / or progenitor cells; assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile, a second genomic profile, and / or a second exomic profile of the subject; averaging the at least one of the first transcriptomic profile, the first genomic profile, and / or the first exomic profile of the subject with the at least one of the second transcriptomic profile, the second genomic profile, and / or the second exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, and / or a baseline exomic profile; obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; enriching a third population of stem cells and / or progenitor cells in the third biological sample; extracting third nucleic acids from the enriched third population of stem cells and / or progenitor cells; assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile, a third genomic profile, and / or a third exomic profile of the subject; computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, and / or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile, the third genomic profile, and / or the third exomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status of the subject.

[0071]

[0065] In another aspect, provided herein are methods of determining a cancer status of a subject, the method comprising: obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; enriching a first population of stem cells and / or progenitor cells in the first biological sample; extracting first WSGR Docket No. 63688-708.601 nucleic acids from the enriched first population of stem cells and / or progenitor cells; assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile, a first genomic profile, and / or a first exomic profile of the subject; obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; enriching a second population of stem cells and / or progenitor cells in the second biological sample; extracting second nucleic acids from the enriched second population of stem cells and / or progenitor cells; assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile, a second genomic profile, and / or a second exomic profile of the subject; obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; enriching a third population of stem cells and / or progenitor cells in the third biological sample; extracting third nucleic acids from the enriched third population of stem cells and / or progenitor cells; assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile, a third genomic profile, and / or a third exomic profile of the subject; averaging the at least one of the first transcriptomic profile, the first genomic profile, and / or the first exomic profile of the subject with the at least one of the second transcriptomic profile, the second genomic profile, and / or the second exomic profile of the subject and with the at least one of the third transcriptomic profile, the third genomic profile, and / or the third exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, and / or a baseline exomic profile; obtaining a fourth biological sample obtained or derived from the subject at a fourth time point that is subsequent to the first, second, and third time points; enriching a fourth population of stem cells and / or progenitor cells in the fourth biological sample; extracting fourth nucleic acids from the enriched fourth population of stem cells and / or progenitor cells; assaying the extracted third nucleic acids to generate at least one of a fourth transcriptomic profile, a fourth genomic profile, and / or a fourth exomic profile of the subject; computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, and / or the baseline exomic profile of the subject, and (2) the at least one of the fourth transcriptomic profile, the fourth genomic profile, and / or the fourth exomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status of the subject.

[0072]

[0066] In another aspect, provided herein are methods of determining an effect of a therapeutic on a subject, the method comprising: obtaining a first biological sample obtained or derived from the subject at a first time point; enriching a first population of stem cells and / or progenitor cells in the first biological sample; extracting first nucleic acids from the enriched first population of stem cells and / or progenitor cells; assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, and / or a WSGR Docket No. 63688-708.601 first exomic profile of a subject; administering the therapeutic to the subject; obtaining a second biological sample obtained or derived from the subject at a second time point subsequent to the administering; enriching a second population of stem cells and / or progenitor cells in the second biological sample; extracting second nucleic acids from the enriched second population of stem cells and / or progenitor cells; assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, and / or a second exomic profile of a subject; computer processing (1) the at least one of the first transcriptomic profile, the first genomic profile, and / or the first exomic profile of the subject and (2) the at least one of the second transcriptomic profile, the second genomic profile, and / or the second exomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status of the subject. In some embodiments, the selection of the therapeutic administered may or may not be informed at least in part by the first transcriptomic profile, first genomic profile, and / or first exomic profile of the subject.

[0073]

[0067] In another aspect, provided herein are methods of determining a health condition of a subject, the method comprising: obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a health condition negative status; enriching a first population of stem cells and / or progenitor cells in the first biological sample; extracting first nucleic acids from the enriched first population of stem cells and / or progenitor cells; assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, and / or a first exomic profile of the subject; obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; enriching a second population of stem cells and / or progenitor cells in the second biological sample; extracting second nucleic acids from the enriched second population of stem cells and / or progenitor cells; assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, and / or a second exomic profile of the subject; averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, and / or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, and / or the second exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, and / or a baseline exomic profile of the subject; obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; enriching a third population of stem cells and / or progenitor cells in the third biological sample; extracting third nucleic acids from the enriched third population of stem cells and / or progenitor cells; assaying the extracted third WSGR Docket No. 63688-708.601 nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, and / or a third exomic profile of the subject; computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, and / or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, and / or the third exomic profile of the subject; and determining, based at least in part on the computer processing, the health condition of the subject.

[0074]

[0068] In another aspect, provided herein are methods of determining a health condition of a subject, the method comprising: obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a health condition negative status; enriching a first population of stem cells and / or progenitor cells in the first biological sample; extracting first nucleic acids from the enriched first population of stem cells and / or progenitor cells; assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, and / or a first exomic profile of the subject; obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; enriching a second population of stem cells and / or progenitor cells in the second biological sample; extracting second nucleic acids from the enriched second population of stem cells and / or progenitor cells; assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, and / or a second exomic profile of the subject; obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; enriching a third population of stem cells and / or progenitor cells in the third biological sample; extracting third nucleic acids from the enriched third population of stem cells and / or progenitor cells; assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, and / or a third exomic profile of the subject; averaging (i) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, and / or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, (ii) the second genomic profile of the subject, and / or the second exomic profile of the subject and (iii) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, and / or the third exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, and / or a baseline exomic profile of the subject; obtaining a fourth biological sample obtained or derived from the subject at a fourth time point that is subsequent to the first, second, and third time points; enriching a fourth population of stem cells and / or progenitor cells in the fourth WSGR Docket No. 63688-708.601 biological sample; extracting fourth nucleic acids from the enriched fourth population of stem cells and / or progenitor cells; assaying the extracted third nucleic acids to generate at least one of a fourth transcriptomic profile of the subject, a fourth genomic profile of the subject, and / or a fourth exomic profile of the subject; computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, and / or the baseline exomic profile of the subject, and (2) the at least one of the fourth transcriptomic profile of the subject, the fourth genomic profile of the subject, and / or the fourth exomic profile of the subject; and determining, based at least in part on the computer processing, the health condition of the subject.

[0075]

[0069] In another aspect, provided herein are methods of assessing an effect of a therapeutic, the method comprising: assaying a first expression profile of a first biological sample obtained or derived from a subject at a first time point to thereby produce a first transcriptomic profile of the subject; administering the therapeutic to the subject; assaying a second expression profile of a second biological sample obtained or derived from the subject at a second time point subsequent to the administering of b) to thereby produce a second transcriptomic profile of the subject; comparing, using a computer, the first and second transcriptomic profiles of the subject; and assessing the effect of the therapeutic based at least in part of the comparing.

[0076]

[0070] In another aspect, provided herein are computer systems for determining a cancer status of a subject, the system comprising: a non-transitory memory; and a processor in communication with the non-transitory memory, the processor configured to execute the following operations in order to effectuate a method comprising the operations of: obtaining a biological sample obtained or derived from the subject; enriching a population of stem cells and / or progenitor cells in the biological sample; extracting nucleic acids from the enriched population of stem cells and / or progenitor cells; assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject and a genomic profile of the subject; computer processing the at least one of the transcriptomic profile of the subject and the genomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or an absence of an organ or a tissue impacted by the cancer

[0077]

[0071] In yet another aspect, provided herein is a non-transitory computer-readable memory storing one or more instructions executable by one or more processors, that when executed by the one or more processors cause the one or more processors to perform processing of a method comprising: obtaining a biological sample obtained or derived from the subject; enriching a population of stem cells and / or progenitor cells in the biological sample; extracting nucleic acids from the enriched population of stem cells and / or progenitor cells; assaying the extracted nucleic WSGR Docket No. 63688-708.601 acids to generate at least one of a transcriptomic profile of the subject and a genomic profile of the subject; computer processing the at least one of the transcriptomic profile of the subject and the genomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or an absence of an organ or a tissue impacted by the cancer.

[0078]

[0072] The disclosed methods and systems comprise advantages in cancer detection in a subject, as well as an organ and / or tissue impacted by such cancer.

[0079]

[0073] One advantage of the methods and systems disclosed herein is a liquid biopsy, blood-based test with little to no side effects in subjects or waiting periods for subjects between tests. This advantage may be particularly helpful for a cancer subject (e.g., cancer survivors or subjects on cancer treatment) or subjects that may not be able to undergo multiple invasive procedures.

[0080]

[0074] An additional advantage of the methods and systems disclosed herein is the ability of a blood-based test to obtain information about all organs in a single, non-invasive test (rather than undergo separate, invasive tissue biopsies that may provide information about one organ at a time).

[0081]

[0075] An additional advantage of the methods and systems disclosed herein is the detection of cancers at an early stage of the cancer (e.g., when the cancer is nascent or when the cancer is at an early stage (e.g., stage 0 cancer, stage I cancer, or stage II cancer)).

[0082]

[0076] An additional advantage of the methods and systems disclosed herein relates to issues of sample heterogeneity. For example, use of a tissue biopsy has heterogeneity issues since the biopsy can only obtain information about a tumor by analyzing the portion of the sample biopsied (rather than the whole tumor). In contrast, the methods and systems disclosed herein can obtain information about the whole tumor through a non-invasive approach, rather than just a portion of the tumor.

[0083]

[0077] An additional advantage of the methods and systems disclosed herein is the identification of an organ or a tissue impacted by the cancer. For example, the methods and systems disclosed herein may identify one or more organs and / or tissues impacted by a cancer. As such, the methods and systems may identify the organ / tissue origin of the cancer (e.g., the primary organ / tissue). This advantage may be particularly helpful in identifying the primary site of the cancer in subjects for whom performing an invasive biopsy may not be possible, for example, due to high vascularization or limited access to the tumor site.

[0084]

[0078] An additional advantage of the methods and systems disclosed herein is the identification of one or more organs and / or tissues impacted by multiple lesions or satellite lesions.

[0085]

[0079] An additional advantage of the methods and systems disclosed herein is the identification of mutational signatures of the cancer. WSGR Docket No. 63688-708.601

[0086]

[0080] An additional advantage of the methods and systems disclosed herein is the determination of the next target organ of a cancer. For example, the methods and systems may first identify the origin of the cancer (e.g., the organ / tissue origin of the cancer). The methods and systems may identify the metastatic potential of the cancer. The methods and systems may identify the next target organ or tissue of the cancer.

[0087]

[0081] An additional advantage of the methods and systems disclosed herein is the determination of a residual disease or condition in a cancer subject, including, but not limited to, minimal residual disease (MRD). This advantage may be particularly helpful in determining a cancer remission or cancer recurrence status, as well as monitoring a subject’s response to a particular therapy.

[0088]

[0082] An additional advantage of the methods and systems disclosed herein is the determination of a health status of an organ and / or tissue that has not been impacted by a cancer that is active in a cancer subject. This advantage may be particularly helpful for cancer subjects in determining a treatment (e.g., a treatment type, a treatment dosage, treatment combinations, and / or a duration / length of a treatment).

[0089]

[0083] An additional advantage of the methods and systems disclosed herein is the active determination of a state of non-cancer in a subject (e.g., a cancer status comprising a noncancer). For example, whereas other methods of cancer detection actively determine the presence of cancer and assume an absence of cancer if cancer was not detected, the methods and systems disclosed herein may make an active determination for the presence of cancer and also an active determination of a state of non-cancer, including an active determination of the state of organ health of a subject as a confirmation of the state of non-cancer (e.g. if a subject is presenting symptoms and / or has an indeterminate result from an alternate test, such as an HrC test, and the methods and systems disclosed herein have indicated a state of non-cancer (e.g., a non-cancer cancer status), an active determination of a possible non-cancer disease or condition of an organ that may explain the subject’s symptoms can be used as a confirmatory method in the determination of a state of non-cancer).

[0090]

[0084] An additional advantage of the methods and systems disclosed herein is the enhanced sensitivity and / or specificity of the detection of cancer. For example, an enhanced accuracy of detecting a cancer in a subject is disclosed herein.

[0091]

[0085] An additional advantage of the methods and systems disclosed herein is the enhanced ability to determine and monitor cancer treatment for a subject. For example, the transcriptomic profile, genomic profile, and / or exomic profile of the subject can be compared with different drug options, which may inform the selection of a therapeutic option. As another example, a treating practitioner (e.g., an oncologist) may choose to target cancer pathways one at a time, WSGR Docket No. 63688-708.601 completing treatments for one pathway and observing the success before moving on to an additional pathway, and monitor the progress of treatments via regular testing. As another example, due to the pathways altering before a tumor changes, the B3(Blood Based Biopsy) may be conducted in synchronization with additional tests (e.g., a PET scan) to monitor the effectiveness of a treatment for cancer as B3can detect smaller and more immediate changes or lack thereof.

[0092]

[0086] An additional advantage of the methods and systems disclosed herein is the enhanced ability to be able to conduct trials on potentially new cancer drugs and treatments by providing an ability to test for a broader scope of information about the impact of a therapeutic in a single test. Additionally, the methods and systems disclosed herein may be able to repeat testing over time more easily.

[0093]

[0087] Further, the disclosed methods and systems comprise advantages in the detection of a disease, disorder, or condition. The disease, disorder, or condition may be in an organ and / or a tissue in a subject. The disclosed methods and systems further comprise detection of a health status of an organ and / or tissue impacted by a disease, disorder, or condition.

[0094]

[0088] One advantage of the methods and systems disclosed herein is the ability of a single bloodbased test to obtain information about all organs non-invasively, rather than undergo separate, invasive tissue biopsies in order to obtain information about each organ one at a time.

[0095]

[0089] An additional advantage of the methods and systems disclosed herein is a blood-based test with little to no side effects in subjects or waiting periods for subjects between tests.

[0096]

[0090] An additional advantage of the methods and systems disclosed herein is the enhanced ability to determine the organ health status of one or more organs or tissues, including organs that are not presenting symptoms, when investigating or monitoring a condition. For example, a person with chronic hepatitis C can use the B Cube test to determine the organ health status of their liver, and also any other organs that may have become impacted by the disease, in a single blood test. This may also include the determination that the organ and / or tissue has not been impacted by a disease, disorder or condition.

[0097]

[0091] An additional advantage of the methods and systems disclosed herein is the determination of a condition, disease or disorder that is difficult or impossible to diagnose via conventional methods. For example, the average time taken to diagnose the condition endometriosis via existing methods is 6 to lOyears. The B Cube test can determine the condition from a single B Cube blood test.

[0098]

[0092] An additional advantage of the methods and systems disclosed herein is an enhanced ability to detect conditions, diseases and disorders at an early stage, including at an asymptomatic stage, before they develop and manifest across the whole system. WSGR Docket No. 63688-708.601

[0099]

[0093] An additional advantage of the methods and systems disclosed herein is the enhanced ability to determine and monitor treatment for a subject. For example, the type of treatment, treatment dosage, treatment combinations, and / or the duration or length of a treatment may be informed by the organ health status of both impacted and non-impacted organs. This may include the existence of comorbidities such as a heart condition, liver damage, or other conditions. As another example, the transcriptomic profile, genomic profile, and / or exomic profile of the subject can be compared with different drug options, which may inform the selection of a therapeutic option. As another example, a treating practitioner may choose to target metabolic pathways one at a time, completing treatments for one pathway and observing the success before moving on to an additional pathway, and monitor the progress of treatments via regular testing. As another example, a series of B Cube tests can be used to monitor changes in the drug pathways as a treatment progresses to determine the efficacy of the treatment as soon as it has occurred. As another example, the B3(Blood Based Biopsy) may be conducted in synchronization with additional tests to monitor the effectiveness of a treatment as B3can detect small and / or immediate changes or lack thereof. As another example, healthy organs can be monitored while treatment is occurring to ensure that they are not impacted, and that no sideeffects as a result of the treatment are occurring.

[0100]

[0094] An additional advantage of the methods and systems disclosed herein is the enhanced ability to be able to conduct trials on potentially new drugs and treatments by providing an ability to test for a broader scope of information about the impact of a therapeutic in a single test. Additionally, the methods and systems disclosed herein may be able to repeat testing over time more easily.

[0101]

[0095] An additional advantage of the methods and systems disclosed herein is the ability to create individualized B Cube gene panels and scoring systems and provide personalized medicine to individual subjects, tailored to their specific genetics and conditions. For example, subjects who have rare diseases can have the disease detected via a B Cube test. In another example, subjects who have a rare disease for which there are no targeted therapies, can have their generalized therapy options monitored closely via repeated testing to determine the efficacy of the treatments in “real time”, and to offer the ability to adjust treatments based on the impact the treatments are having. In another example, treating practitioners are better able to tailor adjuvant therapies for treatments given.

[0102]

[0096] An additional advantage of the methods and systems disclosed herein is an enhanced ability to conduct relapse assessment for patients who have recovered from a condition. WSGR Docket No. 63688-708.601

[0103] METHODS

[0104] Determining a cancer status or a health status of an organ and / or a tissue

[0105]

[0097] Disclosed herein are methods for determining a cancer status. The methods may comprise determining a health status of an organ, a tissue, or a combination thereof. The methods may comprise obtaining a biological sample. The biological sample may be obtained from a subject. The biological sample may be derived from a subject. The methods may comprise enriching a population of cells in a biological sample. The population of cells may comprise stem cells. The population of cells may comprise progenitor cells. The population of cells may comprise stem cells and progenitor cells. The methods may comprise extracting nucleic acids from a population of cells. The population of cells may be an enriched population of stem cells and / or progenitor cells. The methods may comprise assaying nucleic acids to generate a transcriptomic profile of a subject. The methods may comprise assaying nucleic acids to generate a genomic profile of a subject. The methods may comprise assaying nucleic acids to generate an exomic profile of a subject. The nucleic acids may be extracted. The methods may comprise computer processing. The computer processing may comprise computer processing a transcriptomic profile of a subject. The computer processing may comprise computer processing a genomic profile of a subject. The computer processing may comprise computer processing an exomic profile of a subject. The computer processing may comprise computer processing a transcriptomic profile of a subject, a genomic profile of a subject, and an exomic profile of a subject. The methods may comprise determining, based at least in part on computer processing, a cancer status of a subject or a health status of an organ, a tissue, or a combination thereof. The cancer status may comprise a presence or an absence of an organ or a tissue impacted by the cancer. The cancer status may comprise the health status or an organ or tissue when cancer is present or absent. The health status may comprise a presence or an absence of a disease, disorder, or condition, or a combination thereof, of an organ or a tissue, or a combination thereof.

[0106]

[0098] The method may comprise obtaining a biological sample. The biological sample may comprise a blood sample, a fraction of a blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample. The biological sample may be a blood sample. The biological sample may be a fraction of the blood sample. For example, the biological sample may be more than or equal to 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the blood sample. As another example, the biological sample may be less than or equal to 95%, 90%, 85%, 80%, 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, or 5% of the blood sample. The biological sample may be a plasma sample. The biological sample may be a serum sample. The biological sample may be a urine sample. The biological sample may be a saliva sample. The biological sample may be a tissue WSGR Docket No. 63688-708.601 sample. The biological sample may be a tumor biopsy sample. The biological sample may be a vaginal discharge sample. The biological sample may be a sweat sample. The biological sample may be a semen sample. The biological sample may be a cell-free sample. The cell-free sample may comprise cell-free ribonucleic acid (cf-RNA), such as cell-free mRNA (cf-mRNA). The biological sample may be a bone marrow sample. The biological sample may comprise nucleic acids, for example deoxyribonucleic acid (DNA) or ribonucleic acid (RNA).

[0107]

[0099] The biological sample may comprise deoxyribonucleic acid (DNA). The DNA may be single stranded DNA. The DNA may be double stranded DNA. The DNA may be single stranded or double stranded. The DNA may be autosomal DNA. The DNA may be mitochondrial DNA. The DNA may be coding DNA. The DNA may be non-coding DNA.

[0108]

[0100] The biological sample may comprise ribonucleic acid (RNA). Non-limiting examples of RNA include messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). The RNA may comprise small nuclear RNAs (snRNAs), micro RNAs (miRNAs), or small interfering RNAs (siRNAs). The RNA may be cell-free RNA. The cell-free RNA may be cell- free mRNA. The RNA may be pre-mRNA. The RNA may comprise a coding region. The RNA may comprise a non-coding region.

[0109]

[0101] The biological sample may comprise proteins. Non-limiting examples of proteins include globulin proteins, fibrinogen proteins, albumin proteins, prothrombin proteins, and immunoglobulin proteins.

[0110]

[0102] The methods may comprise obtaining a biological sample from a subject. The biological sample may be obtained from the subject. The biological sample may be derived from the subject. The subject may be a mammal, for example a human, a non-human primate, a rodent (e.g., a rat, a mouse, a guinea pig, a hamster, or other similar rodents), a dog, a feline, a pig, a sheep, a cow, a goat, or a rabbit. The subject may be a fish, a bird, or a reptile. The subject may be a human. The subject may be an adult (e.g., a human of 18 years of age or older). The subject may be a child (e.g., a human of 18 years of age or less). The subject may comprise an age of greater or equal to 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100. The subject may be about 30 years of age. The subject may be about 40 years of age. The subject may be about 50 years of age. The subject may be about 53 years of age. The subject may be about 56 years of age. The subject may be about 59 years of age. The subject may be about 60 years of age. The subject may be about 63 years of age. The subject may be about 66 years of age. The subject may be about 69 years of age. The subject may be about 70 years of age. The subject may be suspected of having a cancer. The subject may be suspected of having a disease, disorder, or condition, or a combination thereof. The subject may be suspected of having one or more cancers, diseases, disorders, conditions, or a combination thereof, for WSGR Docket No. 63688-708.601 example, one or more, two or more, three or more, four or more, or five or more cancers, diseases, disorders, or conditions, or a combination thereof. The subject may be predisposed to having a cancer, a disease, a disorder, or a condition. The subject may have one or more symptoms of a cancer, a disease, a disorder, or a condition. The subject may be suspected of having a disease or condition, such as an infectious disease, a deficiency disease, a hereditary disease (e.g., genetic, or non-genetic), or a physiological disease. The subject may be suspected of having one or more diseases, for example, one or more, two or more, three or more, four or more, or five or more diseases. The subject may be predisposed to having a disease. The subject may have one or more symptoms of a disease. The subject may be asymptomatic. A subject may not be suspected of having one or more diseases or conditions. The subject may be a cancer survivor. The subject may be in cancer remission.

[0111]

[0103] The methods may include determining a cancer status in a subject. The methods may comprise determining a health status of an organ, a tissue, or a combination thereof. The cancer may comprise a presence or an absence of the cancer. The cancer may comprise one or more cancers, for example, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more cancers. The cancer may comprise a combination of cancers or a combination of cancer types. Non-limiting examples of cancers may include breast cancer, liver cancer, ovarian cancer, lung cancer, renal cancer, bladder cancer, prostate cancer, pancreatic cancer, cervical cancer, color cancer, testicular cancer, thyroid cancer, bile duct cancer, esophageal cancer, skin cancer, kidney cancer, or endometrial cancer. The cancer may comprise carcinoma, myeloma, leukemia, lymphoma, or sarcoma. The cancer may comprise acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), adrenocortical carcinoma, AIDS-related cancers, anal cancer, appendix cancer, brain cancer, bone cancer, bronchial cancer, cervical cancer, chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), chronic myeloproliferative neoplasms, colorectal cancer (CLC), uterine cancer, esophageal cancer, eye cancer (e.g., intraocular melanoma, retinoblastoma, etc.), fallopian tube cancer, gallbladder cancer, gastrointestinal neuroendocrine tumors, germ cell tumors, testicular cancer, ovarian cancer, head cancer, neck cancer, lip and oral cavity cancer, metastatic cancers, neuroblastoma, non-small cell lung cancer (NSCLC), pancreatic cancer, penile cancer, parathyroid cancer, pharyngeal cancer, prostate cancer, pulmonary inflammatory myofibroblast tumor, rectal cancer, retinoblastoma, salivary gland cancer, small intestine cancer, stomach cancer, urethral cancer, vaginal cancer, vulvar cancer, or the like. The cancer may comprise a stage of the cancer. For example, the cancer may be stage I cancer, stage II cancer, stage III cancer, or stage IV cancer. The cancer may be an early-stage cancer (e.g., stage 0, 1 or II). The cancer may be a late-stage cancer (e.g., stage III or IV). The cancer may be Stage 0 WSGR Docket No. 63688-708.601 cancer / pre-tumor formation. The cancer may be a low-grade (well differentiated) cancer. The cancer may be a high-grade (poorly differentiated) cancer. The cancer may impact one or more organs, for example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more organs. The cancer may impact one or more tissues, for example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more tissues. The cancer may comprise one or more tumors. The cancer may comprise a pre-neoplastic lesion. The cancer may comprise a carcinoma in situ. The cancer may comprise one or more ulcers. The cancer may comprise a disease or condition. In some embodiments, the organ and / or the tissue impacted by the cancer may comprise an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, a bone marrow, testis, a liver, a kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ and / or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, a lymphoid organ, or any combination thereof. The cancer status may comprise a noncancer status. For example, the cancer status may comprise a non-cancerous disease or condition. The organ health status may comprise a presence or an absence of a disease, disorder, or condition, or a combination thereof. The organ health status may comprise one or more diseases, disorders or conditions, for example, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more diseases, disorders or conditions. The organ health status may comprise a combination of diseases, disorders, or conditions or a combination of types of diseases, disorders, or conditions. Non-limiting examples of diseases, disorders or conditions may include pancreatic diseases or conditions, neurodegenerative diseases or conditions, cardiac diseases or conditions, lung diseases or conditions, auto-immune diseases or conditions, lipid related disorders or conditions, liver diseases or conditions, kidney diseases or conditions, bone diseases or conditions, hair diseases or conditions, skin disease or conditions, nail diseases or conditions, endometrial diseases or conditions, or the like. The disease, disorder or condition may impact one or more organs, for example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more organs. The diseases, disorders or conditions may impact all organs. The disease, disorder or condition may impact one or more tissues, for example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more tissues. The diseases, disorders or conditions may impact all tissues. In some embodiments, the organ and / or the tissue impacted by the disease, disorder or condition may comprise an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, bone marrow, a testis, a liver, a WSGR Docket No. 63688-708.601 kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ and / or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, a lymphoid organ, blood, an adipose organ and / or tissue, an autoimmune organ and / or tissue, a heart, a uterus, a biliary organ, an upper respiratory organ, CNS, a spinal cord, a larynx, a gastroesophageal organ, PNS, teeth, cartilage, a reproductive organ, a pituitary gland, a duodenum, a bone, a nasopharynx, an appendix, a cervix, a neuromuscular organ, a thymus, an immunity organ and / or tissue, a penis, a nose, a gonad, an endocrine organ, an ear, or any combination thereof. The organ health status may comprise a status that is free of a disease, disorder or condition.

[0112]

[0104] The cancer may be associated with pancreatic cancer. In some embodiments, the pancreatic cancer may be associated with islet cell tumors, pancreatic neuroendocrine tumors, pancreatic neuroendocrine tumors (e.g., islet cell tumors), or a combination thereof.

[0113]

[0105] The cancer may be associated with lung cancer. In some embodiments, the lung cancer may be associated with bronchial tumors, non-small cell lung cancer (NSCLC), small cell lung cancer, pleuropulmonary blastoma, pulmonary inflammatory myofibroblastic tumors, tracheobronchial tumors, pleuropulmonary blastoma, pulmonary inflammatory myofibroblastic tumors, tracheobronchial tumors, or a combination thereof.

[0114]

[0106] The cancer may be associated with bone marrow cancer. In some embodiments, the bone marrow cancer may be associated with acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), hairy cell leukemia, leukemia, myeloproliferative neoplasms (MPN), myelogenous leukemia chronic (CML), myeloid leukemia, acute (AML), acute promyelocytic leukemia (APL), Ewing sarcoma, Osteosarcoma, malignant fibrous histiocytoma, chordoma, childhood bone cancer, Osteosarcoma, undifferentiated pleomorphic sarcoma of bone treatment, or a combination thereof.

[0115]

[0107] The cancer may be associated with testicular cancer.

[0116]

[0108] The cancer may be associated with liver cancer. In some embodiments, the liver cancer may be associated with hepatocellular cancer, cholangiocarcinoma, or a combination thereof.

[0117]

[0109] The cancer may be associated with kidney cancer. In some embodiments, the kidney cancer may be associated with clear cell renal carcinoma, papillary renal carcinoma, chromophobe renal carcinoma, oncocytoma, collecting duct tumors and renal medullary cancer, unclassified renal cell carcinoma (e.g., unclassified RCC), or a combination thereof.

[0118]

[0110] The cancer may be associated with skin cancer. In some embodiments, the skin cancer may be associated with basal cell carcinoma, squamous cell carcinoma, melanoma, merkel cell carcinoma, or a combination thereof. WSGR Docket No. 63688-708.601

[0119]

[0111] The cancer may be associated with ovarian cancer. In some embodiments, the ovarian cancer may be associated with ovarian germ cell tumors.

[0120]

[0112] The cancer may be associated with thyroid cancer. In some embodiments, the thyroid cancer may be associated with papillary thyroid cancer, follicular thyroid cancer, hurthle cell carcinoma, medullary thyroid carcinoma (MTC), familial medullary thyroid carcinoma, anaplastic carcinoma, or a combination thereof.

[0121]

[0113] The cancer may be associated with colon cancer, rectal cancer, or both. In some embodiments, the colon cancer, rectal cancer, or both, may be associated with adenocarcinoma of colon, gastrointestinal carcinoid tumors, gastrointestinal stromal tumors, anal cancer, appendiceal cancer, large cell neuroendocrine carcinoma, small cell carcinoma, rectal cancer, or a combination thereof.

[0122]

[0114] The cancer may be associated with breast cancer. In some embodiments, the breast cancer may be associated with Luminal A, Luminal B, HER2 positive, Triple Negative, ductal invasive, Invasive lobular carcinoma (ILC), Lobular carcinoma in situ (LCIS), Atypical lobular hyperplasia, or a combination thereof.

[0123]

[0115] The cancer may be associated with urinary bladder cancer. In some embodiments, the urinary bladder cancer may be associated with squamous cell carcinoma, adenocarcinoma, small cell carcinoma, micropapillary, plasmacytoid, or a combination thereof.

[0124]

[0116] The cancer may be associated with gastrointestinal cancer. In some embodiments, the gastrointestinal cancer may be associated with gastrointestinal stromal tumors, esophageal cancer, small intestine cancer, or a combination thereof.

[0125]

[0117] The cancer may be associated with small intestine cancer. In some embodiments, the small intestine cancer may be associated with intestine cancer, adenocarcinoma, gastrointestinal stromal tumor, carcinoid tumors, lymphoma, sarcoma, leiomyosarcoma, or a combination thereof.

[0126]

[0118] The cancer may be associated with esophageal cancer.

[0127]

[0119] The cancer may be associated with salivary gland cancer. In some embodiments, the salivary gland cancer may be associated with mucoepidermoid carcinoma, adenoid cystic carcinoma, acinic cell carcinoma, polymorphous adenocarcinoma, pleomorphic adenomas, Warthin’s tumor, or a combination thereof.

[0128]

[0120] The cancer may be associated with stomach cancer. In some embodiments, the stomach cancer may be associated with non-cardia (distal) stomach cancer, proximal stomach cancer, diffuse stomach cancer, or a combination thereof.

[0129]

[0121] The cancer may be associated with brain cancer. In some embodiments, the brain cancer may be associated with glioma, glioblastoma, primary central nervous system lymphoma, pineal WSGR Docket No. 63688-708.601 region tumors, pituitary tumors, meningioma, acoustic neuroma (vestibular schwannoma), astrocytoma, oligodendroglioma, brain stem glioma, ependymoma, or a combination thereof.

[0130]

[0122] The cancer may be associated with prostate cancer.

[0131]

[0123] The cancer may be associated with lymphoid organ cancer. In some embodiments, the lymphoid organ cancer may be associated with diffuse large B-cell lymphoma, primary mediastinal B cell lymphoma, follicular lymphoma, small lymphocytic lymphoma and chronic lymphocytic leukemia, marginal zone lymphoma, mantle cell lymphoma, Waldenstrom’s macroglobulinemia, Burkitt lymphoma, nodular sclerosis Hodgkin lymphoma, mixed cellularity Hodgkin lymphoma, lymphocyte-rich Hodgkin’s disease, lymphocyte-depleted Hodgkin’s disease, or a combination thereof.

[0132]

[0124] The cancer may be associated with adrenal gland cancer.

[0133]

[0125] The cancer may be associated with parathyroid cancer.

[0134]

[0126] The cancer may be associated with pituitary gland cancer. In some embodiments, the pituitary gland cancer may be associated with pituitary tumors, ACTH-Secreting adenomas, Growth Hormone-Secreting adenomas, Prolactin-Secreting adenomas, TSH-Secreting Pituitary adenomas, Gonadotropin-Secreting adenomas, nonfunctioning pituitary adenomas, or a combination thereof.

[0135]

[0127] The cancer may be associated with eye cancer. In some embodiments, the eye cancer may be associated with uveal or choroidal melanoma, primary intraocular lymphoma, ocular adnexal lymphoma, retinoblastoma, medulloepithelioma, conjunctival intraepithelial neoplasia (CIN), squamous cell cancer of the conjunctiva, melanoma of the conjunctiva and eyelid, or a combination thereof.

[0136]

[0128] The cancer may be associated with endometrium cancer. In some embodiments, the endometrium cancer may be associated with endometrioid adenocarcinoma, adenosquamous carcinoma, carcinosarcoma, serous adenocarcinoma, or a combination thereof.

[0137]

[0129] The cancer may be associated with gall bladder cancer. In some embodiments, the gall bladder cancer may be associated with nonpapillary adenocarcinoma, papillary adenocarcinoma, mucinous adenocarcinoma, or a combination thereof.

[0138]

[0130] The cancer may be associated with bone cancer. In some embodiments, the bone cancer may be associated with Ewing Sarcoma, Osteosarcoma, malignant fibrous histiocytoma, chordoma, childhood bone cancer, undifferentiated pleomorphic sarcoma of bone treatment, or a combination thereof.

[0139]

[0131] The cancer may be associated with tongue cancer.

[0140]

[0132] The cancer status may comprise a presence or an absence of a cancer. The cancer status may comprise a presence or an absence of an organ or a tissue impacted by a cancer. The cancer WSGR Docket No. 63688-708.601 status may comprise a subject having a cancer or more than one cancer. For example, a cancer status may comprise a subject having more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 cancers. The cancer status may comprise a subject having a disease or condition or more than one disease or condition. For example, a cancer status may comprise a subject having more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 diseases or conditions. The cancer status may comprise a presence or an absence of a cancer as disclosed herein. The cancer status may comprise a cancer remission status. The cancer status may comprise a cancer recurrence status. The cancer status may comprise a risk of a subject having a cancer, for example a risk of greater than or equal to 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%,

[0141] 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%,

[0142] 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 99.5%, or 99.9% of the subject having the cancer.

[0143] The cancer status may comprise a presence or an absence of a disease.

[0144]

[0133] The methods disclosed herein may comprise detecting a non-cancerous disease or condition in a subject. One example of a non-cancerous disease or condition is fatty liver disease. Additional examples of non-cancerous diseases or conditions may include comorbidities, diabetes, heart disease, hypertension, mental disorders, Alzheimer’s disease, depression, arthritis, asthma, autoimmune diseases, respiratory diseases, dementia, schizophrenia, kidney diseases, bone diseases, skin diseases, obesity conditions, brain conditions, and the like. Detecting a non-cancerous disease or condition in a subject may confirm that the subject does not have a cancer.

[0145]

[0134] The methods may include determining a health status of an organ and / or a tissue in a subject. The organ health status may comprise a presence or an absence of a disease, disorder, or condition. The organ health status may comprise one or more diseases, disorders, or conditions, for example, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more diseases, disorders, or conditions. The organ health status may comprise a combination of diseases, disorders, or conditions. The organ health status may comprise a combination of types of diseases, disorders, or conditions. Non-limiting examples of diseases, disorders, or conditions may include pancreatic diseases or conditions, neurodegenerative diseases or conditions, cardiac diseases or conditions, lung diseases or conditions, auto-immune diseases or conditions, lipid-related disorders or conditions, liver diseases or conditions, kidney diseases or conditions, bone diseases or conditions, hair diseases or conditions, skin diseases or conditions, nail diseases or conditions, endometrial diseases or conditions, or the like. The disease, disorder, or condition may impact one or more organs in a subject, for example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more organs in a subject. The WSGR Docket No. 63688-708.601 diseases, disorders or conditions may impact all organs of a subject. The disease, disorder, or condition may impact one or more tissues in a subject, for example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more tissues in a subject. The diseases, disorders, or conditions may impact all tissues in a subject. In some embodiments, the organ and / or the tissue impacted by the disease, disorder, or condition may comprise an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, bone marrow, testis, a liver, a kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ and / or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, a lymphoid organ, blood, an adipose organ and / or tissue, an autoimmune organ and / or tissue, a heart, a uterus, a biliary organ, an upper respiratory organ, a central nervous system (CNS) organ and / or tissue, a spinal cord, a larynx, a gastroesophageal organ, a peripheral nervous system (PNS) organ and / or tissue, teeth, cartilage, a reproductive organ, a pituitary gland, a duodenum, a bone, a nasopharynx, an appendix, a cervix, a neuromuscular organ, a thymus, an immunity organ and / or tissue, a penis, a nose, a gonad, an endocrine organ, an ear, or any combination thereof. The organ health status may comprise a status that is free of a disease, disorder, or condition.

[0146]

[0135] The disease, disorder, or condition may be associated with a pancreatic disease, disorder, or condition. In some embodiments, the pancreatic disease, disorder, or condition may be associated with Type 1 diabetes, Type 2 diabetes, Type 3c diabetes, pancreatitis, pancreatic disease, autoimmune pancreatitis, Gastric Pancreatic Intraductal Papillary Mucinous Neoplasm, Acute Necrotizing Pancreatitis, Alcoholic Pancreatitis, Chronic Pancreatitis, Acute Pancreatitis, Acute Recurrent Pancreatitis, Autosomal Dominant Hereditary Pancreatitis, Fibrocalculous pancreatic diabetes, Fibrocystic Disease of Pancreas, Fibrosis of pancreas, Hereditary pancreatitis, Idiopathic chronic pancreatitis, Multiple pancreatic cysts, Pancreatic Cyst, Pancreatic disorders (not diabetes), Pancreatic Intraductal Papillary-Mucinous Neoplasm, Pancreatic intraepithelial neoplasia, Pancreatic Intraepithelial Neoplasia-3, Pancreatic Pseudocyst, or a combination thereof.

[0147]

[0136] The disease, disorder, or condition may be associated with a lung disease, disorder, or condition. In some embodiments, the lung disease, disorder, or condition may be associated with lung disease, interstitial Lung disease, Chronic lung disease, Idiopathic pulmonary arterial hypertension, Idiopathic pulmonary fibrosis, Idiopathic pulmonary hypertension, Interstitial lung fibrosis, Pulmonary arterial hypertension, Chronic obstructive pulmonary disease (COPD), Pulmonary cystic fibrosis, Pulmonary embolism, Pulmonary fibrosis, Pulmonary hypertension, or a combination thereof. WSGR Docket No. 63688-708.601

[0148]

[0137] The disease, disorder, or condition may be associated with the testis.

[0149]

[0138] The disease, disorder, or condition may be associated with a liver disease, disorder, or condition. In some embodiments, the liver disease, disorder, or condition may be associated with Liver Cirrhosis, Cirrhosis, Liver Disease, Experimental Liver Cirrhosis, Steatohepatitis, Liver Fibrosis, Fatty Liver, Non-alcoholic Fatty Liver Disease, Steatotic Liver Disease, Non-alcoholic Steatohepatitis, Chronic Liver Disease, Alcoholic Liver Cirrhosis, Alcoholic Liver Disease, Alcoholic Fatty Liver, Alcoholic Steatohepatitis, End Stage Liver Disease, Fatty Liver Disease, Acute Alcoholic Liver Disease, Metabolic Dysfunction Associated with Steatotic Liver, Polycystic Liver Disease, or a combination thereof.

[0150]

[0139] The disease, disorder, or condition may be associated with a hepatitis disease, disorder, or condition. In some embodiments, the hepatitis disease, disorder, or condition may be associated with Hepatitis, Autoimmune Hepatitis, Toxic Hepatitis, Alcoholic Hepatitis, Drug-induced Hepatitis, Chronic Hepatitis, Chronic Hepatitis B, Chronic Hepatitis C, Chronic Hepatitis D, Hepatitis A, Hepatitis B, Hepatitis C, Hepatitis D, Hepatitis E, or a combination thereof.

[0151]

[0140] The disease, disorder, or condition may be associated with a kidney disease, disorder, or condition. In some embodiments, the kidney disease, disorder, or condition may be associated with Membranoproliferative Glomerulonephritis, Acute Kidney Failure, Chronic Kidney Failure, Type I Membranoproliferative Glomerulonephritis, Type II Membranoproliferative Glomerulonephritis, Type III Membranoproliferative Glomerulonephritis, Interstitial Nephritis, Tubulointerstitial Nephritis, Type I Nephrogenic Diabetes Insipidus, Intralob ar Nephrogenic Rest, Calcium Oxalate Nephrol othiasis, Familial Juvenile Nephronophthisis, Congenital Nephrosis, Minimal Change Nephrotic Syndrome, Autosomal Recessive Steroid-Resistant Nephrotic Syndrome, Type 2 Polycystic kidney Disease, Autosomal Dominant Polycystic kidney, Type 1 Autosomal Dominant Polycystic kidney Disease, Type II Renal Tubular Acidosis, Toe Syndactyly Telecanthus And Anogenital And Renal Malformations, Acute glomerulonephritis, Acute kidney injury, Autosomal Recessive Polycystic Kidney Disease, C3 Glomerulonephritis, Calcium oxalate kidney stones, Central Diabetes Insipidus, Childhood nephrotic syndrome, Chronic glomerulonephritis, Chronic interstitial nephritis, Chronic kidney disease stage 3, Chronic kidney disease stage 5, Chronic Kidney Diseases, Congenital cystic kidney disease, Congenital Nephrogenic Diabetes Insipidus, Cystic Kidney Diseases, Cystic renal dysplasia, Diabetes Insipidus, Diabetic Nephropathy, Distal Renal Tubular Acidosis, Glomerulocystic Kidney Disease, Glomerulonephritis, Hypertensive Nephropathy, Hypertrophy Of Kidney, Idiopathic Crescentic Glomerulonephritis, Idiopathic Membranous Glomerulonephritis, Idiopathic Nephrotic Syndrome, Iga Glomerulonephritis, Kidney Diseases, Kidney Failure, Medullary Cystic Kidney Disease 1, Membranous Glomerulonephritis, WSGR Docket No. 63688-708.601

[0152] Multicystic Dysplastic Kidney, Multiple Renal Cysts, Multiple Small Medullary Renal Cysts, Nephritis, Nephrogenic Diabetes Insipidus, Obstructive Nephropathy, Polycystic Kidney Disease 1, Polycystic Kidney Diseases, Pre-Renal Acute Kidney Injury, Primary Immunoglobulin A Nephropathy, Progressive Renal Failure, Proliferative Glomerulonephritis, Proliferative Nephritis Unspecified, Rapidly Progressive Glomerulonephritis, Reflux Nephropathy, Renal Adysplasia, Renal Artery Stenosis, Renal Cortical Cysts, Renal Cortical Microcysts, Renal Corticomedullary Cysts, Renal Cyst, Renal Cysts And Diabetes Syndrome, Renal Dysplasia, Renal Dysplasia And Retinal Aplasia, Renal Fibrosis, Renal Glomerular Disease, Renal Glomerular Fibrosis, Renal Hypertension, Renal Hypoplasia / Aplasia, Renal Interstitial Fibrosis, Simple Renal Cyst, Steroid-Resistant Nephrotic Syndrome, Steroid- Sensitive Nephrotic Syndrome, Steroid Resistant Nephrotic Syndrome Of Childhood, End-stage Renal Disease, Renal Agenesis, Renal Artery Disease, or a combination thereof.

[0153]

[0141] The disease, disorder, or condition may be associated with a skin disease, disorder, or condition. In some embodiments, the skin disease, disorder, or condition may be associated with Skin Disease, Psoriasis, Atopic Dermatitis, Acne, Rosacea, Vitiligo, Actinic Keratosis, or a combination thereof.

[0154]

[0142] The disease, disorder, or condition may be associated with a hair disease, disorder, or condition. In some embodiments, the hair disease, disorder, or condition may be associated with Alopecia, Male Pattern Alopecia, Alopecia Areata, Alopecia Totalis, Alopecia Universalis, Androgenetic Alopecia, Dry Hair, Female Pattern Alopecia, Generalized Hirsutism, Hair Diseases, Hirsutism, Patchy Alopecia, Scarring Alopecia Of Scalp, or a combination thereof.

[0155]

[0143] The disease, disorder, or condition may be associated with a cardiac disease, disorder, or condition. In some embodiments, the cardiac disease, disorder, or condition may be associated with Atherosclerosis, Heart Disease, Coronary Artery Disease, Heart Failure Diastolic, Heart Failure Systolic, Cardiac Arrest, Cardiac Arrhythmia, Cardiac Hypertrophy, Chronic Heart Failure, Congestive Heart Failure, Coronary Heart Disease, Heart Diseases, Heart Failure, Hypertensive Heart Disease, Sudden Cardiac Arrest, Sudden Cardiac Death, Tachyarrhythmia, Ventricular Arrhythmia, or a combination thereof.

[0156]

[0144] The disease, disorder, or condition may be associated with the ovaries.

[0157]

[0145] The disease, disorder, or condition may be associated with the thyroid.

[0158]

[0146] The disease, disorder, or condition may be associated with the colon, the rectum, or both.

[0159]

[0147] The disease, disorder, or condition may be associated with the breast.

[0160]

[0148] The disease, disorder, or condition may be associated with the urinary bladder.

[0161]

[0149] The disease, disorder, or condition may be associated with the gastrointestinal tract.

[0162]

[0150] The disease, disorder, or condition may be associated with the small intestine. WSGR Docket No. 63688-708.601

[0163]

[0151] The disease, disorder, or condition may be associated with the esophagus.

[0164]

[0152] The disease, disorder, or condition may be associated with the salivary gland.

[0165]

[0153] The disease, disorder, or condition may be associated with the stomach.

[0166]

[0154] The disease, disorder, or condition may be associated with the brain.

[0167]

[0155] The disease, disorder, or condition may be associated with a neurodegenerative disease, disorder, or condition. In some embodiments, the neurodegenerative disease, disorder, or condition may be associated with Neurodegeneration, Alzheimer's Disease (AD), Parkinson's Disease (PD), Huntington’s Disease (HD), Amyotrophic Lateral Sclerosis (ALS), prion disease, or a combination thereof.

[0168]

[0156] The disease, disorder, or condition may be associated with the prostate.

[0169]

[0157] The disease, disorder, or condition may be associated with the lymphoid organ.

[0170]

[0158] The disease, disorder, or condition may be associated with the adrenal gland.

[0171]

[0159] The disease, disorder, or condition may be associated with the parathyroid.

[0172]

[0160] The disease, disorder, or condition may be associated with the pituitary gland.

[0173]

[0161] The disease, disorder, or condition may be associated with the eye.

[0174]

[0162] The disease, disorder, or condition may be associated with the endometrium.

[0175]

[0163] The disease, disorder, or condition may be associated with a reproductive organ.

[0176]

[0164] The disease, disorder, or condition may be associated with a penis.

[0177]

[0165] The disease, disorder, or condition may be associated with a gonad.

[0178]

[0166] The disease, disorder, or condition may be associated with a cervix.

[0179]

[0167] The disease, disorder, or condition may be associated with a nose.

[0180]

[0168] The disease, disorder, or condition may be associated with an ear.

[0181]

[0169] The disease, disorder, or condition may be associated with the gall bladder.

[0182]

[0170] The disease, disorder, or condition may be associated with a bone disease, disorder, or condition. In some embodiments, the bone disease, disorder, or condition may be associated with Arthritis, Adjuvant-induced Arthritis, Bacterial Arthritis, Collagen-induced Arthritis, Experimental Arthritis, Gouty Arthritis, Infectious Arthritis, Psoriatic Arthritis, Reactive Arthritis, Aneurysmal Bone Cysts, Developmental Bone Diseases, Knee Osteoarthritis, Spine Osteoarthritis, Developmental Bone Diseases, Primary Hypertrophic Osteoarthropathy, Dominant Perinatal Lethal Osteogenesis Imperfecta, Autosomal Recessive 3 Osteopetrosis, Age- Related Osteoporosis, Senile Osteoporosis, Post-menopausal Osteoporosis, Polyarticular Juvenile Idiopathic Arthritis, Rheumatoid Factor Negative, Paget’s Disease of Bone, Rheumatoid Arthritis, Cartilage Disease, Juvenile Rheumatoid Arthritis, or a combination thereof.

[0183]

[0171] The disease, disorder, or condition may be associated with the tongue. WSGR Docket No. 63688-708.601

[0184]

[0172] The disease, disorder, or condition may be associated with a nail disease, disorder, or condition. In some embodiments, the nail disease, disorder, or condition may be associated with Nail Disorder Nonsyndromic Congenital, Nail Diseases, Onychogryposis, Onycholysis, Onychomycosis, or a combination thereof.

[0185]

[0173] The disease, disorder, or condition may be associated with a lipid-related disease, disorder, or condition. In some embodiments, the lipid-related disease, disorder, or condition may be associated with Lipid Metabolism Disorder, Familial Combined Hyperlipidemia, Inborn Errors of Lipid Metabolism, Abnormal Obesity, Visceral Obesity, Morbid Obesity, Abnormal Obesity Metabolic Syndrome, Abnormality of Lipid Metabolism, Adult-onset Obesity, Antiphospholipid Syndrome, Childhood-onset Truncal Obesity, Dyslipidemia, Lipidemia, Hyperlipidemia, Moderate Obesity, Monogenic Obesity, Obesity, Obsolete Combined Hyperlipidemia, Overweight, Pediatric Obesity, or a combination thereof.

[0186]

[0174] The disease, disorder, or condition may be associated with an autoimmune disease, disorder, or condition. In some embodiments, the autoimmune disease, disorder, or condition may be associated with Collagenous Colitis, Ischemic Colitis, Lymphocytic Colitis, Microscopic Colitis, Autoimmune Diabetes, Autoimmune Hepatitis, Acute Fulminating Multiple Sclerosis, Chronic Progressive Multiple Sclerosis, Primary Progressive Multiple Sclerosis, Secondary Progressive Multiple Sclerosis, Relapsing-Remitting Multiple Sclerosis, Rheumatoid Factor Negative Polyarticular Juvenile Idiopathic Arthritis, Acute and chronic colitis, Acute Colitis, Addison's disease due to autoimmunity, Addison’s Disease, Amoebic colitis, Autoimmune arthritis, Autoimmune Diseases, Autoimmune enteropathy, Autoimmune gastritis, Autoimmune Hemolytic Anemia, Autoimmune liver disease, Autoimmune Lymphoproliferative Syndrome, Autoimmune Lymphoproliferative Syndrome Type 2B, Autoimmune neutropenia, Autoimmune pancreatitis, Autoimmune Primary Adrenal Insufficiency, Autoimmune state, Autoimmune thrombocytopenia, Autoimmune thyroid disease, Autoimmune thyroiditis, Celiac Disease, Chronic colitis, Chronic small plaque psoriasis, Chronic stable plaque psoriasis, Chronic ulcerative colitis, Colitis, Crohn Disease, Early Rheumatoid Arthritis, Enterocolitis, Experimental Autoimmune Encephalomyelitis, Familial psoriasis, Generalized pustular psoriasis, Graves’ Disease, Hashimoto Disease, Haemorrhagic colitis, Inflammatory Bowel Diseases, Juvenile rheumatoid arthritis, Latent Autoimmune Diabetes in Adults, Latent autoimmune diabetes mellitus in adult, Left sided colitis, Multiple Sclerosis, Paediatric Crohn's disease, Postpartum Thyroiditis, Progressive multiple sclerosis, Psoriasis, Psoriasis vulgaris, Pustular psoriasis, Rheumatoid Arthritis, Thyroiditis, Ulcerative Colitis, Autoimmune Optic Neuritis, Autoimmune Interstitial Ling, Joint, and Kidney Disease, Autoimmune Polyendocrine Syndrome, Autoimmune Neuropathy, or a combination thereof. WSGR Docket No. 63688-708.601

[0187]

[0175] The health status of the organ or tissue may comprise a presence or an absence of a disease, disorder, or condition. The organ health status may comprise a presence or an absence of an organ or a tissue impacted by a disease, disorder, or condition. The organ health status may comprise a subject having a disease, disorder, or condition or more than one disease, disorders, or conditions. For example, an organ health status may comprise a subject having more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 diseases, disorders, or conditions. The organ health status may comprise a presence or an absence of a disease, disorder, or condition as disclosed herein. The organ health status may comprise a disease remission status. The organ health status may comprise a disease recurrence status. The organ health status may comprise a risk of a subject having a disease, disorder, or condition, for example a risk of greater than or equal to 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 99.5%, or 99.9% of the subject having the disease, disorder, or condition. The organ health status may comprise a presence or an absence of a disease, disorder, or condition.

[0188]

[0176] The methods disclosed herein may comprise detecting a disease, disorder, or condition in a subject. One non-limiting example of a disease or condition is fatty liver disease. Additional non-limiting examples of diseases or conditions may include comorbidities, diabetes, heart disease, hypertension, mental disorders, Alzheimer’s disease, depression, arthritis, asthma, autoimmune diseases, respiratory diseases, dementia, schizophrenia, kidney diseases, bone diseases, skin diseases, obesity conditions, brain conditions, and the like.

[0189]

[0177] The methods may comprise use of a blood processing protocol. As shown in FIG. 2, the blood processing protocol may comprise one or more operations of: obtaining whole blood (202), enriching cell populations (204), red blood cell (RBC) lysis (206), cell counting (208), antibodies staining (210), sorted cell fractions collected in a cold chamber (212), or any combination thereof.

[0190]

[0178] FIG. 4 shows an additional example workflow that may be used in the methods disclosed herein. In 402, a whole blood-pellet may be obtained. The whole blood-pellet may be obtained from a biological sample of a subject. In 404, a cell population ranging from 2 pm to 8 pm in size may be obtained from the whole blood-pellet. The cell population may comprise one or more of: pluripotent stem cells (PSCs), very small embryonic-like stem cells (VSELs), tissue committed progenitor cells, and cancer stem cells (CSCs). In 406, the cells in the cell population may be distinguished from each other by, for example, cell morphological features, counts, and expression of molecular markers. The cells may be distinguished from each other using one or more techniques such as imaging, staining, enumeration of experimental data, and the like. In WSGR Docket No. 63688-708.601

[0191] 408, a combination of cells of the cell population may be enriched. The enrichment may be through Ficoll Hypaque-blood-pellet. The enrichment may be through flow cytometry. The enriched cells may be used for the methods disclosed herein for cancer detection and / or cancer / non-cancer prediction. In 410, a machine learning (ML) algorithm, as disclosed herein in the machine learning section, may be used for cancer detection and / or cancer / non-cancer prediction. The ML algorithm may make use of artificial intelligence (Al). In 412, somatic and germline mutations may be performed. Still referring to 412 in FIG. 4, the somatic and germline mutations may produce Blood Based Biopsy (B3) exome data.

[0192]

[0179] A gene panel may be used for cancer and non-cancer prediction. A gene panel may be used for prediction of an organ health status, for example, a presence or absence of a disease, disorder, or condition, or a combination thereof. One or more genes panels may be used for cancer and non-cancer prediction. One or more gene panels may be used for prediction of an organ health status. The gene panel may comprise 11 genes. The gene panel may comprise any of the genes disclosed herein. In some embodiments, the gene panel may comprise more than or equal to 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000,17,000, 18,000, 19,000, or 20,000 genes. In some embodiments, the gene panel may comprise less than or equal to 20,000, 19,000, 18,000, 17,000, 16,000, 15,000, 14,000, 13,000, 12,000, 11,000, 10,000, 9,000, 8,000, 7,000, 6,000, 5,000, 4,000, 3,000, 2,000, 1,000, 950, 900, 850, 800, 750, 700, 650, 600, 550, 500, 450, 400, 350, 300, 250, 240, 230, 220, 210, 200, 190, 180, 170, 160, 150, 140, 130, 120, 110, 100, 95, 90, 85, 80, 75, 70, 65, 60, 55, 50, 45, 40, 35, 30, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, or 3 genes.

[0193]

[0180] An organ panel may be used for organ prediction, for example, an organ impacted by a cancer, a disease, a disorder, or a condition, or an organ not impacted by a cancer, a disease, a disorder, or a condition, an organ impacted by a disease, disorder, or condition, or a combination thereof, other than cancer, or any combination thereof. In some embodiments, one or more organ panels may be used for organ prediction. Any of the organs disclosed herein may be used in an organ panel. An organ panel may be an “organ specific” panel and comprise of genes that exhibit organ specificity and are strongly associated with one organ but may have genes that appear in one or more organs. An organ panel may be an “organ related” panel and comprise of genes related to more than one organ but not related to all organs. An “organ related” panel may comprise of genes that are commonly expressed, with known expression across various organs. An “organ related” panel may comprise of genes that are widely expressed and ubiquitous in WSGR Docket No. 63688-708.601 their expression. An “organ related” panel may comprise genes that are found in a large number of organs, for example, more than 3 organs. An organ panel may comprise 10 organs. In some embodiments, the organ panel may comprise more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 organs. In some embodiments, the organ panel may comprise less than or equal to 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 organs.

[0194]

[0181] A tissue panel may be used for tissue prediction, for example, a tissue impacted by a cancer, a disease, a disorder, or a condition, or a tissue not impacted by a cancer, a disease, a disorder, or a condition, a tissue impacted by a disease, disorder, or condition other than cancer, or any combination thereof. In some embodiments, one or more tissue panels may be used for tissue prediction. Any of the tissues disclosed herein may be used in a tissue panel. A tissue panel may be an “tissue specific’ panel and comprise of genes that exhibit tissue specificity and are strongly associated with only one tissue. A tissue panel may be a “tissue related” panel and comprise of genes related to more than one tissue but not related to all tissues. A “tissue related” panel may comprise of genes that are commonly expressed, with known expression across various tissues. A “tissue related” panel may comprise of genes that are widely expressed and ubiquitous in their expression. A “tissue related” panel may comprise genes that are found in a large number of tissues, for example, more than 3 organs. A tissue panel may comprise 10 tissues. In some embodiments, the tissue panel may comprise more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 tissues. In some embodiments, the tissue panel may comprise less than or equal to 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 tissues.

[0195]

[0182] The methods may comprise enriching a population of cells in a biological sample. The population of cells may comprise stem cells, such as cancer stem cells, pluripotent stem cells, progenitor cells, or a combination thereof. The population of cells may comprise very small embryonic-like stem cells (VSELs). The population of cells may comprise progenitor cells, such as tissue committed progenitor cells. The enriching may include use of one or more reagents. The enriching may include use of centrifugation. In some embodiments, the enrichment may comprise one or more rounds of centrifugation, for example, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 rounds of centrifugation. In some embodiments, the enrichment may comprise a first round of centrifugation to be performed. The pellet from the first centrifugation round may be obtained and may be resuspended and centrifugated a second round. The pellet from the second centrifugation round may be used in the methods disclosed herein. In some embodiments, the pellet obtained from the second round of centrifugation may be referred to as the white pellet or pellet comprising pluripotent and progenitor stem cells. In some 6b

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[0202] I09 803-889E9 °N PTOWSM WSGR Docket No. 63688-708.601 cell separation technology, single cell RNA Seq., a culture method, or a plasmid method (306). Non-limiting examples of flow cytometry include cell counting, cell sorting, and imaging flow cytometry. Non-limiting examples of single cell RNA sequencing include fluorescence-based detection, fluorescence biosensors, FRET biosensors, and mass spectrometry. Additional nonlimiting examples of cell sorting techniques include positive and negative cell selection (e.g., flow cytometry applications and selective media), label-free methods (e.g., visual identification, sedimentation, centrifugation, filtering, microfluidics), sequencing, immunophenotyping, and the like.

[0203]

[0184] In some embodiments, the methods may comprise conducting a triangulation method of cell sub-populations from a blood sample and / or a fraction of the blood sample. For example, three sub-populations of cells may be segregated by methods disclosed herein. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 sub-populations of cells may be segregated by the methods disclosed herein. The segregation may be conducted before immunofluorescent staining for organ specificity related to cancer. In some embodiments, the sub-populations may include non-committed pluripotent stem cells (NCPSCs), cancer stem cells (CSCs), tissue committed progenitor cells (TCPCs), or any combination thereof. In some cases, the transcriptomic, exomic, and / or genomic features are derived from the sub-populations of cells. For example, in some embodiments, the transcriptomic and exomic features may be derived from the TCPCs.

[0204]

[0185] The methods may include use of one or more sorting methods. The sorting methods may be used to sort or subcategorize cells into sub-populations. Non-limiting examples of sorting methods that may be used include flow cytometry, magnetic-activated cell sorting (MACS), cell separation technology, single-cell sorting (SCS), cell culturing, CRISPR-Cas9 methods, or the like.

[0205]

[0186] The methods may include use of flow cytometry. Flow cytometry is a technology that provides rapid multi-parametric analysis of single cells in solution. Flow cytometry may utilize lasers as light sources to produce both scattered and fluorescent light signals that are read by detectors such as photodiodes or photomultiplier tubes. These signals may be converted into electronic signals that may be analyzed by a computer as disclosed herein. Cell populations can be analyzed and / or purified based on their fluorescent or light scattering characteristics. A variety of fluorescent reagents may be utilized in flow cytometry. These include, for example, fluorescently conjugated antibodies, DNA binding dyes, viability dyes, ion indicator dyes and fluorescent expression proteins, and the like. Blood lineage negative, CD45 negative, Oct4A+ cells may be sorted as NCPSCs; Blood lineage negative, CD45 negative, CD133+CD166+ cells may be sorted as CSCs; and remaining cells may be considered as TCPs. WSGR Docket No. 63688-708.601

[0206]

[0187] The methods may include use of magnetic-activated cell sorting (MACS). MACS may use superparamagnetic nanoparticles and columns. The superparamagnetic nanoparticles may be of the order of 100 nanometers (nm). The superparamagnetic nanoparticles may be used to tag the targeted cells in order to capture them inside a column. The column may be placed between permanent magnets so that when the magnetic particle-cell complex passes through it, the tagged cells can be captured. The column may include steel wool which may increase the magnetic field gradient to maximize separation efficiency when the column is placed between the permanent magnets. Magnetic-activated cell sorting is a method that may be used in areas like cancer research, neuroscience, and stem cell research. Microbeads, which are an example of magnetic nanoparticles, may conjugate to antibodies which can be used to target specific cells. MACS may be utilized to sort SSEA4 positive NCPSCs and CD166 positive beads may be utilized to enrich CSCs with remaining population termed as TCPs. In some embodiments, the methods may make use of beads. The beads may be coated beads. The beads may be coated with one or more chemicals.

[0207]

[0188] The methods may include use of single-cell sorting (SCS). Single-cell RNA sequencing (scRNA-seq) can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in development. Single-cell isolation is the first operation for obtaining transcriptome information from an individual cell. In this method, cells may first be tagged with a fluorescent monoclonal antibody, which may recognize specific surface markers and may enable sorting of distinct populations. In this case, based on predetermined fluorescent parameters, a charge may be applied to a cell of interest using an electrostatic deflection system, and cells may be isolated magnetically. Common operations that may be required for the generation of scRNA-seq libraries include cell lysis, reverse transcription into first-strand cDNA, second-strand synthesis, and cDNA amplification. Single cell RNA seq data analysis by bioinformatic pathway analysis may reveal distinct islands of the 3 cell sub-populations based on their transcriptome. This transcriptome, when compared to existing literature and databases, may provide information about an organ impacted (e.g., site of cancer), cancer type, subtype, next targets, etc.

[0208]

[0189] The methods may include use of cell culturing. Cell culture is a molecular biology technique used to maintain body tissue cells in a petri-dish under physiological conditions of pH, temperature and humidity. Culturing cells is a way to increase their proportionate number so that there are enough populations for next generation sequencing (NGS), although, cell cultures, with each passage, may alter mutational and gene expression profiles. Freshly sorted (e.g., using specific cell surface markers) NCPSCs (5* 102) may be plated in 0.2 mL of DMEM+10% FBS, supplemented with valporic acid and a cocktail of two pituitary sex hormones, follicle- WSGR Docket No. 63688-708.601 stimulating factor and luteinizing hormone together with BMP -4 (bone morphogen protein 4), insulin-like growth factor 2, and kit ligand. Cells may be incubated and cultured until reaching 70 to 80% confluency and passaged. After obtaining sufficient numbers of cells after subsequent passaging, the cells may be divided into 2 parts; one part may be frozen for future use and the other part may be utilized for NGS characterization.

[0209]

[0190] The methods may include use of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas methods, for example, CRISPR / Cas9. CRISPR / Cas9 may edit genes by precisely cutting DNA and letting natural DNA repair processes to take over. The system may include two parts: the Cas9 enzyme and a guide RNA. CRISPR “'spacer'’ sequences may be transcribed into short RNA sequences (“CRISPR RNAs” or “crRNAs”) capable of guiding the system to matching sequences of DNA. When the target DNA is found, Cas9 - one of the enzymes produced by the CRISPR system - may bind to the DNA and cut it, shutting the targeted gene off.

[0210]

[0191] The methods may comprise extracting nucleic acids. The nucleic acids may be extracted from a population of cells, such as stem cells and / or progenitor cells. The nucleic acids may include deoxyribonucleic acid (DNA). The DNA may be single stranded or double stranded. The DNA may be autosomal DNA. The DNA may be mitochondrial DNA. The DNA may be coding DNA. The DNA may be non-coding DNA. The nucleic acids may include ribonucleic acid (RNA). The RNA may comprise messenger RNA (mRNA), transfer RNA (tRNA), or ribosomal RNA (rRNA). The RNA may include small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), small interfering RNA (siRNA), micro-RNA (miRNA), short hairpin RNA (shRNA), or the like. The nucleic acids may include RNA and DNA. The stem cells and / or progenitor cells may be enriched from a biological sample. The extracting may include use of centrifugation, for example, density gradient centrifugation. The extracting may include use of phenol -chloroform extraction. The extracting may include use of solid-phase extraction. The extracting may include use of flow cytometry. The extracting may include use of beads, for example magnetic beads. The beads may be coated beads. The beads may be coated with one or more chemicals. The extracting may include use of polymerase chain reaction. The polymerase chain reaction may include any polymerase chain reaction as disclosed herein. The extracting may be performed manually. The extracting may be performed automatically. The extracting may include use of any extraction technique suitable to extract nucleic acids.

[0211]

[0192] The methods may comprise assaying nucleic acids. The nucleic acids may be extracted from a population of cells, such as stem cells and / or progenitor cells. The assaying may comprise sequencing methods as disclosed herein. The assaying may include amplification. The assaying may include polymerase chain reaction (PCR), such as multiplex PCR, long-range WSGR Docket No. 63688-708.601

[0212] PCR, single-cell PCR, fast-cycling PCR, PCT using methylation, digital PCR, in situ PCR, or the like. The assaying may include droplet digital Polymerase Chain Reaction (ddPCR). ddPCR is a method that that can measure nucleic acids by splitting the nucleic acids into thousands of droplets and amplifying them. The assaying may include use of temperature change. The assaying may include use of beads, such as magnetic beads. The beads may be coated beads. The beads may be coated with one or more chemicals. The assaying may include use of flow cytometry. The assaying may include isolation techniques. The assaying may include capture techniques. The assaying may include amplification techniques. The assaying may include denaturation techniques. The assaying may include annealing techniques. The assaying may include elongation techniques. The assaying may include use of one or more reagents. The assaying may include use of one or more primers.

[0213]

[0193] The methods may comprise sequencing nucleic acids. For example, DNA or RNA in a biological sample may be sequenced. Non-limiting examples of sequencing techniques include sequencing by synthesis (SBS), pyrosequencing, sequencing by reversible terminator chemistry, sequencing by ligation, phospholinked fluorescent nucleotide sequencing, real-time sequencing, and the like. The sequencing may include next generation sequencing (NGS), which utilizes the concept of massively parallel processing to obtain high-throughput, speed, and scalability. NGS may be referred to herein as massive parallel sequencing, massively parallel sequencing, or second-generation sequencing. The sequencing may include RNA sequencing, for example, mRNA sequencing, total RNA sequencing, low-input RNA sequencing, ultra-low-input RNA sequencing, small RNA sequencing, single cell RNA sequencing, and the like. The methods may include DNA sequencing, for example Sanger sequencing, capillary electrophoresis, sequencing by synthesis, shotgun sequencing, pyrosequencing, combinatorial probe anchor synthesis, sequencing by ligation, nanopore sequencing, single molecular real time sequencing, ion torrent sequencing, nanoball sequencing, next generation sequencing, or the like. The sequencing may include whole genome sequencing. The sequencing may include whole transcriptome sequencing. The sequencing may include whole exome sequencing. The sequencing may include next generation sequencing (NGS).

[0214]

[0194] The methods may comprise generating a baseline profile (e.g., a baseline) of a subject. The baseline profile may be used to determine a cancer status of the subject. The baseline profile may be used to determine an organ health status of a subject. In some embodiments, a baseline profile may be generated to test a subject that has a known chronic disease, disorder, or condition. In some embodiments, a baseline profile may be generated to test a subject that is a cancer survivor. A cancer survivor may be referred to a subject that has completed treatment at least 6 months prior and is determined to have a cancer negative status (e.g., through a PET WSGR Docket No. 63688-708.601

[0215] (positron emission tomography) or other appropriate method of determining a cancer positive or negative status). A cancer survivor may be tested for recurrence or remission status. Cancer recurrence status may be referred to as when a cancer returns after a periods of cancer remission. A cancer recurrence may occur due to remaining cancer cells in a subject’s body. Cancer remission status may be referred to as when the signs and symptoms of a cancer are reduced. A cancer remission status may be partial or complete. In a complete cancer remission status, all signs and symptoms of a cancer may have disappeared. In a partial cancer remission status, some of the signs and symptoms of a cancer may have disappeared. A cancer survivor may have different readings in their blood before and after a cancer. As such, a baseline profile may be generated for a cancer survivor to detect a cancer status in said cancer survivor. In some embodiments, to generate a baseline profile, a subject (e.g., a cancer survivor) may be tested more than once over a period of time, the subject’s transcriptomic profile, exomic profile, and / or genomic profile may be averaged, a baseline profile may be generated of the subject’s transcriptomic profile, exomic profile, and / or genomic profile, and the baseline profile may be compared to further profiles of the subject (e.g., a transcriptomic profile, an exomic profile, and / or a genomic profile) to determine a cancer status or an organ health status of the subject.

[0195] The methods may comprise obtaining a first biological sample obtained or derived from the subject at a first time point. The subject may comprise a cancer negative status. The methods may comprise enriching a first population of stem cells and / or progenitor cells in the first biological sample. The methods may comprise extracting first nucleic acids from the enriched first population of stem cells and / or progenitor cells. The methods may comprise assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile, a first genomic profile, and / or a first exomic profile of the subject. The methods may comprise obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point. The methods may comprise enriching a second population of stem cells and / or progenitor cells in the second biological sample. The methods may comprise extracting second nucleic acids from the enriched second population of stem cells and / or progenitor cells. The methods may comprise assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile, a second genomic profile, and / or a second exomic profile of the subject. The methods may comprise averaging the at least one of the first transcriptomic profile, the first genomic profile, and / or the first exomic profile of the subject with the at least one of the second transcriptomic profile, the second genomic profile, and / or the second exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, and / or a baseline exomic profile. The methods may comprise obtaining a third biological sample obtained or derived from the subject at a third time point that WSGR Docket No. 63688-708.601 is subsequent to the first and second time points. The methods may comprise enriching a third population of stem cells and / or progenitor cells in the third biological sample. The methods may comprise extracting third nucleic acids from the enriched third population of stem cells and / or progenitor cells. The methods may comprise assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile, a third genomic profile, and / or a third exomic profile of the subject. The methods may comprise computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, and / or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile, the third genomic profile, and / or the third exomic profile of the subject. The methods may comprise determining, based at least in part on the computer processing, the cancer status or the organ health status of the subject.

[0216]

[0196] The methods of generating a baseline may comprise obtaining a biological sample obtained or derived from a subject. The subject may comprise a cancer negative status. The subject may be a cancer survivor. The obtaining may be performed as disclosed herein. In some embodiments, one or more biological samples may be obtained from the subject. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 biological samples may be obtained from the subject. In some embodiments, a first, a second, a third, a fourth, a fifth, a sixth, a seventh, an eighth, a nineth, or a tenth biological sample may be obtained from the subject. In some embodiments, a first, a second, and a third biological sample is obtained from the subject where the third biological sample in obtained at a time subsequent to obtaining the first and second biological sample, and the second biological sample is obtained at a time subsequent to the first biological sample. In some embodiments, a first, a second, a third, and a fourth biological sample is obtained from the subject, where the fourth biological sample is obtained at a time subsequent to obtaining the first, second, and third biological samples, and where the third biological sample is obtained at a time subsequent to obtaining the first and second biological sample, and where the second biological sample is obtained at a time subsequent to obtaining the first biological sample.

[0217]

[0197] The methods of generating a baseline may comprise enriching a population of stem cells and / or progenitor cells in the biological sample. The enriching may be performed as disclosed herein. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 biological samples comprising a population of stem cells and / or progenitor cells may be enriched.

[0218]

[0198] The methods of generating a baseline may comprise extracting nucleic acids from the enriched population of stem cells and / or progenitor cells. The extracting may be performed as disclosed herein. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, WSGR Docket No. 63688-708.601

[0219] 13, 14, 15, 16, 17, 18, 19, or 20 population of stem cells and / or progenitor cells may be extracted for nucleic acids.

[0220]

[0199] The methods of generating a baseline may comprise assaying nucleic acids. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 population of stem cells and / or progenitor cells with extracted nucleic acids may be assayed. The assaying the nucleic acids may comprise generating at least one of a transcriptomic profile, a genomic profile, and / or an exomic profile. In some embodiment, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 transcriptomic profiles may be generated. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 genomic profiles may be generated. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 exomic profiles may be generated.

[0221]

[0200] The methods may comprise generating a baseline. The baseline may be generated by averaging one or more transcriptomic profiles, one or more genomic profiles, and / or one or more exomic profiles of the subject.

[0222]

[0201] In some embodiments, a subject’s transcriptomic profiles may be averaged to generate a baseline (e.g., a baseline transcriptomic profile). For example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more of a subject’s transcriptomic profiles may be averaged to generate a baseline. In one example, two transcriptomic profiles of a subject are averaged to generate a baseline. In another example, three transcriptomic profiles of a subject are averaged to generate a baseline. In yet another example, four transcriptomic profiles of a subject are averaged to generate a baseline.

[0223]

[0202] In some embodiments, a subject’s genomic profiles may be averaged to generate a baseline (e.g., a baseline genomic profile). For example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more of a subject’s genomic profiles may be averaged to generate a baseline. In one example, two transcriptomic profiles of a subject are averaged to generate a baseline. In another example, three transcriptomic profiles of a subject are averaged to generate a baseline. In yet another example, four transcriptomic profiles of a subject are averaged to generate a baseline.

[0224]

[0203] In some embodiments, a subject’s exomic profiles may be averaged to generate a baseline (e.g., a baseline exomic profile). For example, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, or ten or more of a subject’s exomic profiles may be averaged to generate a baseline. In one example, two transcriptomic profiles of a subject are averaged to generate a baseline. In another example, WSGR Docket No. 63688-708.601 three transcriptomic profiles of a subject are averaged to generate a baseline. In yet another example, four transcriptomic profiles of a subject are averaged to generate a baseline.

[0225]

[0204] The methods may comprise comparing a subject’s baseline to an additional profile of the subject. For example, a baseline profile may be generated from a subject, and said baseline profile may be compared to a profile generated from an additional biological sample of the subject. The additional profile of the subject may comprise an additional transcriptomic profile of the subject, an additional genomic profile of the subject, and / or an additional exomic profile of the subject.

[0226]

[0205] In some embodiments, a baseline profile may be generated from the average of a subject’s transcriptomic profiles. For example, one or more, two or more, three or more, four or more, or five or more transcriptomic profiles of a subject may be averaged to generate a baseline profile (e.g., a baseline transcriptomic profile). In some embodiments, said baseline transcriptomic profile is computer processed and / or compared to a further transcriptomic profile generated from the subject. The further transcriptomic profile may be generated from a biological sample obtained from the subject at a time subsequent to obtaining the biological samples (e.g., one or more, two or more, three or more, four or more, or five or more) used to generate the baseline profile. The further transcriptomic profile may be generated from: obtaining a biological sample obtained or derived from the subject, enriching a population to stem cells and / or progenitor cells, extracting nucleic acids from the enriched population of stem cells and / or progenitor cells, and assaying the nucleic acids to generate the transcriptomic profile, as disclosed herein. A cancer status or an organ health status of the subject may be determined at least in part on the computer processing and / or comparison of the subject’s transcriptomic profile and the subject’s further transcriptomic profile.

[0227]

[0206] In some embodiments, a baseline profile may be generated from the average of a subject’s genomic profiles. For example, one or more, two or more, three or more, four or more, or five or more genomic profiles of a subject may be averaged to generate a baseline profile (e.g., a baseline genomic profile). In some embodiments, said baseline genomic profile is computer processed and / or compared to a further genomic profile generated from the subject. The further genomic profile may be generated from a biological sample obtained from the subject at a time subsequent to obtaining the biological samples (e.g., one or more, two or more, three or more, four or more, or five or more) used to generate the baseline profile. The further genomic profile may be generated from: obtaining a biological sample obtained or derived from the subject, enriching a population to stem cells and / or progenitor cells, extracting nucleic acids from the enriched population of stem cells and / or progenitor cells, and assaying the nucleic acids to generate the genomic profile, as disclosed herein. A cancer status or an organ health status of the WSGR Docket No. 63688-708.601 subject may be determined at least in part on the computer processing and / or comparison of the subject’s genomic profile and the subject’s further genomic profile.

[0228]

[0207] In some embodiments, a baseline profile may be generated from the average of a subject’s exomic profiles. For example, one or more, two or more, three or more, four or more, or five or more exomic profiles of a subject may be averaged to generate a baseline profile (e.g., a baseline exomic profile). In some embodiments, said baseline exomic profile is computer process and / or compared to a further exomic profile generated from the subject. The further exomic profile may be generated from a biological sample obtained from the subject at a time subsequent to obtaining the biological samples (e.g., one or more, two or more, three or more, four or more, or five or more) used to generate the baseline profile. The further exomic profile may be generated from: obtaining a biological sample obtained or derived from the subject, enriching a population to stem cells and / or progenitor cells, extracting nucleic acids from the enriched population of stem cells and / or progenitor cells, and assaying the nucleic acids to generate the exomic profile, as disclosed herein. A cancer status of the subject may be determined at least in part on the computer processing and / or comparison of the subject’s exomic profile and the subject’s further exomic profile.

[0229]

[0208] The method may comprise generating a transcriptomic profile. A transcriptomic profile of a subject (e.g., an organism) may comprise a set of RNA molecules expressed under certain conditions. For example, a transcriptomic profile of a subject may vary depending on one or more of a development stage, an environment, and a biological process. The transcriptomic profile may be generated for a subject. The transcriptomic profile may be generated from extracted nucleic acids, which may be from a population of stem cells and / or progenitor cells. One or more transcriptomic profiles may be generated, for example, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 transcriptomic profiles may be generated. The transcriptomic profile of the subject may comprise one or more cancer-associate genes.

[0230]

[0209] In some cases, the transcriptomic profile may comprise more than or equal to 1, 2, 3, 4, 5,

[0231] 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 53, 54, 55, 56, 57,

[0232] 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,

[0233] 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 125, 150, 175, 200, 225, 250,

[0234] 275, or 300 genes. In some cases, the transcriptomic profile may comprise more than or equal to

[0235] 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 15,000, 20,000, 25,000, 30,000, 35,000, 40,000, 45,000, or 50,000 genes.

[0236]

[0210] In some cases, the transcriptomic profile may comprise less than or equal to 300, 275, 250, 225, 175, 150, 125, 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, WSGR Docket No. 63688-708.601

[0237] 80, 79, 78, 77, 76, 75, 74, 73, 72, 71, 70, 69, 68, 67, 66, 65, 64, 63, 62, 61, 60, 59, 58, 57, 56, 55,

[0238] 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29,

[0239] 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 genes. In some cases, the transcriptomic profile may comprise less than or equal to 50,000,

[0240] 45,000, 40,000, 35,000, 30,000, 25,000, 20,000, 15,000, 10,000, 5,000, 4,000, 3,000, 2,000, 1,000, 900, 800, 700, 600, 500, or 400 genes.

[0241]

[0211] The genes may be cancer-associated genes. The genes may not be associated with cancer. In some cases, the genes may comprise any of the genes provided herein.

[0242]

[0212] The genes may be disease-associated genes. The genes may be associated with a disease, disorder or condition. The genes may not be associated with a disease, disorder or condition. In some cases, the genes may comprise any of the genes provided herein.

[0243]

[0213] The methods may comprise generating a genomic profile. A genomic profile of a subject (e.g., an organism) may comprise a set of genes expressed under certain conditions. A genomic profile of a subject may provide genetic information related to the subject and how genes of the subject interact with each other and the environment. The genomic profile may be generated for a subject. The genomic profile may be generated from extracted nucleic acids, which may be from a population of stem cells and / or progenitor cells. One or more genomic profiles may be generated, for example, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 genomic profiles may be generated. The genomic profile of the subject may comprise one or more cancer-associate genes. The genomic profile of the subject may comprise one or more disease-associated genes.

[0244]

[0214] In some cases, the genomic profile may comprise more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 125, 150, 175, 200, 225, 250, 275, 300, 325, 350, 375, 400, 425, 450, 475, 500, 525, 550, 575, 600, 625, 650, 675, 700, 725, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975, or 1,000 genes. In some cases, the genomic profile may comprise more than or equal to 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 15,000, 20,000, 25,000, 30,000, 35,000, 40,000, 45,000, or 50,000, 55,000, 60,000, 65,000, 70,000, 75,000, 80,000, 85,000, 90,000, 95,000, 100,000, 110,000, 120,00, 130,000, 140,000, 150,000, 160,000, 170,000, 180,000, 190,000, 200,000, 210,000, 220,000, 230,000, 240,000, 250,000, 260,000, 270,000, 280,000, 290,000, 300,000, 325,000, 350,000, 375,000, 400,000, 425,000, 450,000, 475,000, or 500,000 genes.

[0245]

[0215] In some cases, the genomic profile may comprise less than or equal to 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79, 78, 77, 76, 75, 74, 73, 72, 71, 70, WSGR Docket No. 63688-708.601

[0246] 69, 68, 67, 66, 65, 64, 63, 62, 61, 60, 59, 58, 57, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44,

[0247] 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18,

[0248] 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 genes. In some cases, the genomic profile may comprise less than or equal to 500,000, 475,000, 450,000, 425,000, 400,000, 375,000,

[0249] 350,000, 325,000, 300,000, 290,000, 280,000, 270,000, 260,000, 250,000, 240,000, 230,000, 220,000, 210,000, 200,000, 190,000, 180,000, 170,000, 160,000, 150,000, 140,000, 130,000, 120,000, 110,000, 100,000, 95,000, 90,000, 85,000, 80,000, 75,000, 70,000, 65,000, 60,000, 55,000, 50,000, 45,000, 40,000, 35,000, 30,000, 25,000, 20,000, 15,000, 10,000, 5,000, 4,000, 3,000, 2,000, or 1,000 genes.

[0250]

[0216] The genes may be associated with cancer. The genes may not be associated with cancer. In some cases, the cancer genes may comprise any of the genes provided herein.

[0251]

[0217] The genes may be associated with a disease, disorder or condition. The genes may not be associated with a disease, disorder or condition. In some cases, the cancer genes may comprise any of the genes provided herein.

[0252]

[0218] The genes disclosed herein may be grouped into panels. The panels may be associated with one or more organs. The panels may be associated with one or more tissues. The panels may be associated with one or more diseases, disorders, or conditions wherein one or more genes in the panel may be associated with one or more diseases, disorders, or conditions. In some embodiments, the panels may be associated with the expression patterns of the genes. In some embodiments, some genes and gene panels may be associated with one organ, tissue, disease, disorder or condition. In some embodiments, some genes and gene panels may be associated with more than one organs, tissues, diseases, disorders or conditions. In some embodiments, some genes and gene panels may be associated with all organs, tissues, diseases, disorders or conditions. For example, a gene panel may include genes that may be found in a variety of organs, tissues, diseases, disorders, or conditions. In some embodiments, a gene panel may be associated with pancreatic disease and / or disorders. In some embodiments, a gene panel may be associated with lung disease and / or disorders. In some embodiments, a gene panel may be associated with upper respiratory tract disease and / or disorders. In some embodiments, a gene panel may be associated with bone disease and / or disorders. In some embodiments, a gene panel may be associated with bone marrow disease and / or disorders. In some embodiments, a gene panel may be associated with testicular disease and / or disorders. In some embodiments, a gene panel may be associated with liver disease and / or disorders. In some embodiments, a gene panel may be associated with renal disease and / or disorders. In some embodiments, a gene panel may be associated with skin disease and / or disorders. In some embodiments, a gene panel may be associated with ovarian disease and / or disorders. In some embodiments, a gene panel may be WSGR Docket No. 63688-708.601 associated with breast disease and / or disorders. In some embodiments, a gene panel may be associated with urinary bladder disease and / or disorders. In some embodiments, a gene panel may be associated with gastrointestinal disease and / or disorders. In some embodiments, a gene panel may be associated with small intestine disease and / or disorders. In some embodiments, a gene panel may be associated with esophageal disease and / or disorders. In some embodiments, a gene panel may be associated with salivary gland disease and / or disorders. In some embodiments, a gene panel may be associated with stomach disease and / or disorders. In some embodiments, a gene panel may be associated with brain disease and / or disorders. In some embodiments, a gene panel may be associated with neurodegenerative disease and / or disorders. In some embodiments, a gene panel may be associated with neurodevelopmental disease and / or disorders. In some embodiments, a gene panel may be associated with prostate disease and / or disorders. In some embodiments, a gene panel may be associated with lymphatic system disease and / or disorders. In some embodiments, a gene panel may be associated with adrenal gland disease and / or disorders. In some embodiments, a gene panel may be associated with parathyroid disease and / or disorders. In some embodiments, a gene panel may be associated with pituitary disease and / or disorders. In some embodiments, a gene panel may be associated with eye disease and / or disorders. In some embodiments, a gene panel may be associated with endometrial disease and / or disorders. In some embodiments, a gene panel may be associated with gall bladder disease and / or disorders. In some embodiments, a gene panel may be associated with tongue disease and / or disorders. In some embodiments, a gene panel may be associated with thyroid disease and / or disorders. In some embodiments, a gene panel may be associated with hair disease and / or disorders. In some embodiments, a gene panel may be associated with nail disease and / or disorders. In some embodiments, a gene panel may be associated with lipid-related disorders. In some embodiments, a gene panel may be associated with auto-immune disease and / or disorders. In some embodiments, a gene panel may be associated with cardiac disease and / or disorders. In some embodiments, a gene panel may be associated with blood disease and / or disorders. In some embodiments, a gene panel may be associated with colon disease and / or disorders. In some embodiments, a gene panel may be associated with bowel disease and / or disorders. In some embodiments, a gene panel may be associated with uterus disease and / or disorders. In some embodiments, a gene panel may be associated with biliary tract disease and / or disorders. In some embodiments, a gene panel may be associated with CNS disease and / or disorders. In some embodiments, a gene panel may be associated with spinal cord disease and / or disorders. In some embodiments, a gene panel may be associated with larynx disease and / or disorders. In some embodiments, a gene panel may be associated with gastroesophageal disease and / or disorders. In some embodiments, a gene panel WSGR Docket No. 63688-708.601 may be associated with PNS disease and / or disorders. In some embodiments, a gene panel may be associated with tooth disease and / or disorders. In some embodiments, a gene panel may be associated with cartilage disease and / or disorders. In some embodiments, a gene panel may be associated with reproductive system diseases and / or disorders. In some embodiments, a gene panel may be associated with duodenum disease and / or disorders. In some embodiments, a gene panel may be associated with nasopharynx disease and / or disorders. In some embodiments, a gene panel may be associated with appendix disease and / or disorders. In some embodiments, a gene panel may be associated with cervical disease and / or disorders. In some embodiments, a gene panel may be associated with lymph node disease and / or disorders. In some embodiments, a gene panel may be associated with neuromuscular system disease and / or disorders. In some embodiments, a gene panel may be associated with thymus disease and / or disorders. In some embodiments, a gene panel may be associated with immunity disease and / or disorders. In some embodiments, a gene panel may be associated with penile disease and / or disorders. In some embodiments, a gene panel may be associated with adrenal cortex disease and / or disorders. In some embodiments, a gene panel may be associated with fallopian tube disease and / or disorders. In some embodiments, a gene panel may be associated with uveal disease and / or disorders. In some embodiments, a gene panel may be associated with ciliary body disease and / or disorders. In some embodiments, a gene panel may be associated with sweat gland disease and / or disorders. In some embodiments, a gene panel may be associated with placenta disease and / or disorders. In some embodiments, a gene panel may be associated with sebaceous gland disease and / or disorders. In some embodiments, a gene panel may be associated with nasal disease and / or disorders. In some embodiments, a gene panel may be associated with gonad disease and / or disorders. In some embodiments, a gene panel may be associated with endocrine disease and / or disorders. In some embodiments, a gene panel may be associated with ear disease and / or disorders.

[0253]

[0219] The genes disclosed herein may be grouped into panels. In some embodiments, a panel of unique genes way be developed using various databases and scientific literature. In some embodiments, these sources may include but are not limited to Jensen Lab, Disgenet, EnrichR, Cell Marker, and / or KEGG / Reactome / SMPDB pathways related to organ / disease specific pathways. In some embodiments, genes associated with the pathogenesis of disease. In some embodiments, genes may be manually analyzed to assess their impact on adversity, for example, up or down adverse with PMIDs. In some embodiments, key genes associated with refined panel development for RT-PCR validation / ddPCR panel development may be generated, using but not limited to a set of features viz. directionality in conjunction with scientific literature, stem / progenitor markers, organ / disease specific functionality, organ / disease-specific pathway WSGR Docket No. 63688-708.601 correlations, and / or hub genes from scientific literature. In some embodiments, intensity (type) of gene, preclinical / clinical evidence, knockout / knockin studies, preclinical-clinical variants, journal impact factor may be factored in.

[0254]

[0220] FIG. 13 shows an example workflow for gene panel development. The workflow in FIG. 13 may be used in the methods and systems herein. FIG. 13 provides non-limiting operations 1302, 1304, 1306, 1308, 1310, and 1312. At operation 1302, a condition may be inputted. Nonlimiting examples of conditions that may be inputted include a goal, a condition, a symptom, a disease, a syndrome, or the like. The conditions that may be inputted may include one or more goals, one or more conditions, one or more symptoms, one or more diseases, one or more syndromes, or the like. At operation 1304, genes that may be associated with gene-disease association databases may be identified. Genes associated with gene-disease association databases may include more than or equal to about 1, 2, 3, 4, 5, 10, 25, 50, 100, 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 25,000, 50,000, 100,000, 250,000, 500,000, 750,000, or 1,000,000 genes. At operation 1306, genes that may be associated with scientific literature may be identified. Genes associated with scientific literature may include more than or equal to about 1, 2, 3, 4, 5, 10, 25, 50, 100, 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 25,000, 50,000, 100,000, 250,000, 500,000, 750,000, or 1,000,000 genes. At operation 1306, genes associated with stem markers, progenitor markers, or a combination thereof, may be identified. Genes associated with stem markers, progenitor markers, or a combination thereof, may include more than or equal to about 1, 2, 3, 4, 5, 10, 25, 50, 100, 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 25,000, 50,000, 100,000, 250,000, 500,000, 750,000, or 1,000,000 genes. At operation 1308, genes associated with pathway databases may be identified. Genes associated with pathway databases may include more than or equal to about 1, 2, 3, 4, 5, 10, 25, 50, 100, 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 25,000, 50,000, 100,000, 250,000, 500,000, 750,000, or 1,000,000 genes. At operation 1310, gene duplicates may be removed. At operation 1310, a unique gene panel may be created. At operation 1312, a scoring system as described herein may be implemented.

[0255]

[0221] The methods may comprise generating an exomic profile. The exome may be a whole exome or a panel-based exome. An exomic profile of a subject (e.g., an organism) may comprise a set of variants detected under certain conditions. An exomic profile of a subject may provide genetic information related to the subject and how variants of the subject have been impacted by the environment. The exomic profile may be generated for a subject. The exomic profile may be generated from extracted nucleic acids, which may be from a population of stem cells and / or progenitor cells. One or more exomic profiles may be generated, for example, more than or WSGR Docket No. 63688-708.601 equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 exomic profiles may be generated. The exomic profile of the subject may comprise one or more variants.

[0256]

[0222] In some cases, the exomic profile may comprise more than or equal to 1, 2, 3, 4, 5, 6, 7, 8,

[0257] 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 53, 54, 55, 56, 57, 58, 59,

[0258] 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,

[0259] 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 125, 150, 175, 200, 225, 250, 275, 300,

[0260] 325, 350, 375, 400, 425, 450, 475, 500, 525, 550, 575, 600, 625, 650, 675, 700, 725, 750, 775,

[0261] 800, 825, 850, 875, 900, 925, 950, 975, or 1,000 variants. In some cases, the exomic profile may comprise more than or equal to 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 15,000, 20,000, 25,000, 30,000, 35,000, 40,000, 45,000, 50,000, 55,000, 60,000, 65,000, 70,000, 75,000, 80,000, 85,000, 90,000, 95,000, 100,000, 110,000, 120,000, 130,000, 140,000, 150,000, 160,000, 170,000, 180,000, 190,000, or 200,000 variants.

[0262]

[0223] In some cases, the exomic profile may comprise less than or equal to 1,000, 975, 950, 925,

[0263] 900, 875, 850, 825, 800, 775, 750, 725, 700, 675, 650, 625, 600, 575, 550, 525, 500, 475, 450, 425, 400, 375, 350, 325, 300, 275, 250, 225, 200, 175, 150, 125, 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79, 78, 77, 76, 75, 74, 73, 72, 71, 70, 69, 68, 67,

[0264] 66, 65, 64, 63, 62, 61, 60, 59, 58, 57, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41,

[0265] 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15,

[0266] 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 variants. In some cases, the exomic profile may comprise less than or equal to 200,000, 190,000, 180,000, 170,000, 160,000, 150,000, 140,000, 130,000, 120,000, 110,000, 100,000, 95,000, 90,000, 85,000, 80,000, 75,000, 70,000, 65,000, 60,000, 55,000, 50,000, 45,000, 40,000, 35,000 30,000, 25,000, 20,000, 15,000, 10,000, 9,000, 8,000, 7,000, 6,000, 5,000, 4,000, 3,000, or 2,000 variants.

[0267]

[0224] The variants may be associated with cancer. The variants may not be associated with cancer. In some cases, the cancer associated variants may comprise any of the genes provided herein. In some cases, the cancer associated variants may alter the expression profile of the corresponding genes and / or the associated genes. In some cases, the exomic profile may comprise an indication of the effect of environmental impacts on the exomic profile, for example, somatic mutations. In some cases, the exomic profile may comprise an indication of the effect of, for example, germline polymorphisms on the phenotype.

[0268]

[0225] The genes may be associated with cancer. The genes may not be associated with cancer.

[0269]

[0226] The genes disclosed herein may be grouped into panels. In some embodiments, the panels may be associated with a number of organs, tissues, and / or cancers that each gene may be associated with. In some embodiments, the panels may be associated with the expression WSGR Docket No. 63688-708.601 patterns of the genes. In some embodiments, some genes and gene panels may be associated with all organs, tissues, and / or cancers. For example, a gene panel may include genes that may be found in a variety of organs, tissues, and / or cancer. In some embodiments, some genes and gene panels may be associated with one organ, tissue, cancer, or a combination thereof, but may be found in more than one organ, tissue, cancer, or a combination thereof. For example, a gene panel may comprise genes that are commonly expressed with known expression across various organs. In another example, a gene panel may comprise genes that are widely expressed with expression in a large number of organs, for example, more than 3 organs. In some embodiments, some genes and gene panels may be associated with one organ, tissue, and / or cancer. For example, a gene panel may be associated with one organ. In some embodiments, a gene panel may be associated with a pancreas. In some embodiments, a gene panel may be associated with a lung or the lungs. In some embodiments, a gene panel may be associated with bone marrow. In some embodiments, a gene panel may be associated with testis. In some embodiments, a gene panel may be associated with a liver. In some embodiments, a gene panel may be associated with a kidney. In some embodiments, a gene panel may be associated with skin. In some embodiments, a gene panel may be associated with an ovary or the ovaries. In some embodiments, a gene panel may be associated with a breast or the breasts. In some embodiments, a gene panel may be associated with a urinary bladder. In some embodiments, a gene panel may be associated with a gastrointestinal organ. In some embodiments, a gene panel may be associated with a small intestine. In some embodiments, a gene panel may be associated with an esophagus. In some embodiments, a gene panel may be associated with a salivary gland. In some embodiments, a gene panel may be associated with a stomach. In some embodiments, a gene panel may be associated with a brain. In some embodiments, a gene panel may be associated with a prostate. In some embodiments, a gene panel may be associated with a lymphoid organ. In some embodiments, a gene panel may be associated with an adrenal gland. In some embodiments, a gene panel may be associated with a parathyroid gland. In some embodiments, a gene panel may be associated with a pituitary gland. In some embodiments, a gene panel may be associated with an eye or the eyes. In some embodiments, a gene panel may be associated with endometrium. In some embodiments, a gene panel may be associated with a gall bladder. In some embodiments, a gene panel may be associated with a tongue.

[0270]

[0227] In some embodiments, the genes may be associated with all organs, tissues, and / or cancers. Cancer originates from cancer stem cells and sternness genes may have a key role in tumor mass proliferation and differentiation. Proto-oncogenes are a group of genes that cause normal cells to become cancerous. Proto-oncogenes, which may also be referred to as “oncogenes,” are causative genes of cancer initiation. The cell cycle has several regulatory operations that may be WSGR Docket No. 63688-708.601 crucial to maintaining homeostasis inside of the cells during the replication of DNA. The division of cells and mutation of cell cycle genes can lead to the loss of balance inside the cells, thus resulting in cancer growth. Tumor suppressor genes represent the opposite side of cell growth control, normally acting to inhibit cell proliferation and tumor development. Immune checkpoint genes (ICGs) play pivotal roles in tumor immune microenvironment (TIME) and are essential to develop immune response against cancerous cells. Inflammatory cytokines and chemokines, which can be produced by the tumor cells and / or tumor-associated leukocytes and platelets, may contribute to malignant progression. Metastatic genes are those that provide an advantage in primary tumors and may help in the spread of cancer cells to different sites in the body. DNA damage is well recognized as a critical factor in cancer development and progression, as a result, DNA repair genes may have a crucial role in cancer biology. Dysregulation of biomolecules metabolism may be a hallmark of physiological changes in cancer cells. Each type of cancer may have a certain set of unique signature genes which may be frequently mutated in each cancer type and their dysregulation at the transcript level may be due to gene alteration. Cancer diagnosis genes are the signature genes that are associated with different cancer types.

[0271]

[0228] In some embodiments, the genes may be associated with one organ, tissue, and / or cancer, but may be found in more than one organ, more than one tissue, and / or more than one cancer, but not be common to all organs, tissues, and / or cancers. In some embodiments, some genes and gene panels may be associated with genes that are commonly expressed, with known expression across various organs. In some embodiments, some genes and gene panels may be associated with genes that are widely expressed, where the genes have ubiquitous expression in a large number of organs, for example, more than 3 organs.

[0272]

[0229] In some embodiments, one or more gene panels may be used in the methods disclosed herein. In some embodiments, more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,

[0273] 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,

[0274] 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66,

[0275] 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,

[0276] 93, 94, 95, 96, 97, 98, 99 or 100 gene panels may be used in the methods disclosed herein. In some embodiments, less than or equal to 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79, 78, 77, 76, 75, 74, 73, 72, 71, 70, 69, 68, 67, 66, 65, 64, 63, 62, 61,

[0277] 60, 59, 58, 57, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35,

[0278] 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9,

[0279] 8, 7, 6, 5, 4, 3, or 2 gene panels may be used in the methods disclosed herein. WSGR Docket No. 63688-708.601

[0280]

[0230] In some embodiments, some genes and gene panels may be associated with one or more organs, tissues, cancers, diseases, disorders, or conditions. For example, the genes and gene panels may be associated with one or more organs, tissues, cancers diseases, disorders, or conditions disclosed herein. In some embodiments, the genes and gene panel may be associated with more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, or 50 organs, tissues, cancers, diseases, disorders, or conditions disclosed herein. In some embodiments, the genes and gene panels may be associated with less than or equal to 50, 45, 40, 35, 30, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 organs, tissues, cancers, diseases, disorders, or conditions disclosed herein. In some embodiments, the gene may also be associated with one or more organs, tissues, cancers diseases, disorders, or conditions other than the organ, tissue, cancer, diseases, disorders, or conditions that the gene is already associated with, but may not be present in all organs, tissues, cancers diseases, disorders, or conditions.

[0281]

[0231] In some embodiment, each gene panel may comprise a number of genes. For example, the gene panel may comprise more than or equal to 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 15,000, 20,000, or 25,000 genes. In some embodiments, the gene panel may comprise more than or equal to 30,000, 35,000, 40,000, 45,000, 50,000, 55,000, 60,000, 65,000, 70,000, 75,000, 80,000, 85,000, 90,000, 95,000, 100,000, 110,000, 120,000, 130,000, 140,000, 150,000, 160,000, 170,000, 180,000, 190,000, 200,000, 225,000, 250,000, 275,000, 300,000, 350,000, 400,000, 450,000, 500,000, 550,000, 600,000, 650,000, 700,000, 750,000, 800,000, 850,000, 900,000, 950,000, or 1,000,000 genes. In some embodiments, the gene panel may comprise less than or equal to 25,000, 20,000, 15,000, 10,000, 5,000, 4,000, 3,000, 2,000, 1,000, 950, 900, 850, 800, 750, 700, 650, 600, 550, 500, 450, 400, 350, 300, 350, 200, 150, 100, 75, 50, 45, 40, 35, 30, 25, 20, 15, 10, or 5 genes. In some embodiments, the gene panel may comprise less than or equal to 1,000,000, 950,000, 900,000, 850,000, 800,000, 750,000, 700,000, 650,000, 600,000, 550,000, 500,000, 450,000, 400,000, 350,000, 300,000, 275,000, 250,000, 225,000, 200,000, 190,000, 180,000, 170,000, 160,000, 150,000, 140,000, 130,000, 120,000, 110,000, 100,000, 95,000, 90,000, 85,000, 80,000, 75,000, 70,000, 65,000, 60,000, 55,000, 50,000, 45,000, 40,000, 35,000 or 30,000 genes. Each gene panel may comprise a different number of genes. In one embodiment, all gene panels are used in the methods disclosed herein. In this example, each of the gene panels may comprise a different number of genes.

[0282]

[0232] In some embodiments, a biological sample may be obtained as disclosed herein and various genes in the biological sample may be upregulated or downregulated in each gene panel. WSGR Docket No. 63688-708.601

[0283] In some embodiments, the upregulated genes may be adversely dysregulated or non-adversely dysregulated. In some embodiments, the downregulated genes may be adversely dysregulated or non-adversely dysregulated. The upregulated and downregulated genes in each panel may inform a determination of a cancer status or an organ health status. The upregulated and downregulated genes in each panel may further inform various pathways, which may further inform a cancer status or an organ health status in a subject. These pathways may comprise, for example, one or more metabolic pathways, one or more endocrine system pathways, one or more inflammation pathways, one or more immune health pathways, or any combination thereof. For example, FIGs. 8A-8B show pathways in cancer where some genes are determined to be upregulated, some genes are determined to be downregulated, and some genes are determined not to be unregulated or downregulated. As another example, FIG. 10A shows a flowchart showing genes that are upregulated, downregulated, and neither upregulated nor downregulated in pathways in cancer. FIG. 10B shows a flowchart showing genes that are upregulated, downregulated, and neither upregulated nor downregulated in pathways in noncancer. In some embodiments, pathways as disclosed herein may help inform a cancer status (e.g., a cancer or a non-cancer disease or condition) or an organ health status of a subject. In some embodiments, pathways as disclosed herein may be analyzed with data resulting from the gene panels disclosed herein to determine a cancer status (e.g., a cancer or a non-cancer disease or condition) or an organ health status of a subject. In some embodiments, the genes may be associated with pathways in a non-cancerous condition, for example Alzheimer’s disease, diabetes, endometriosis, or the like.

[0284]

[0233] In some embodiments, the methods may comprise analyzing one or more pathways to determine a cancer status of a subject. The analyzing may comprise use of computer processing. In some embodiments, the one or more pathways may comprise cancer-associated pathways.

[0285]

[0234] In some embodiments, the methods may comprise analyzing one or more pathways to determine a health condition of a subject. The analyzing may comprise use of computer processing. In some embodiments, the one or more pathways may comprise cancer-associated pathways.

[0286]

[0235] The pathways may comprise a p53 signaling pathway. The pathways may comprise a Ras signaling pathway. The pathways may comprise a Calcium signaling pathway. The pathways may comprise a cAMP signaling pathway. The pathways may comprise a Hippo signaling pathway. The pathways may comprise a JAK-STAT signaling pathway. The pathways may comprise a MAPK signaling pathway. The pathways may comprise an mTOR signaling pathway. The pathways may comprise a Notch signaling pathway. The pathways may comprise a PI3K-Akt signaling pathway. The pathways may comprise a TGF-beta signaling pathway. The WSGR Docket No. 63688-708.601 pathways may comprise a VEGF signaling pathway. The pathways may comprise a Wnt signaling pathway. The pathways may comprise Pl 3-AKT pathway, MAPK pathway, Calcium pathway, RAS pathway, cAMP pathway, Wnt pathway, JAK-STAT pathway, HIPPO pathway, MTOR pathway, TGFB pathway, TP53 pathway, VEGF pathway, Hedgehog pathway, or a combination thereof.

[0287]

[0236] The pathways may comprise a pathway associated with a health condition. In some embodiments, the pathway may comprise a urea pathway, a cytochrome p450 drug metabolism pathway, a surfactant pathway, a proteoglycan pathways, a collagen synthesis pathway, a keratan sulfate pathway, a uric acid synthesis pathway, a glycan biosynthesis pathway, an insulin pathway, a glucagon synthesis pathway, an insulin resistance pathway, a hemoglobin pathway, a ceramide pathway, a phosphatidylcholine pathway, a myelin synthesis pathway, a melanin synthesis pathway, a dermatan sulfate pathway, an androgen biosynthesis pathway, a progesterone synthesis pathway, an estrogen synthesis pathway, a testosterone metabolism pathway, a thyroid hormone synthesis pathway, a fatty acid metabolism pathway, an adrenaline pathway, a cortisol synthesis pathway, a hyaluronan synthesis pathway, a chondroitin sulfate metabolism pathway, or a creatinine pathway, or a combination thereof. The pathway may comprise a urea pathway. The pathway may comprise a cytochrome p450 drug metabolism pathway. The pathway may comprise a surfactant pathway. The pathway may comprise a proteoglycan pathway. The pathway may comprise a collagen synthesis pathway. The pathway may comprise a keratan sulfate pathway. The pathway may comprise a uric acid synthesis pathway. The pathway may comprise a glycan biosynthesis pathway. The pathway may comprise an insulin pathway. The pathway may comprise a glucagon synthesis pathway. The pathway may comprise an insulin resistance pathway. The pathway may comprise a hemoglobin pathway. The pathway may comprise a ceramide pathway. The pathway may comprise a phosphatidylcholine pathway. The pathway may comprise a myelin synthesis pathway. The pathway may comprise a melanin synthesis pathway. The pathway may comprise a dermatan sulfate pathway. The pathway may comprise an androgen biosynthesis pathway. The pathway may comprise a progesterone synthesis pathway. The pathway may comprise an estrogen synthesis pathway. The pathway may comprise a testosterone metabolism pathway. The pathway may comprise a thyroid hormone synthesis pathway. The pathway may comprise a fatty acid metabolism pathway. The pathway may comprise an adrenaline pathway. The pathway may comprise a cortisol synthesis pathway. The pathway may comprise a hyaluronan synthesis pathway. The pathway may comprise a chondroitin sulfate metabolism pathway. The pathway may comprise a creatinine pathway. WSGR Docket No. 63688-708.601

[0288]

[0237] The pathways may relate to an organ. The pathways may relate to a liver. The pathways may relate to a lung. The pathways may relate to a bone. The pathways may relate to a kidney. The pathways may relate to a colon / gastric. The pathways may relate to a pancreas. The pathways may relate to blood / bone marrow. The pathways may relate to a brain. The pathways may relate to skin. The pathways may a prostate. The pathways may relate to an ovary. The pathways may relate to a breast. The pathways may relate to testis. The pathways may relate to a thyroid. The pathways may relate to adipose. The pathways may relate to adrenal. The pathways may relate to cartilage. The pathways may relate to muscle.

[0289]

[0238] In some embodiments, the methods may comprise determining one or more upregulated genes in one or more pathways. The one or more upregulated genes may comprise more than or equal to about 2 genes, about 3 genes, about 4 genes, about 5 genes, about 6 genes, about 7 genes, about 8 genes, about 9 genes, about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 550 genes, about 600 genes, about 650 genes, about 700 genes, about 750 genes, about 800 genes, about 850 genes, about 900 genes, about 950 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 30,000 genes, about 35,000 genes, about 40,000 genes, about 45,000 genes, about 50,000 genes, about 55,000 genes, about 60,000 genes, about 65,000 genes, about 70,000 genes, about 75,000 genes, about 80,000 genes, about 85,000 genes, about 90,000 genes, about 95,000 genes, about 100,000 genes, about 110,000 genes, about 120,000 genes, about 130,000 genes, about 140,000 genes, about 150,000 genes, about 160,000 genes, about 170,000 genes, about 180,000 genes, about 190,000 genes, or about 200,000 genes. In some embodiments, the methods may comprise determining one or more downregulated genes in one or more pathways. The one or more downregulated genes may comprise more than or equal to about 2 genes, about 3 genes, about 4 genes, about 5 genes, about 6 genes, about 7 genes, about 8 genes, about 9 genes, about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 550 genes, about 600 genes, about 650 genes, about 700 genes, about 750 genes, about 800 genes, about 850 genes, about 900 genes, about 950 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 WSGR Docket No. 63688-708.601 genes, about 20,000 genes, about 25,000 genes, about 30,000 genes, about 35,000 genes, about 40,000 genes, about 45,000 genes, about 50,000 genes, about 55,000 genes, about 60,000 genes, about 65,000 genes, about 70,000 genes, about 75,000 genes, about 80,000 genes, about 85,000 genes, about 90,000 genes, about 95,000 genes, about 100,000 genes, about 110,000 genes, about 120,000 genes, about 130,000 genes, about 140,000 genes, about 150,000 genes, about 160,000 genes, about 170,000 genes, about 180,000 genes, about 190,000 genes, or about 200,000 genes.

[0290]

[0239] The methods may comprise comparing one or more upregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a cancer status.

[0291]

[0240] The methods may comprise comparing one or more downregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a cancer status.

[0292]

[0241] The methods may comprise comparing one or more upregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a health condition.

[0293]

[0242] The methods may comprise comparing one or more downregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a health condition.

[0294]

[0243] In some embodiments, the methods may comprise determining one or more adversely dysregulated genes in one or more pathways. The one or more adversely dysregulated genes may comprise more than or equal to about 2 genes, about 3 genes, about 4 genes, about 5 genes, about 6 genes, about 7 genes, about 8 genes, about 9 genes, about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 550 genes, about 600 genes, about 650 genes, about 700 genes, about 750 genes, about 800 genes, about 850 genes, about 900 genes, about 950 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 30,000 genes, about 35,000 genes, about 40,000 genes, about 45,000 genes, about 50,000 genes, about 55,000 genes, about 60,000 genes, about 65,000 genes, about 70,000 genes, about 75,000 genes, about 80,000 genes, about 85,000 genes, about 90,000 genes, about 95,000 genes, about 100,000 genes, about 110,000 genes, about 120,000 genes, about 130,000 genes, about 140,000 genes, about 150,000 genes, about 160,000 genes, about 170,000 genes, WSGR Docket No. 63688-708.601 about 180,000 genes, about 190,000 genes, or about 200,000 genes. In some embodiments, the methods may comprise determining one or more non-adversely dysregulated genes in one or more pathways. The one or more non-adversely dysregulated genes may comprise more than or equal to about 2 genes, about 3 genes, about 4 genes, about 5 genes, about 6 genes, about 7 genes, about 8 genes, about 9 genes, about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 550 genes, about 600 genes, about 650 genes, about 700 genes, about 750 genes, about 800 genes, about 850 genes, about 900 genes, about 950 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 30,000 genes, about 35,000 genes, about 40,000 genes, about 45,000 genes, about 50,000 genes, about 55,000 genes, about 60,000 genes, about 65,000 genes, about 70,000 genes, about 75,000 genes, about 80,000 genes, about 85,000 genes, about 90,000 genes, about 95,000 genes, about 100,000 genes, about 110,000 genes, about 120,000 genes, about 130,000 genes, about 140,000 genes, about 150,000 genes, about 160,000 genes, about 170,000 genes, about 180,000 genes, about 190,000 genes, or about 200,000 genes.

[0295]

[0244] The methods may comprise comparing one or more adversely dysregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a cancer status.

[0296]

[0245] The methods may comprise comparing one or more non-adversely dysregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a cancer status.

[0297]

[0246] The methods may comprise comparing one or more adversely dysregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a health condition.

[0298]

[0247] The methods may comprise comparing one or more non-adversely dysregulated genes of one or more pathways of a subject to a reference biological sample obtained or derived from a subject known not to have a health condition.

[0299]

[0248] Pathways described herein may relate to insulin secretion. For example, FIG. 15A shows an example of a flow diagram showing pathways in insulin secretion in a diabetic subject. As another example, FIG. 15B shows an example of a flow diagram showing pathways in insulin secretion in a pre-diabetic subject. As another example, FIG. 15C shows an example of a flow diagram showing pathways in insulin secretion in a control subject (e.g., not diabetic or pre- WSGR Docket No. 63688-708.601 diabetic). As shown in FIGs. 15A-15B, in some embodiments, the blue boxes represent upregulated genes and the yellow boxes represent Downregulated genes. Still referring to FIGs. 15A-15B, in some embodiments, the blue boxes represent adversely dysregulated or non- adversely dysregulated genes and the yellow boxes represent adversely dysregulated or non- adversely dysregulated genes.

[0300]

[0249] Pathways described herein may relate to Alzheimer’s Disease (AD). For example, FIG. 16A shows an example of a flow diagram showing pathways in Alzheimer’s Disease (AD) in a control subject without AD. As another example, FIG. 16B shows an example of a flow diagram showing pathways in AD in a subject with AD. As shown in FIGs. 16A-16B, the red boxes represent adversely dysregulated genes and green boxes represent non-adversely dysregulated genes.

[0301]

[0250] Pathways described herein may relate to atherosclerosis and cholesterol. For example, FIG. 17A shows an example of a flow diagram showing pathways in lipids and atherosclerosis in a control subject that does not have atherosclerosis. As another example, FIG. 17B shows an example of a flow diagram showing pathways in lipids and atherosclerosis in a subject having a risk of atherosclerosis or high cholesterol levels. As another example, FIG. 17C shows an example of a flow diagram showing pathways in lipids and atherosclerosis in a subject having coronary artery disease. As shown in FIGs. 17A-17B, the red boxes represent adversely dysregulated genes and green boxes represent non-adversely dysregulated genes.

[0302]

[0251] Pathways described herein may relate to non-alcoholic fatty liver disease. For example, FIG. 18A shows an example of a flow diagram showing pathways in non-alcoholic fatty liver disease in a control subject that does not have non-alcoholic fatty liver disease. As another example, FIG. 18B shows an example of a flow diagram showing pathways in non-alcoholic fatty liver disease in a subject having mild fatty liver. As shown in FIGs. 18A-18B, the red boxes represent upregulated genes, and the green boxes represent downregulated genes.

[0303]

[0252] FIG. 19A shows an example of a flow diagram showing pathways in cancer in a control subject. FIG. 19B shows an example of a flow diagram showing pathways in cancer in a cancer subject that is treatment naive. FIG. 19C shows an example of a flow diagram showing pathways in cancer in a cancer subject that is on treatment. FIG. 19D shows an example of a flow diagram showing pathways in cancer in a subject that is a cancer survivor.

[0304]

[0253] Pathways described herein may relate to neurodegeneration (NDD). FIG. 20A shows an example of a flow diagram showing pathways in neurodegeneration (multiple diseases) in a subject that has absence of neurodegeneration (NDD). FIG. 20B shows an example of a flow diagram showing pathways in neurodegeneration (multiple diseases) in a subject that has a risk WSGR Docket No. 63688-708.601 of neurodegeneration. FIG. 20C shows an example of a flow diagram showing pathways in neurodegeneration (multiple diseases) in a subject that has a presence of neurodegeneration.

[0305]

[0254] In some embodiments, a biological sample may be analyzed in a number of gene panels. In some embodiments, three or more gene panels are used (e.g., one or more gene panels comprising genes found in all cancers, in addition to one or more gene panels comprising organ specific genes, in addition to one or more gene panels comprising genes that are associated with one organ that can appear in more than one organ but less than all organs). In some embodiments all gene panels may be used. The upregulated and downregulated genes in each of the gene panels may help inform a cancer status or an organ health status of a subject as disclosed herein.

[0306]

[0255] In some embodiments, the genes may be associated with cancer stem cells. For example, the genes may comprise one or more genes comprising ABCB1, ABCB5, ABCG2, ABL1, AKT1, ALCAM, ALDH1A1, ALDH1A3, ARHGEF1, BMI1, CCND1, CD34, CD38, CD44, CDH1, CDH2, CDKN2A, CTD-2131H8, CTNNB1, CXCL12, CXCR4, DCLK1, DNAJB8, EGF, EGFR, EPCAM, ERBB2, EZH2, GLI1, GLI2, HRAS, HSA-MIR-200C-3P, HSA-MIR- 34A-5P, HSA-MIR-520C-5P, HSA-MIR-589-5P, IL3RA, ITGA6, ITGB1, JAG1, KIT, KLF4, KRAS, LGR5, LIN28A, LIN28B, MELK, MET, MGMT, MSI1, MTOR, MYC, NANOG, NES, NGFR, N0TCH1, N0TCH4, POU2AF1, POU5F1, POU5F1A, POU5F1B, PR0M1, PTCHI, PTEN, SALL4, SHH, SNAI1, SNAI2, SOX2, SRY, STAT3, SUZ12, TCF4, TGFB1, THY1, TP53, TWIST1, USP22, VEGFA, WNT1, or ZEB 1.

[0307]

[0256] In some embodiments, the genes may be associated with inflammatory response. For example, the genes may comprise one or more genes comprising ABCA1, ABH, ACVR1B, ACVR2A, ADGRE1, ADM, AD0RA2B, ADRM1, AHR, APLNR, AQP9, ATP2A2, ATP2B1, ATP2C1, AXL, BDKRB1, BEST1, BST2, BTG2, C3AR1, C5AR1, CALCRL, CCL17, CCL2, CCL20, CCL22, CCL24, CCL5, CCL7, CCR7, CCRL2, CD14, CD28, CD40, CD40LG, CD48, CD55, CD69, CD70, CD80, CD82, CD86, CDKN1A, CHST2, CLEC5A, CMKLR1, COL1A1, COL1A2, COL3A1, CSF1, CSF3, CSF3R, CX3CL1, CXCL10, CXCL11, CXCL6, CXCL8, CXCL9, CXCR2, CXCR6, CYBB, DCBLD2, EBB, EDN1, EIF2AK2, EMP3, EREG, F3, FFAR2, FN1, FPR1, FZD5, GABBR1, GCH1, GNA15, GNAI3, GP1BA, GPC3, GPR132, GPR183, HAS2, HBEGF, HIF1A, HPN, HRH1, ICAM1, ICAM4, ICOSLG, IFITM1, IFNAR1, IFNG, IFNGR2, IL10, IL10RA, IL12B, IL15, IL15RA, IL18, IL18R1, IL18RAP, ILIA, IL1B, IL1R1, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, IL6, IL7R, INHBA, IRAK2, IRF1, IRF7, ITGA5, ITGB3, ITGB8, KCNA3, KCNJ2, KCNMB2, KIF1B, KLF6, LAMA5, LAMB1, LAMB2, LAMC1, LAMC2, LAMP3, LCK, LCP2, LDLR, LIF, LPAR1, LT A, LY6E, LYN, MARCO, MEFV, MEP1A, MET, MMP14, MSR1, MXD1, MYC, NAMPT, NDP, NFKB1, WSGR Docket No. 63688-708.601

[0308] NFKBIA, NLRP3, NMI, NMUR1, N0D2, NPFFR2, 0LR1, OPRK1, OSM, OSMR, P2RX4, P2RX7, P2RY2, PCDH7, PDE4B, PDPN, PIK3R5, PLAUR, PROK2, PSEN1, PTAFR, PTGER2, PTGER4, PTGIR, PTPRE, PVR, RAFI, RASGRP1, RELA, RGS1, RGS16, RHOG, RIPK2, RNF144B, ROS1, RTP4, SCARF1, SCN1B, SELE, SELENOS, SELL, SEMA4D, SERPINE1, SGMS2, SLAMF1, SLC11A2, SLC1A2, SLC28A2, SLC31A1, SLC31A2, SLC4A4, SLC7A1, SLC7A2, SPHK1, SRI, STAB1, TACR1, TACR3, TAPBP, THBS1, THBS3, TIMP1, TLR1, TLR2, TLR3, TNFAIP6, TNFRSF1A, TNFRSF1B, TNFRSF9, TNFSF10, TNFSF15, TNFSF9, TPBG, VIP, VTN, or ZAP70.

[0309]

[0257] In some embodiments, the genes may be associated with immune regulators. For example, the genes may comprise one or more genes comprising ABD, ABL1, AIM2, AIRE, AKAP8, AL0X15, ARNTL, AXL, BATF, BCL6, BCL6B, BTK, C4A, C4BPA, C8orf4, CACNA1C, CARD11, CASP3, CCL20, CCR5, CCR6, CD244, CD274, CD28, CD3E, CD46, CD55, CD59, CD79B, CEBPB, CEBPG, CFB, CFH, CHUK, CIITA, CLC, COL1A1, COL2A1, CR2, CRLF1, CRT AM, CRY2, CSF1R, CTLA4, CXADR, CXCL5, CXCR5, DAB2IP, DDX17, DDX3X, DDX58, DHX58, DNAIC2, DNMT3B, EIF2AK2, EOMES, FCGR2B, FCGR2C, FGB, FGG, FOXI1, FOXP3, FTH1, FUT7, FYB, FYN, GATA3, GATA6, GEM, GPI, GRB2, GRHL3, GZMA, HAVCR2, HBA1, HBA2, HCK, HCST, HERC5, HLA-DRB1, HLA-G, HMGB1, HMGB2, HSPD1, ICAM1, IDO1, IFI16, IFIH1, IFIT2, IFNG, IFNK, IGF1R, IK, IKBKB, IKBKE, IKBKG, IL1R1, IL1RN, IL2, IL27, IL2RA, IL4, IRAKI, IRF1, IRF3, IRF4, IRF5, IRF7, IRF8, ISG15, KLRK1, LAIR1, LCK, LEPR, LGALS1, LGALS9, LIF, LILRB2, LYN, MATK, MEF2C, MID2, MPL, MYLPF, MY09B, NAIP, NCF1, NCKAP1, NFIL3, NFKB1, NFKBIA, NFKBIL1, NR1H4, OAS1, OPRK1, OTUB1, OTUD7B, PACRG, PCBP2, PDCD1, PER2, PF4, PHF20, PIK3CD, PIK3CG, PML, POLR3K, PPARG, PPBP, PPP1R14B, PRDM1, PRF1, PRKCD, PRKD2, PSEN1, PSMA1, PSMA7, PSMB10, PSMB5, PSMB8, PSMB9, PTK2, PTK2B, PTPN22, PTPN6, RELB, RFX1, RFX4, RIPK1, RIPK2, RNF125, SATB1, SFTPA1, SFTPD, SIN3A, SIRPB1, SIRT1, SIRT2, SKAP2, SLAMF1, SMAD3, SMAD6, SMURF1, SOX9, SP1, SPN, SRC, SRPK1, STAT6, STIM1, SYK, TAB3, TBK1, TCF12, TCF7, TFE3, TFEB, TGFB1, THBS1, TICAM1, TIRAP, TLR5, TNF, TNFSF18, TNFSF4, TNK1, TRAF6, TREX1, TRIM28, TRIM6, TXK, TYROBP, VTCN1, WASF2, WNT5A, XBP1, ZAP70, ZBP1, ZC3H12A, ZEB1, or ZFP36Ll.

[0310]

[0258] In some embodiments, the genes may be associated with immune check points. For example, the genes may comprise one or more genes comprising BTLA, BTN2A1, BTN2A2, BTN3A1, BTNL3, BTNL9, CD137, CD137L, CD155, CD160, CD200, CD200R, CD209, CD27, CD273, CD274, CD276, CD28, CD40, CD47, CD48, CD70, CD80, CD86, CD96, WSGR Docket No. 63688-708.601

[0311] CEACAM1, CTLA4, DNAM1, Galectin-9, GITR, GITRL, HHLA2, HVEM, ICOS, IDO, LAG3, LIGHT, 0X40, PDCD1, SIRPA, TDO, TIGIT, TIM-3, TMIGD2, VISTA, or VTCN1.

[0312]

[0259] In some embodiments, the genes may be, or may be associated with, cell cycle genes. For example, the genes may comprise one or more genes comprising ABL1, ANAPC1, ANAPC10, ANAPC11, ANAPC13, ANAPC2, ANAPC4, ANAPC5, ANAPC7, ATM, ATR, BUB1, BUB1B, BUB3, CCNA1, CCNA2, CCNB1, CCNB2, CCNB3, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNH, CDC14A, CDC14B, CDC16, CDC20, CDC23, CDC25A, CDC25B, CDC25C, CDC26, CDC27, CDC45, CDC6, CDC7, CDK1, CDK2, CDK4, CDK6, CDK7, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CHEK1, CHEK2, CHEK2, CREBBP, CUL1, CUL1, DBF4, E2F1, E2F2, E2F2, E2F3, E2F4, E2F4?, E2F5, EP300, ESPL1, FZR1, GADD45A, GADD45B, GADD45G, GSK3B, HDAC1, HDAC2, MAD2L1, MAD2L2, MCM2, MCM3, MCM4, MCM5, MCM6, MCM7, MDM2, MYC, ORC6?, PCNA, PKMYT1, PLK1, PRKDC, PTTG1, PTTG2, RAD21, RBI, RBL1, RBL2, RBX1, SFN, SKP1, SKP2, SMAD2, SMAD3, SMAD4, SMC1A, SMC1B, SMC3, STAG1, STAG2, TFDP1, TFDP2?, TGFB1, TGFB2, TGFB3, TICRR?, TP53, TTK, WEE1, WEE2, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAQ, YWHAZ, or ZB TB 17.

[0313]

[0260] In some embodiments, the genes may be associated with metastasis. For example, the genes may comprise one or more genes comprising ACTN1, ACTR2, ACTR3, AKT1, AKT2, AKT3, APC, AR, ARF1, ARF6, ARHGEF4, BCAR1, BMP1, CAPN1, CBL, CCR10, CCR7, CD44, CDC42, CDH1, CDH11, CDH2, CDH3, CDH5, COL1A1, COL1A2, CRK, CSF1, CTNNA1, CTNNB1, CTNND1, CTTN, CXCR4, CYB5R3, DOCK1, DVL1, EGF, EGFR, ENPP2, ESRI, ESR2, FGF2, FGFR1, FLT3, FN1, FXYD5, FYN, FZD1, GLI1, GPI, GRLF1, GSK3B, GSN, HGF, HIF1A, IGF1, ILK, INPP5D, IQGAP1, IQGAP2, IQGAP3, ITGA2, ITGA3, ITGA4, ITGA5, ITGA6, ITGA9, ITGAV, ITGB1, ITGB3, ITGB4, JAK2, LAMA1, LAMA3, LAMB3, LAMC1, MED 19, MET, MMP1, MMP13, MMP2, MMP9, MRC2, MSN, MTA1, MT A3, MTSS1, MYLK, NCK1, NF2, NFAT5, NFATC2, NR0B2, NUPR1, PARD6A, PDGFRB, PIK3CG, PLAU, PLAUR, PLXNB1, PRKCI, PTCHI, PTEN, PTK2, PTPN11, PXN, RAC1, RDX, RHOA, RHOC, RHOU, ROCK1, SEMA6D, SIP1, SMAD2, SMO, SNAI1, SNAI2, SPP1, SRC, SRF, STAT5A, STK11, TCF3, TGFBR1, TIAM1, TIAM2, TJP1, TLN1, TNFSF11, TNS1, TPT1, VASP, VCL, VEGFA, VEGFC, VTN, WAS, WASF1, WASF2, WASF3, WASL, WIT1, WT1, WTAP, or ZEB2.

[0314]

[0261] In some embodiments, the genes may be, or may be associated with, protooncogenes. For example, the genes may comprise one or more genes comprising ABL1, AFF3, AGAP2, AKT1, ATAD2, BAD, BAX, BCL11A, BCL2, BCL2A1, BCL3, BCL6, BRAF, C1ORF56, C3, C5, CASC4, CBL, CCDC6, CCND1, CCNE1, CD274, CDC73, CDH1, CDK2, CDKN1A, CDX2, WSGR Docket No. 63688-708.601

[0315] CEP55, CGA, CHEK2, CLU, CREB1, CRK, CSF1R, CSNK2A1, CT45A1, CTNNB1, CTNND1, DEK, DHRS2, DNMT3B, DRD2, DRD3, E2F1, EDN3, EEF1A2, EFNA1, EGFR, EIF2AK2, EIF3I, ELANE, ELK1, EPHA2, ERBB2, ERBB4, ETS1, ETS2, FASN, FGF2, FOS, FOSL1, F0XA1, GAP43, GAS6, GDNF, GFI1, GHET1, GNA12, GNAI2, GSK3B, HAX1, HCK, HGF, HRAS, HSF2, HSP90AA1, HSPB1, IGF2BP1, IGFBP3, JUN, KAT6A, KIT, KITLG, KLK1, KMT2A, KNG1, KRAS, LYPLA1, LYPLA2, MAF, MAGEA11, MAPK1, MAPKAPK2, MCF2, MDM2, MEN1, MET, MIR138-1, MIR138-2, MIR155HG, MIR193B, MIR199A1, MIR222, MIR34A, MIR372, MST1R, MXD1, MYB, MYC, NEDD4, NFKB1, NRAS, PAK1, PATZ1, PEG10, PELP1, PIM1, PIP5K1C, PLAU, PLAUR, PML, POU5F1, PRKCD, PTEN, PTGS2, PTK2, PTPN11, PTTG1, PTTG1IP, RBI, RBL1, RBM3, RELA, RET, ROS1, SDHB, SDHD, SH3KBP1, SKI, SKIL, SLC5A5, SMO, SNAI2, SOS1, SP1, SRC, SREBF1, SRSF2, STAT3, SYK, TCL1A, TFAP2C, TGFB1, TLR2, TP53, TP73, TPD52, TRIM33, TUBB3, TWIST1, UBE2V1, UBTF, VHL, WNT10B, YES1, YY1, ZBTB7A, or ZEB2.

[0316]

[0262] In some embodiments, the genes may be associated with tumor suppressors. For example, the genes may comprise one or more genes comprising ABCG2, ABD, ACHE, ACVR1C, ACY1, ADAMTS18, ADAMTS8, ADAMTS9, ADAMTS9-AS2, AD ARB I , ADPRH, AFAP1L2, AGTR1, AHCYL1, AHNAK, AHR, AHRR, AIF1, AIM2, AIMP1, AIMP2, AIP, AJAP1, AKAP12, AKR1B1, AKT1, ALDH1A2, AL0X15, AL0X15B, ALPL, AMER1, AMH, ANAPC1, ANGPTL4, ANP32A, ANXA1, ANXA7, APAF1, APC, APITD1, ARF1, ARG1, ARHGAP29, ARHGEF12, ARID! A, ARID2, ARL11, ARL6IP5, ARMC10, ARMC5, ARNTL, ASCL1, ASS1, ASXL1, ATF3, ATM, ATMIN, ATR, AXIN1, AXIN2, AZGP1, BANP, BAP1, BARD1, BASP1, BATF2, BAX, BBC3, BCL10, BCL2L11, BCL6B, BCORL1, BCR, BECN1, BEX2, BHLHE41, BIK, BINI, BLCAP, BLID, BLM, BLNK, BMF, BMP 10, BMP2, BMP4, BMPR1A, BMPR2, BNIP3L, BRCA1, BRCA2, BRD7, BRF1, BRINP1, BRMS1, BRSK1, BTG2, BTG3, BTG4, BTK, C2orf40, CABLES1, CACNA2D3, CADM1, CADM2, CADM3, CADM4, CAMK2N1, CAMTAI, CAPG, CASC1, CASC2, CASP2, CASP5, CASP8, CAT, CAV1, CBFA2T3, CBL, CBX5, CCAR1, CCAR2, CCDC136, CCDC154, CCDC67, CCNC, CCNDBP1, CD4, CD44, CD82, CDC73, CDCP1, CDH1, CDH11, CDH13, CDH17, CDH4, CDH5, CDK2, CDK2AP1, CDK6, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDO1, CDX2, CEACAM1, CEBPA, CEBPD, CFTR, CHD1, CHD5, CHEK1, CHEK2, CHFR, CHST10, CHUK, CIC, CITED2, CIZ1, CLDN1, CLDN23, CLU, CMTM3, CMTM5, CNDP2, CNN1, CNOT3, CNTNAP2, COPS2, CPNE7, CREB3L1, CREBBP, CREM, CRNN, CSF2, CSMD1, CSNK1A1, CSRNP1, CST5, CST6, CTCF, CTCFL, CTDSPL, CTGF, CTNNA2, CTNNA3, CTNNBIP1, CTNND1, CUL1, CUL2, CUL5, CUX1, CXCL10, CXCL12, WSGR Docket No. 63688-708.601

[0317] CXCL14, CXCR2, CXXC4, CXXC5, CYB561D2, CYB5A, CYB5R2, CYGB, CYLD, DAB2, DAB2IP, DACH1, DACT1, DAPK1, DAPK2, DAPK3, DCC, DCDC2, DCLRE1A, DCN, DCUN1D3, DDB2, DDR2, DDX3X, DDX58, DEFBI, DENND2D, DFFA, DFNA5, DIABLO, DICER1, DIDOI, DIRAS1, DIRAS3, DKK1, DKK3, DLC1, DLEC1, DLEU1, DLEU2, DLG1, DLK1, DMBT1, DMD, DMTF1, DNAJA3, DNAJB1, DNAJB4, DNAJC11, DND1, DNMT1, DNMT3A, DNMT3B, DOK1, DOK2, DOK3, DPH1, DPP4, DSC3, DSP, DUSP1, DUSP22, DUSP26, DUSP5, DUSP6, DUSP9, E2F1, E2F2, E2F3, EAF1, EAF2, EBF3, ECT2, EDA2R, EDNRB, EED, EEF1A1, EEF1E1, EFNA5, EGLN1, EGLN3, EGR1, EGR2, EHD3, EHF, EI24, EIF3F, EMP1, EMP2, EPAS1, EPB41, EPB41L3, EPHA1, EPHA2, EPHA3, EPHB2, EPHB3, EPHB4, EPHB6, ERBB2, ERBB4, ERF, ERRFI1, ESRI, ESR2, ESRP1, ESRRB, ETS2, ETV6, EXT1, EXT2, EXTL1, EXTL2, EXTL3, EYA4, EZH1, EZH2, FABP3, FADD, FAM172A, FAM188A, FANCG, FAS, FAT1, FAT4, FBLN1, FBP1, FBXL13, FBXO25, FBXO31, FBXO32, FBXW7, FER1L4, FH, FHIT, FHL1, FLCN, FLNA, FLT3, FOXA1, FOXA2, FOXCI, FOXD3, FOXL2, FOXO1, FOXO3, FOXO4, FOXO6, FOXP1, FOXP3, FRK, FRS3, FUS, FXN, FZR1, G0S2, GAB ARAP, GADD45A, GADD45B, GADD45G, GADD45GIP1, GALR1, GANAB, GAS1, GAS5, GATA4, GATA5, GBP1, GGNBP2, GJA1, GJB2, GKN1, GKN2, GLI1, GLIPR1, GLS2, GLTSCR1, GLTSCR2, GNAT1, GNB2L1, GNMT, GORAB, GPC3, GPC5, GPRC5A, GPX3, GREM1, GRIN2A, GSK3B, GSN, GSTP1, GSTT1, GTPBP4, GUCY2C, H19, H2AFX, HACD4, HACE1, HBP1, HCAR2, HDAC1, HDAC3, HECA, HEP AC AM, HIC1, HIF1A, HINT1, HIPK2, HIRA, HIVEP1, HIVEP3, HLTF, HNF4A, H0MER2, HOPX, HOTS, HOXB13, HPGD, HRASLS2, HRG, HSP90B1, HSPB7, HSPD1, HTATIP2, HTRA1, HTRA2, HTRA3, ID4, IDH1, IER3, IFH6, IFT88, IGF1, IGF2R, IGFALS, IGFBP3, IGFBP4, IGFBP5, IGFBP7, IGFBPL1, IKZF1, IKZF2, IKZF3, IL17A, IL17RD, IL24, ILK, ING1, ING2, ING3, ING4, ING5, INPP4B, INTS6, IQGAP2, IRF 1 , IRF3, IRF4, IRF5, IRF8, IRX1, ISG15, ITGA5, ITGA7, ITGAV, ITGB1, ITGB3, JDP2, JUP, KANK1, KAT5, KCNRG, KDM3A, KDM3B, KDM5A, KDM6A, KDM8, KIF1B, KIF7, KISSI, KL, KLF10, KLF4, KLF5, KLF6, KLK10, KLK6, KMT2C, KRIT1, KRT19, L3MBTL4, LAT2, LATS1, LATS2, LEFTY1, LEFTY2, LGALS7, LHX4, LHX6, LIFR, LIMA1, LIMD1, LIN9, LINC- PINT, LITAF, LLGL1, LMNTD1, LOC401317, LOX, LRIG1, LRIG3, LRMP, LRP1B, LRRC3B, LRRC4, LSAMP, LTF, LXN, LZTS1, MAD1L1, MADD, MAL, MAP2K4, MAP3K4, MAP3K8, MAP4K1, MAPK10, MAPK9, MARCKS, MARVELD1, MAT2A, MAX, MBD4, MCC, MCM9, MCPH1, MDC1, MEG3, MEN1, MFSD2A, MIA, MIA2, MIR100, MIRlOl-1, MIR101-2, MIR106A, MIR107, MIR10A, MIR1-1, MIR1-2, MIR122, MIR1226, MIR124-1, MIR124-2, MIR124-3, MIR1247, MIR125A, MIR125B1, MIR125B2, MIR126, MIR127, MIR1291, MIR129-1, MIR129-2, MIR1297, MIR130A, MIR132, MIR133A1, WSGR Docket No. 63688-708.601

[0318] MIR133A2, MIR134, MIR135A1, MIR135A2, MIR136, MIR137, MIR138-1, MIR138-2, MIR140, MIR141, MIR142, MIR143, MIR145, MIR146A, MIR147A, MIR148A, MIR148B, MIR149, MIR150, MIR152, MIR155, MIR15A, MIR16-1, MIR16-2, MIR17, MIR181A1, MIR181A2, MIR181B1, MIR181B2, MIR181C, MIR182, MIR183, MIR185, MIR186, MIR187, MIR18A, MIR18B, MIR192, MIR193A, MIR193B, MIR194-1, MIR194-2, MIR195, MIR196A2, MIR196B, MIR198, MIR199A1, MIR200A, MIR200B, MIR200C, MIR203A, MIR204, MIR205, MIR206, MIR20A, MIR210, MIR211, MIR214, MIR215, MIR217, MIR218-1, MIR218-2, MIR219A1, MIR22, MIR222, MIR223, MIR23A, MIR23B, MIR24-1, MIR25, MIR26A1, MIR26A2, MIR26B, MIR27A, MIR27B, MIR28, MIR296, MIR29A, MIR29B1, MIR29C, MIR302B, MIR30A, MIR30C1, MIR31, MIR320A, MIR326, MIR329-1, MIR335, MIR338, MIR33A, MIR340, MIR34A, MIR34B, MIR34C, MIR367, MIR370, MIR375, MIR378A, MIR383, MIR409, MIR410, MIR422A, MIR424, MIR449A, MIR449B, MIR451A, MIR483, MIR486-1, MIR487B, MIR490, MIR493, MIR494, MIR495, MIR497, MIR502, MIR503, MIR504, MIR505, MIR508, MIR509-3, MIR511, MIR517A, MIR519D, MIR520B, MIR520C, MIR551A, MIR574, MIR615, MIR636, MIR708, MIR7-1, MIR7-2, MIR7-3, MIR874, MIR888, MIR9-1, MIR9-2, MIR9-3, MIR941-1, MIR98, MIR99A, MIRLET7A1, MIRLET7A2, MIRLET7A3, MIRLET7B, MIRLET7C, MIRLET7D, MIRLET7E, MIRLET7F1, MIRLET7F2, MIRLET7G, MIRLET7I, MLH1, MLH3, MME, MNT, M0B1A, MOB IB, MRVI1, MSH2, MSMB, MST1, MST1R, MT1DP, MT1F, MT1G, MT1M, MT2A, MTAP, MTSS1, MTUS1, MUS81, MXI1, MYBBP1A, MYH9, MYO18B, MYO1A, MZB1, NAPEPLD, NBN, NCOA4, NCOA5, NDN, NDRG1, NDRG2, NDRG4, NDST4, NEDD4, NEDD4L, NEURL1, NF1, NF2, NFATC1, NFATC2, NFKB1, NGFR, NINJ1, NIT2, NKX2-8, NKX3-1, NME1, NNAT, NOL7, NOTCH1, NOTCH2, NOTCH3, NOV, NPAS2, NPM1, NPRL2, NR0B2, NR1I2, NR2C2, NR4A1, NR4A3, NRBP1, NRCAM, NRF1, NRSN2, NTRK3, NUAK1, NUMB, NUP98, NUPR1, OLFM4, ONECUT1, OPCML, OSCP1, OSGIN1, PACRG, PAEP, PAFAH1B1, PAIP2, PALB2, PANO1, PANX2, PARK2, PARK7, PARP1, PAWR, PAX4, PAX5, PAX6, PBRM1, PCDH10, PCDH17, PCDH8, PCDH9, PCDHGC3, PCGF2, PDCD4, PDCD5, PDGFRL, PDLIM4, PDS5B, PDSS2, PDX1, PEA15, PEBP1, PEG3, PER2, PF4, PFN1, PGR, PGRMC2, PHACTR4, PHB, PHC3, PHF6, PHLDA2, PHLDA3, PHLPP1, PHLPP2, PHOX2A, PIAS1, PIN1, PINX1, PIWIL2, PKD1, PKNOX1, PLA2G16, PLA2G2A, PLA2G7, PLA2R1, PLAGL1, PLCB3, PLCD1, PLCE1, PLD1, PLEKHO1, PLK1, PLK2, PLK5, PLXNC1, PML, PNN, POU2F3, POU6F2, PPARA, PPARG, PPM1A, PPM1L, PPP1CA, PPP1R1B, PPP2CA, PPP2CB, PPP2R1B, PPP2R2C, PPP2R4, PPP2R5C, PPP3CC, PRDM1, PRDM11, PRDM2, PRDM4, PRDM5, PRICKLEI, PRKAA1, PRKAA2, PRKAR1A, PRKCB, PRKCD, PRKCDBP, PRKCE, PRODH, PROXI, PRR5, WSGR Docket No. 63688-708.601

[0319] PTCHI, PTCH2, PTCSC3, PTEN, PTENP1, PTGDR, PTPN1, PTPN11, PTPN12, PTPN13, PTPN2, PTPN23, PTPN6, PTPRC, PTPRD, PTPRJ, PTPRK, PTPRT, PWAR4, PYCARD, PYHIN1, RAB25, RAB7A, RAD23B, RAD51C, RANBP9, RAP1A, RAP1GAP, RARB, RARRES3, RASAL1, RASAL2, RASL10A, RASL1OB, RASL11A, RASSF1, RASSF1O, RASSF2, RASSF3, RASSF4, RASSF5, RASSF8, RBI, RB1CC1, RBBP7, RBBP8, RBL1, RBL2, RBM14, RBM38, RBM4, RBM5, RBM6, RBMS3, RBMX, RBP1, RCHY1, RECK, RFWD2, RHOA, RHOB, RHOBTB2, RINT1, RITA1, RNASEL, RNASET2, RND3, RNF111, RNF144A, RNF180, RNF8, RNH1, ROBO1, ROR2, RPA1, RPL10, RPL11, RPL5, RPRM, RPS6KA2, RPS6KA6, RTN4, RTN4IP1, RUNX1, RUNX2, RUNX3, S1OOA11, S100A2, SAA1, SAFB, SAFB2, SALL2, SALL4, SAMD9L, SASH1, SCGB3A1, SCRIB, SCUBE2, SCYL1, SDHA, SDHB, SDHD, SEC14L2, SELENBP1, SEMA3B, SEMA3F, SERPINB5, SERPINI2, SETD2, SFN, SFRP1, SFRP2, SFRP4, SFRP5, SGMS1, SH2B3, SH3GLB1, SHISA3, SHPRH, SHQ1, SIAH1, SIK1, SIRT1, SIRT2, SIRT3, SIRT4, SIRT6, SKIL, SKP2, SLC39A1, SLC39A4, SLC5A8, SLC9A3R1, SLIT2, SLX4, SMAD2, SMAD4, SMARCA2, SMARCA4, SMARCB1, SMARCC1, SMCHD1, SMYD4, SNORD50A, SOCS1, SOCS3, SOD2, SOX1, SOX11, SOX15, SOX7, SP1OO, SPARC, SPARCL1, SPI1, SPINK7, SPINT2, SPOP, SPRY2, SPRY4, SPTBN1, SRGAP3, SRPX, SSBP2, ST13, ST20, ST5, ST7, STARD13, STAT1, STAT3, STAT5A, STK10, STK11, S TRAD A, STUB1, SUFU, SUZ12, SYK, SYNM, SYNPO2, SYT13, TAGLN, TANK, TAT, TBL2, TBRG1, TBX5, TCEAL7, TCEB3, TCF3, TCF4, TCF7L2, TCHP, TDGF1, TDRG1, TES, TET2, TFAP2A, TFPI2, TGFB1, TGFBI, TGFBR2, TGFBR3, TGM3, THBD, THBS1, THRA, THRB, THSD1, THY1, TIMP3, TMEFF1, TMEFF2, TMEM127, TMPRSS11A, TMPRSS6, TNFAIP3, TNFAIP8L2, TNFRSF10A, TNFRSF10B, TNFRSF12A, TNFRSF18, TNFSF12, TNFSF9, TNK1, TOM1L2, TOPORS, TP53, TP53BP1, TP53BP2, TP53COR1, TP53INP1, TP63, TP73, TPTE2, TREX2, TRIM13, TRIM15, TRIM24, TRIM3, TRIM31, TRIM32, TRIM35, TRIM62, TRIT1, TSC1, TSC2, TSC22D1, TSG101, TSLP, TSPAN13, TSPAN32, TSSC4, TTC4, TTF1, TUSC1, TUSC2, TUSC7, TWIST2, TXNIP, UBE2QL1, UBE4B, UBIAD1, UCHL1, UFL1, UHRF2, UIMC1, UNC5A, UNC5B, UNC5C, UNC5D, USP12, USP33, UVRAG, VDR, VEGFA, VEZT, VHL, VIL1, VIM, VPS53, VSNL1, VTRNA2-1, VWA5A, WDR11, WDR48, WFDC1, WHSC1L1, WIFI, WISP3, WNK2, WNT11, WNT5A, WNT7A, WT1, WWOX, XAF1, XIST, XPO5, XRCC5, YAP1, YPEL3, ZBTB16, ZBTB18, ZBTB4, ZBTB48, ZBTB7C, ZC3H10, ZDHHC2, ZFAS1, ZFHX3, ZFP36, ZFP36L2, ZFP82, ZHX2, ZIC1, ZMYND10, ZMYND11, ZNF185, ZNF292, ZNF366, ZNF382, ZNF668, or ZYX.

[0320]

[0263] In some embodiments, the genes may be associated with cancer diagnostic markers. For example, the genes may comprise one or more genes comprising MUC2, MUC4, MUC5AC, WSGR Docket No. 63688-708.601

[0321] MUC16, CEA, MUC1, ST6GALNAC6, MUC3, MUC5B, MUC6, MUC17, TAG-72, AFP, CEACAM1, CEACAM5, CEACAM6, or CRP.

[0322]

[0264] In some embodiments, the genes may be, or may be associated with, DNA repair genes. For example, the genes may comprise one or more genes comprising ABRAXAS 1, ALKBH2, ALKBH3, APEX1, APEX2, APLF, APTX, ATM, ATR, ATRIP, ATRX, BARD1, BLM, BRCA1, BRCA2, BRIP1, CCNH, CDK7, CETN2, CHAF1A, CHEK1, CHEK2, CLK2, DCLRE1A, DCLRE1B, DCLRE1C, DDB1, DDB2, DMC1, DNA2, DNPH1, DNTT, DUT, EMEI, EME2, ENDOV, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, ERCC6, ERCC8, EX01, EX05, FAAP100, FAAP20, FAAP24, FAN1, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FEN1, GEN1, GTF2E2, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AX, HELQ, HERC2, HFM1, HLTF, HMCES, HUS1, LIG1, LIG3, LIG4, MAD2L2, MBD4, MDC1, MGMT, MLH1, MLH3, MMS19, MNAT1, MPG, MPLKIP, MRE11 A, MSH2, MSH3, MSH4, MSH5, MSH6, MUS81, MUTYH, NABP2, NBN, NEIL1, NEIL2, NEIL3, NHEJ1, NTHL1, NUDT1, NUDT15, NUDT18, OGGI, PALB2, PARG, PARK7, PARP1, PARP2, PARP3, PARPBP, PAXIP1, PCNA, PDS5B, PERI, PMS1, PMS2, PMS2P3, PNKP, POLA1, POLB, POLDI, POLD2, POLD3, POLD4, POLE, POLE2, POLE3, POLE4, POLG, POLH, POLI, POLK, POLL, POLM, POLN, POLQ, PRIMPOL, PRKDC, PRPF19, RADI, RAD 17, RAD 18, RAD23A, RAD23B, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RAD9A, RBBP8, RDM1, RECQL, RECQL4, RECQL5, REV1, REV3L, RIF1, RMI1, RNF168, RNF4, RNF8, RPA1, RPA2, RPA3, RPA4, RRM2B, SEMI, SETMAR, SHLD1, SHLD2, SHLD3, SHPRH, SLX1A, SLX1B, SLX4, SMC5, SMC6, SMUG1, SPIDR, SPO11, SPRTN, SWI5, SWSAP1, TDG, TDP1, TDP2, TFIIH, TOP3A, TOPBP1, TP53, TP53BP1, TREX1, TREX2, UBE2A, UBE2B, UBE2N, UBE2T, UBE2V2, UNG, USP1, UVSSA, WDR48, WRN, XAB2, XPA, XPC, XRCC1, XRCC2, XRCC3, XRCC4, XRCC5, XRCC6, or ZSWIM7.

[0323]

[0265] In some embodiments, the genes may be, or may be associated with, genes that are frequently mutated. For example, the genes may comprise one or more genes comprising ABCA13, ANK2, APC, APOB, ATM, BRAF, COL11A1, CSMD1, CSMD2, CSMD3, CTNNB1, DMD, DNAH11, DNAH5, DNAH8, DNAH9, DST, FAT3, FAT4, FLG, HMCN1, KDM5A, KRAS, LRP1B, LRP2, MACF1, MLL2, MLL3, MUC16, MUC17, MUC4, NEB, NF1, OBSCN, PCDH15, PIK3CA, PKHD1, PTEN, Q9Y6V0-3, RELN, RYR1, RYR2, RYR3, SPTA1, SYNE1, TP53, TTN, USH2A, XIRP2, or ZFHX4.

[0324]

[0266] In some embodiments, the genes may be associated with cancer cell metabolism. For example, the genes may comprise one or more genes comprising AACS, ABCA1, ABCB1, ABCB11, ABCG2, ABCG8, ACACA, ACAD8, ACADM, ACADS, ACAN, ACO1, ACPI, WSGR Docket No. 63688-708.601

[0325] ACPP, ACSL3, ACSL5, ACSL6, ACTB, ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, AGL, AGT, AGXT, AHCY, AKAP5, AKR1B1, AKR1B10, AKT1, ALB, ALDH2, ALG14, ALLC, ALOX12B, ALOX15, ALOX15B, ALOX5, AMPD1, AMY1A, AMY2B, ANP32A, APOA1, APOA2, APOA5, APOE, ARF1, ARFGEF2, ARG1, ARNTL, ARSB, ASL, ASP A, ATIC, B4GALT1, BCKDHA, BGN, BMP1, BSG, C1GALT1C1, CA12, CA2, CA9, CAD, CALR, CANT1, CAT, CAV1, CCNC, CCT5, CCT8, CD36, CD38, CD44, CDK19, CDX2, CERK, CERS2, CHST1, CHST7, CLOCK, CNOT3, CNOT4, CNOT7, COL4A3BP, COMT, CP, CREBBP, CSNK1G2, CTGF, CTNNB1, CTSA, DAO, DCP2, DDX6, DGKA, DGKB, DGKD, DGKE, DGKG, DGKH, DGKI, DGKQ, DGKZ, DGUOK, DIS3, DMGDH, DNMT1, DNMT3A, DNMT3B, DPAGT1, DPM2, DPM3, DPP4, DPYD, EEF1A1, EEF1B2, EIF1AX, EIF2B1, EIF2B2, EIF2B5, EIF2S1, EIF2S2, EIF3E, EIF3H, EIF3I, EIF4A2, EIF4E, EIF4EBP1, EIF4G1, EIF5A, EIF5A2, ELAVL1, ENO1, ENO3, ENTPD5, EP300, EXOSC9, EXT1, EXT2, F10, F2, F7, FABP4, FASN, FAU, FBXL5, FBXO4, FBXO6, FBXW5, FBXW7, FECH, FH, FHIT, FURIN, FXN, G6PD, GALE, GALNT13, GALNT5, GALNTL6, GALT, GAPDH, GCK, GCKR, GK, GLA, GLIPR1, GLUD1, GLUD2, GMPS, GNA11, GNA15, GNAI1, GNAI2, GNAQ, GNAS, GNB4, GNG2, GNMT, GOT1, GPC3, GPC5, GPC6, GPHN, GPI, GPX3, GPX5, GRP, GSPT2, GSTA1, GSTP1, GSTT1, GUCY1A2, GUCY2C, GUCY2D, GUCY2F, GUK1, GUSB, HADHB, HAS2, HDAC3, HEXB, HIF1A, HM0X1, HNMT, HNRNPD, HPD, HPRT1, HSPA1B, HSPA8, HSPB1, HYAL1, IDH1, IDH2, INHA, INHBA, INHBE, INPP4A, INPP4B, INPPL1, INS, ITPA, ITPKA, ITPKB, ITPR3, IYD, KCNC2, KDSR, KIF13A, LALBA, LDHA, LDLR, LMAN1, LRP2, LSM1, LSM2, LTA4H, LUM, MAO A, MAOB, MAPK11, MAPK14, MAPKAPK2, MAT2A, MDH1, MED1, MED12, MED17, MED23, MED24, MED29, MGAM, MGAT5, MIF, MLXIPL, MOCS1, MTAP, MTHFD1, MTHFR, MTOR, MTTP, MUC16, MUC17, MUC4, MUC5B, MUC6, MVK, NAT2, NAT6, NCOA1, NCOA2, NCOA3, NCOA6, NCOR1, NCOR2, NFYA, NFYB, NIT2, NME1, NOS2, NOS3, NPR1, NPR2, NQO1, NR1D1, NT5C3A, NUDT2, NUP107, NUP133, NUP153, NUP210, NUP214, NUP62, NUP88, NUP93, OGDH, OGN, OMD, P4HB, PABPC1, PAFAH1B2, PAH, PAIP1, PARN, PAX6, PDE1B, PDE3B, PDE4B, PDIA3, PDK1, PDK2, PDK3, PDK4, PFDN2, PFDN5, PFKFB1, PHGDH, PHKG2, PI4KA, PIGU, PIK3C2B, PIK3C2G, PIK3C3, PIK3CA, PIK3CB, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R4, PIP5K1A, PLA2G10, PLA2G16, PLA2G1B, PLAUR, PLCB1, PLCB4, PLCD1, PLCE1, PLCG1, PLCG2, PLD1, PLD2, PNLIPRP2, PNPLA3, POLA1, POLDI, POLD3, POLD4, POLE, POLE2, POLR1A, POLR1B, POLR1C, POLR1D, POLR1E, POLR2A, POLR2B, POLR2F, POLR2G, POLR2H, POLR2I, POLR2L, POLR3A, POM121, PPAP2A, PPARA, PPARG, PPM1L, PPP1CC, PPP2CA, PPP2CB, PPP2R1A, PPP2R1B, PPP2R2A, WSGR Docket No. 63688-708.601

[0326] PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACA, PRKACB, PRKACG, PRKAG2, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCA, PRKCD, PRKCSH, PRKD1, PRMT5, PROC, PRODH, PROS1, PRPS1, PSMA6, PSMB5, PSMC1, PSMC2, PSMC3, PSMD1, PSMD11, PSMD12, PSMD13, PSMD3, PSMD6, PSMD7, PTEN, PTGES, PTGS1, PTGS2, RANBP2, RAP1A, RAP1B, RAPGEF3, RAPGEF4, RDH5, RORA, RPE65, RPL10, RPL11, RPL22, RPL30, RPL4, RPL5, RPL7A, RPN1, RPS10, RPS11, RPS13, RPS15, RPS2, RPS27, RPS29, RPS3, RQCD1, RRM1, RRM2B, RXRA, SDC2, SDC4, SDHB, SDHC, SDHD, SEC24D, SEC31A, SEPHS2, SHMT1, SI, SIN3A, SLC10A2, SLC16A1, SLC2A5, SLC44A1, SLC44A3, SLC5A5, SLC5A6, SLC9A1, SLCO1B1, SMG1, SMG5, SMG8, SMN1, SMPD2, SNRPE, SPHK1, SPHK2, SREBF1, SRPR, ST6GALNAC3, STK11, STXBP1, SULT1A1, TBL1XR1, TH, TK1, TNPO1, TP53, TPH1, TPO, TPR, TPTE2, TRIB3, TUBA1A, TUSC3, TYMS, TYRP1, UGT1A9, UGT2A3, UGT2B10, UPF3B, UPP1, UROS, USP11, VBP1, VCAN, VDAC1, WBSCR17, WWTR1, XDH, XPO1, XRN1, YAP1, YWHAB, YWHAZ, ZFP36, or ZFP36Ll.

[0327]

[0267] In some embodiments, the genes may be associated with epigenetic regulators. For example, the genes may comprise one or more genes comprising DNMT1, DNMT3A, DNMT3B, DNMT3L, H2AFB1, H2AFX, H2AFZ, H2BFS, H3F3A, HIST1H2AB, HIST1H2AC, HIST1H2AD, HIST1H2AJ, HIST1H2BA, HIST1H2BB, HIST1H2BC, HIST1H2BD, HIST1H2BH, HIST1H2BJ, HIST1H2BK, HIST1H2BL, HIST1H2BM, HIST1H2BN, HIST1H2BO, HIST1H3A, HIST1H4A, HIST2H2AA3, HIST2H2AC, HIST2H2BE, HIST2H3A, HIST3H2BB, UHRF1, ACTB, ACTL6A, ACTL6B, ACTR6, ACTR8, ANP32E, ARID1A, ARID1B, ATRX, BAHD1, BAZ1A, BAZ1B, BAZ2A, BPTF, BRDT, CASC5, CBX3, CDKN2A, CECR2, CENPA, CENPC, CENPH, CENPI, CENPK, CENPL, CENPM, CENPN, CENPO, CENPP, CENPQ, CENPT, CENPU, CENPV, CENPW, CHD1, CHD1L, CHD4, CHD5, CHD8, CHEK1, CHRAC1, DAXX, DMAP1, ESRI, FOXA1, FOXP3, GATAD2B, HDAC1, HDAC2, HDAC4, HDAC5, HELLS, HJURP, HMG20A, HMG20B, HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGB4, HMGXB4, HNRNPC, INO80, INO80B, INO80C, ITGB3BP, KAT2A, KAT2B, KLF1, KMT2B, MBD2, MBD3, MEN1, MIS18A, MIS18BP1, MTA2, MYB, MYC, MYSM1, NASP, NPM1, NPM2, OIP5, PADI2, PADI4, PAX7, PBRM1, PSME4, RBI, RBBP4, RBBP7, RERE, RNF8, RSF1, RUVBL1, RUVBL2, SATB1, SATB2, APBB1, ATF2, BRCA2, BRD1, BRD4, BRD8, BRPF1, BRPF3, CCDC101, CDYL, CLOCK, CPA4, CREBBP, CRTC2, CSRP2BP, DR1, ELP3, ELP4, EP300, EP400, EPCI, GTF3C4, HAT1, HCFC1, ING3, ING4, ING5, IRF4, JADE1, JADE2, JADE3, KANSL1, KANSL2, KANSL3, KAT5, KAT6A, KAT6B, KAT7, KAT8, KMT2A, LDB1, LEF1, MAP3K7, MBIP, MCRS1, MEAF6, MECP2, MED24, MGEA5, MORF4L1, WSGR Docket No. 63688-708.601

[0328] MSL1, MSL2, MSL3, MYODI, NAA50, NAA60, NCOA1, NCOA2, NCOA3, OGT, PCGF2, PERI, PHF20, POLE3, POLE4, SAP130, SMARCA4, SPI1, SRCAP, SUPT3H, SUPT7L, TADA1, TADA2A, TADA3, TAF1, TAF10, TAF1L, TAF5, TAF5L, TAF6L, TAF9, TCF3, TRIM16, TRRAP, USP22, WDR5, YEATS2, or YEATS4.

[0329]

[0268] In some embodiments, the genes may be associated with one or more pathways in cancer. For example, the genes may comprise one or more genes comprising ABL1, ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, AGT, AGTR1, AKT1, AKT2, AKT3, ALK, APAF1, APC, APC2, APPL1, AR, ARAF, ARHGEF1, ARHGEF11, ARHGEF12, ARNT, ARNT2, AXIN1, AXIN2, BAD, BAK1, BAX, BBC3, BCL2, BCL2L1, BCL2L11, BCR, BDKRB1, BDKRB2, BID, BIRC2, BIRC3, BIRC5, BIRC7, BMP2, BMP4, BRAF, BRCA2, CALM1, CALM2, CALM3, CALML3, CALML4, CALML5, CALML6, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CASP3, CASP7, CASP8, CASP9, CBL, CCDC6, CCNA1, CCNA2, CCND1, CCND2, CCND3, CCNE1, CCNE2, CDC42, CDH1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CEBPA, CHUK, CKS1B, CKS2, COL4A1, COL4A2, COL4A3, COL4A4, COL4A5, COL4A6, CREBBP, CRK, CRKL, CSF1R, CSF2RA, CSF2RB, CSF3R, CTBP1, CTBP2, CTNNA1, CTNNA2, CTNNA3, CTNNB1, CUL1, CUL2, CXCL12, CXCL8, CXCR4, CYCS, DAPK1, DAPK2, DAPK3, DCC, DDB2, DLL1, DLL3, DLL4, DVL1, DVL2, DVL3, E2F1, E2F2, E2F3, EDN1, EDNRA, EDNRB, EGF, EGFR, EGLN1, EGLN2, EGLN3, ELK1, ELOB, ELOC, EML4, EP300, EPAS1, EPO, EPOR, ERBB2, ESRI, ESR2, ETS1, F2, F2R, F2RL3, FADD, FAS, FASLG, FGF1, FGF10, FGF16, FGF17, FGF18, FGF19, FGF2, FGF20, FGF21, FGF22, FGF23, FGF3, FGF4, FGF5, FGF6, FGF7, FGF8, FGF9, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLT3, FLT3LG, FLT4, FN1, FOS, FOXO1, FRAT1, FRAT2, FZD1, FZD10, FZD2, FZD3, FZD4, FZD5, FZD6, FZD7, FZD8, FZD9, GADD45A, GADD45B, GADD45G, GLI1, GLI2, GLI3, GNA11, GNA12, GNA13, GNAI1, GNAI2, GNAI3, GNAQ, GNAS, GNB1, GNB2, GNB3, GNB4, GNB5, GNG10, GNG11, GNG12, GNG13, GNG2, GNG3, GNG4, GNG5, GNG7, GNG8, GNGT1, GNGT2, GRB2, GSK3B, GSTA1, GSTA2, GSTA3, GSTA4, GSTA5, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO1, GSTO2, GSTP1, GSTT1, GSTT2, GSTT2B, HDAC1, HDAC2, HES1, HES5, HEY1, HEY2, HEYL, HGF, HHIP, HIF1A, HM0X1, HRAS, HSP90AA1, HSP90AB1, HSP90B1, IFNA1, IFNA10, IFNA13, IFNA14, IFNA16, IFNA17, IFNA2, IFNA21, IFNA4, IFNA5, IFNA6, IFNA7, IFNA8, IFNAR1, IFNAR2, IFNG, IFNGR1, IFNGR2, IGF1, IGF1R, IGF2, IKBKB, IKBKG, IL12A, IL12B, IL12RB1, IL12RB2, IL13, IL13RA1, IL15, IL15RA, IL2, IL23A, IL23R, IL2RA, IL2RB, IL2RG, IL3, IL3RA, IL4, IL4R, IL5, IL5RA, IL6, IL6R, IL6ST, IL7, IL7R, ITGA2, ITGA2B, ITGA3, ITGA6, ITGAV, ITGB1, JAG1, JAG2, JAK1, JAK2, JAK3, JUN, JUP, KEAP1, KIF7, KIT, KITLG, KLK3, KNG1, WSGR Docket No. 63688-708.601

[0330] KRAS, LAMA1, LAMA2, LAMA3, LAMA4, LAMA5, LAMB1, LAMB2, LAMB3, LAMB4, LAMC1, LAMC2, LAMC3, LEF1, LPAR1, LPAR2, LPAR3, LPAR4, LPAR5, LPAR6, LRP5, LRP6, MAP2K1, MAP2K2, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MAX, MDM2, MECOM, MET, MGST1, MGST2, MGST3, MITF, MLH1, MMP1, MMP2, MMP9, MSH2, MSH3, MSH6, MTOR, MYC, NCOA1, NCOA3, NCOA4, NFE2L2, NFKB1, NFKB2, NFKBIA, NKX3-1, NOS2, NOTCH1, NOTCH2, NOTCH3, NOTCH4, NQO1, NRAS, NTRK1, PAX8, PDGFA, PDGFB, PDGFRA, PDGFRB, PGF, PIK3CA, PIK3CB, PIK3CD, PIK3R1, PIK3R2, PIK3R3, PIM1, PIM2, PLCB1, PLCB2, PLCB3, PLCB4, PLCG1, PLCG2, PLD1, PLD2, PLEKHG5, PMAIP1, PML, POLK, PPARD, PPARG, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB, PRKCG, PTCHI, PTCH2, PTEN, PTGER1, PTGER2, PTGER3, PTGER4, PTGS2, PTK2, RAC1, RAC2, RAC3, RAD51, RAFI, RALA, RALB, RALBP1, RALGDS, RARA, RARB, RASGRP1, RASGRP2, RASGRP3, RASGRP4, RASSF1, RASSF5, RBI, RBX1, RELA, RET, RHOA, ROCK1, ROCK2, RPS6KA5, RPS6KB1, RPS6KB2, RUNX1, RUNX1T1, RXRA, RXRB, RXRG, SHH, SKP1, SKP2, SLC2A1, SMAD2, SMAD3, SMAD4, SMO, SOS1, SOS2, SP1, SPI1, STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, STAT6, STK4, SUFU, TCF7, TCF7L1, TCF7L2, TERC, TERT, TFG, TGFA, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TP53, TPM3, TPR, TRAF1, TRAF2, TRAF3, TRAF4, TRAF5, TRAF6, TXNRD1, TXNRD2, TXNRD3, VEGFA, VEGFB, VEGFC, VEGFD, VHL, WNT1, WNT10A, WNT10B, WNT11, WNT16, WNT2, WNT2B, WNT3, WNT3A, WNT4, WNT5A, WNT5B, WNT6, WNT7A, WNT7B, WNT8A, WNT8B, WNT9A, WNT9B, XIAP, ZBTB16, or ZBTB17.

[0331]

[0269] In some embodiments, the genes may be, or may be associated with, rate limiting genes (metabolism). For example, the genes may comprise one or more genes comprising ACACA, ACACB, ACADL, ACADS, ACOX1, ACOX3, ACSL1, ADH1A, ADH1B, ADH1C, ADH4, ADH6, ADK, ALAD, ALAS1, ALDH1B1, ALDH2, ALDH7A1, ALDH9A1, BCHE, BCKDHA, BCKDHB, CAD, CBS, CPT2, CTPS, CTPS2, CYP1A2, CYP2A6, CYP2B6, CYP2C18, CYP2C8, CYP2C9, CYP2J2, CYP39A1, CYP3A4, CYP3A43, DHODH, DLD, DTYMK, EHHADH, FBP1, G6PD, GATM, GGT5, GNE, GPD2, GSTZ1, GYS2, HADH, HMGCS2, HSD17B10, HSD17B4, HSD17B6, IDO2, IMPDH1, IMPDH2, KMO, LIPA, LIPC, LIPG, MAN2B2, MGST1, MGST2, NT5C3, OGDHL, PAH, PANK1, PANK4, PCK2, PIP4K2B, PIP5K1A, PKM2, PLA2G12A, PLA2G5, PNPO, PPAP2B, PTGS2, PTS, PYGL, RDH5, RRM1, RRM2, SAT1, SOAT2, SQLE, SRM, SUCLA2, TAT, TDO2, TK1, TK2, TKT, TYMS, UCK2, UCKL1, or XDH.

[0332]

[0270] In some embodiments, the genes may be associated with cancer cell metabolism. For example, the genes may comprise one or more genes comprising AACS, ABCA1, ABCB1, WSGR Docket No. 63688-708.601

[0333] ABCB11, ABCG2, ABCG8, ACACA, ACAD8, ACADM, ACADS, ACAN, AC01, ACPI, ACPP, ACSL3, ACSL5, ACSL6, ACTB, ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, AGL, AGT, AGXT, AHCY, AKAP5, AKR1B1, AKR1B10, AKT1, ALB, ALDH2, ALG14, ALLC, ALOX12B, ALOX15, ALOX15B, ALOX5, AMPD1, AMY1A, AMY2B, ANP32A, APOA1, APOA2, APOA5, APOE, ARF1, ARFGEF2, ARG1, ARNTL, ARSB, ASL, ASP A, ATIC, B4GALT1, BCKDHA, BGN, BMP1, BSG, C1GALT1C1, CA12, CA2, CA9, CAD, CALR, CANT1, CAT, CAV1, CCNC, CCT5, CCT8, CD36, CD38, CD44, CDK19, CDX2, CERK, CERS2, CHST1, CHST7, CLOCK, CNOT3, CNOT4, CNOT7, COL4A3BP, COMT, CP, CREBBP, CSNK1G2, CTGF, CTNNB1, CTSA, DAO, DCP2, DDX6, DGKA, DGKB, DGKD, DGKE, DGKG, DGKH, DGKI, DGKQ, DGKZ, DGUOK, DIS3, DMGDH, DNMT1, DNMT3A, DNMT3B, DPAGT1, DPM2, DPM3, DPP4, DPYD, EEF1A1, EEF1B2, EIF1AX, EIF2B1, EIF2B2, EIF2B5, EIF2S1, EIF2S2, EIF3E, EIF3H, EIF3I, EIF4A2, EIF4E, EIF4EBP1, EIF4G1, EIF5A, EIF5A2, ELAVL1, ENO1, ENO3, ENTPD5, EP300, EXOSC9, EXT1, EXT2, F10, F2, F7, FABP4, FASN, FAU, FBXL5, FBXO4, FBXO6, FBXW5, FBXW7, FECH, FH, FHIT, FURIN, FXN, G6PD, GALE, GALNT13, GALNT5, GALNTL6, GALT, GAPDH, GCK, GCKR, GK, GLA, GLIPR1, GLUD1, GLUD2, GMPS, GNA11, GNA15, GNAI1, GNAI2, GNAQ, GNAS, GNB4, GNG2, GNMT, GOT1, GPC3, GPC5, GPC6, GPHN, GPI, GPX3, GPX5, GRP, GSPT2, GSTA1, GSTP1, GSTT1, GUCY1A2, GUCY2C, GUCY2D, GUCY2F, GUK1, GUSB, HADHB, HAS2, HDAC3, HEXB, HIF1A, HM0X1, HNMT, HNRNPD, HPD, HPRT1, HSPA1B, HSPA8, HSPB1, HYAL1, IDH1, IDH2, INHA, INHBA, INHBE, INPP4A, INPP4B, INPPL1, INS, ITPA, ITPKA, ITPKB, ITPR3, IYD, KCNC2, KDSR, KIF13A, LALBA, LDHA, LDLR, LMAN1, LRP2, LSM1, LSM2, LTA4H, LUM, MAO A, MAOB, MAPK11, MAPK14, MAPKAPK2, MAT2A, MDH1, MED1, MED12, MED17, MED23, MED24, MED29, MGAM, MGAT5, MIF, MLXIPL, MOCS1, MTAP, MTHFD1, MTHFR, MTOR, MTTP, MUC16, MUC17, MUC4, MUC5B, MUC6, MVK, NAT2, NAT6, NCOA1, NCOA2, NCOA3, NCOA6, NCOR1, NCOR2, NFYA, NFYB, NIT2, NME1, NOS2, NOS3, NPR1, NPR2, NQO1, NR1D1, NT5C3A, NUDT2, NUP107, NUP133, NUP153, NUP210, NUP214, NUP62, NUP88, NUP93, OGDH, OGN, OMD, P4HB, PABPC1, PAFAH1B2, PAH, PAIP1, PARN, PAX6, PDE1B, PDE3B, PDE4B, PDIA3, PDK1, PDK2, PDK3, PDK4, PFDN2, PFDN5, PFKFB1, PHGDH, PHKG2, PI4KA, PIGU, PIK3C2B, PIK3C2G, PIK3C3, PIK3CA, PIK3CB, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R4, PIP5K1A, PLA2G10, PLA2G16, PLA2G1B, PLAUR, PLCB1, PLCB4, PLCD1, PLCE1, PLCG1, PLCG2, PLD1, PLD2, PNLIPRP2, PNPLA3, POLA1, POLDI, POLD3, POLD4, POLE, POLE2, POLR1A, POLR1B, POLR1C, POLR1D, POLR1E, POLR2A, POLR2B, POLR2F, POLR2G, POLR2H, POLR2I, POLR2L, POLR3A, POM121, PPAP2A, WSGR Docket No. 63688-708.601

[0334] PPARA, PPARG, PPM1L, PPP1CC, PPP2CA, PPP2CB, PPP2R1A, PPP2R1B, PPP2R2A, PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACA, PRKACB, PRKACG, PRKAG2, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCA, PRKCD, PRKCSH, PRKD1, PRMT5, PROC, PRODH, PROS1, PRPS1, PSMA6, PSMB5, PSMC1, PSMC2, PSMC3, PSMD1, PSMD11, PSMD12, PSMD13, PSMD3, PSMD6, PSMD7, PTEN, PTGES, PTGS1, PTGS2, RANBP2, RAP1A, RAP1B, RAPGEF3, RAPGEF4, RDH5, RORA, RPE65, RPL10, RPL11, RPL22, RPL30, RPL4, RPL5, RPL7A, RPN1, RPS10, RPS11, RPS13, RPS15, RPS2, RPS27, RPS29, RPS3, RQCD1, RRM1, RRM2B, RXRA, SDC2, SDC4, SDHB, SDHC, SDHD, SEC24D, SEC31A, SEPHS2, SHMT1, SI, SIN3A, SLC10A2, SLC16A1, SLC2A5, SLC44A1, SLC44A3, SLC5A5, SLC5A6, SLC9A1, SLCO1B1, SMG1, SMG5, SMG8, SMN1, SMPD2, SNRPE, SPHK1, SPHK2, SREBF1, SRPR, ST6GALNAC3, STK11, STXBP1, SULT1A1, TBL1XR1, TH, TK1, TNPO1, TP53, TPH1, TPO, TPR, TPTE2, TRIB3, TUBA1A, TUSC3, TYMS, TYRP1, UGT1A9, UGT2A3, UGT2B10, UPF3B, UPP1, UROS, USP11, VBP1, VCAN, VDAC1, WBSCR17, WWTR1, XDH, XPO1, XRN1, YAP1, YWHAB, YWHAZ, ZFP36, or ZFP36Ll.

[0335]

[0271] In some embodiments, the genes may be, or may be associated with, cell metabolism. For example, the genes may comprise one or more genes comprising A2M, AAAS, AACS, AADAT, AANAT, AASDHPPT, AASS, ABAT, ABCA1, ABCB1, ABCB11, ABCB4, ABCC3, ABCC5, ABCC8, ABCD1, ABCG1, ABCG2, ABCG5, ABCG8, ABHD5, ACAA1, ACAA2, ACACA, ACACB, ACAD8, ACADL, ACADM, ACADS, ACADSB, ACADVL, ACAN, ACAT1, ACAT2, ACER1, ACER2, ACER3, ACHE, ACLY, ACMSD, ACO1, ACO2, ACOT12, ACOT8, ACOX1, ACOX2, ACOX3, ACPI, ACP2, ACP5, ACP6, ACPP, ACPT, ACSL1, ACSL3, ACSL4, ACSL5, ACSL6, ACSM1, ACSM2A, ACSM3, ACSM4, ACSM5, ACSS1, ACSS2, ACSS3, ACTB, ACY1, ACY3, ACYP1, ACYP2, ADA, AD AL, ADCY1, ADCY10, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, ADH1A, ADH1B, ADH1C, ADH4, ADH5, ADH6, ADH7, ADHFE1, ADI1, ADK, ADO, ADRA2A, ADSL, ADSS, ADSSL1, AFMID, AGK, AGL, AGMAT, AGP ATI, AGPAT2, AGPAT3, AGPAT4, AGPAT5, AGPAT6, AGPAT9, AGPS, AGRN, AGT, AGXT, AGXT2, AHCY, AHCYL1, AHCYL2, AK1, AK2, AK3, AK4, AK5, AK7, AKAP5, AKR1A1, AKR1B1, AKR1B10, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR1D1, AKT1, ALAD, ALAS1, ALAS2, ALB, ALDH18A1, ALDH1A1, ALDH1A2, ALDH1A3, ALDH1B1, ALDH2, ALDH3A1, ALDH3A2, ALDH3B1, ALDH3B2, ALDH4A1, ALDH5A1, ALDH6A1, ALDH7A1, ALDH9A1, ALDOA, ALDOB, ALDOC, ALG1, ALG10, ALG10B, ALG11, ALG12, ALG13, ALG14, ALG2, ALG3, ALG5, ALG6, ALG8, ALG9, ALLC, ALOX12, ALOX12B, ALOX15, ALOX15B, ALOX5, AMACR, AMD1, AMDHD1, AMDHD2, AMN, WSGR Docket No. 63688-708.601

[0336] AMPD1, AMPD2, AMPD3, AMT, AMY1A, AMY1B, AMY1C, AMY2A, AMY2B, ANGPTL4, ANKRD1, ANP32A, ANPEP, A0C2, A0C3, A0X1, AP3M1, APIP, APOA1, APOA2, APOA5, APOB, APOC2, APOC3, APOE, APRT, ARF1, ARF3, ARFGEF2, ARG1, ARG2, ARNTL, ARSA, ARSB, ARSE, ARSF, ARSG, ARSH, ARSI, ARSJ, ARSK, ASAHI, ASAH2, ASL, ASMT, ASNS, ASP A, ASS1, ATIC, ATP5A1, ATP5B, ATP5G1, AUH, AWAT2, AZINI, AZIN2, B3GALT6, B3GAT1, B3GAT2, B3GAT3, B3GNT2, B3GNT3, B3GNT4, B3GNT5, B3GNT6, B3GNT7, B3GNT8, B3GNT9, B3GNTL1, B4GALT1, B4GALT2, B4GALT3, B4GALT4, B4GALT5, B4GALT6, B4GALT7, BAAT, BBOX1, BCAN, BCAT1, BCAT2, BCKDHA, BCKDHB, BCO1, BCS1L, BDH1, BDH2, BGN, BHMT, BLVRA, BLVRB, BMP1, BPGM, BPNT1, BSG, BST1, C1GALT1, C1GALT1C1, CAI, CA12, CAB, CAM, CA2, CA3, CA4, CA5A, CA5B, CA6, CA7, CA8, CA9, CACNA1A, CACNB2, CACNB3, CAD, CALM1, CALM2, CALM3, CALR, CANT1, CANX, CASC3, CAT, CAV1, CBR1, CBR3, CBS, CCBL1, CCBL2, CCNC, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT7, CCT8, CD36, CD38, CD44, CDA, CDIPT, CDK19, CDK8, CDO1, CDS1, CDS2, CDX2, CEL, CEPT1, CERK, CERS2, CERS3, CERS4, CERS5, CERS6, CES1, CES2, CES5A, CETP, CGA, CGB, CGB5, CGB8, CH25H, CHAT, CHCHD4, CHDH, CHIA, CHIT1, CHKA, CHKB, CHPF, CHPF2, CHPT1, CHRM3, CHST1, CHST11, CHST12, CHST13, CHST14, CHST15, CHST2, CHST3, CHST5, CHST6, CHST7, CHST9, CHSY1, CHSY3, CKB, CKM, CKMT1A, CKMT1B, CKMT2, CLNS1A, CLOCK, CLPS, CMAS, CMPK1, CMPK2, CNDP1, CNDP2, CNOTIO, CNOT2, CNOT3, CNOT4, CNOT6, CNOT7, CNOT8, COASY, COL4A3BP, COMT, COQ2, COXIO, COX15, COX17, CP, CPOX, CPS1, CPT1A, CPT1B, CPT1C, CPT2, CRAT, CREBBP, CRLS1, CROT, CS, CSAD, CSGALNACT1, CSGALNACT2, CSNK1G2, CSPG4, CTGF, CTH, CTNNB1, CTPS1, CTPS2, CTSA, CUBN, CYC1, D2HGDH, DADI, DAK, DAO, DBH, DBT, DCK, DCN, DCP1A, DCP1B, DCP2, DCPS, DCT, DCTD, DDC, DDO, DDOST, DDX20, DDX6, DECR1, DEGS1, DEGS2, DGAT1, DGAT2, DGKA, DGKB, DGKD, DGKE, DGKG, DGKH, DGKI, DGKQ, DGKZ, DGUOK, DHCR24, DHCR7, DHDH, DHFR, DHODH, DHPS, DHRS3, DHRS4, DHRS4L2, DHRS9, DIO1, DIO2, DIO3, DIS3, DLAT, DLD, DLST, DMGDH, DNAJC19, DNMT1, DNMT3A, DNMT3B, DNMT3L, DOHH, DOLK, DOLPP1, DPAGT1, DPMI, DPM2, DPM3, DPP4, DPYD, DPYS, DSE, DTYMK, DUT, EARS2, EBP, ECHS1, ECU, ECI2, EDC3, EDC4, EDEMI, EDEM2, EDEM3, EEF1A1, EEF1B2, EEF1D, EEF1G, EEF2, EHHADH, EIF1AX, EIF2B1, EIF2B2, EIF2B3, EIF2B4, EIF2B5, EIF2S1, EIF2S2, EIF2S3, EIF3A, EIF3B, EIF3C, EIF3D, EIF3E, EIF3F, EIF3G, EIF3H, EIF3I, EIF3J, EIF3K, EIF4A1, EIF4A2, EIF4A3, EIF4B, EIF4E, EIF4EBP1, EIF4G1, EIF4H, EIF5, EIF5A, EIF5A2, EIF5B, ELAVL1, ELOVL1, ELOVL2, ELOVL3, ELOVL4, ELOVL5, ELOVL6, ELOVL7, ENO1, ENO2, WSGR Docket No. 63688-708.601

[0337] EN03, EN0PH1, ENPP1, ENPP2, ENPP3, ENPP6, ENPP7, ENTPD1, ENTPD2, ENTPD3, ENTPD4, ENTPD5, ENTPD6, ENTPD8, EP300, EPHX1, EPHX2, EPRS, EPT1, ESRRA, ETF1, ETHE1, ETNK1, ETNK2, EXOSC1, EXOSC2, EXOSC3, EXOSC4, EXOSC5, EXOSC6, EXOSC7, EXOSC8, EXOSC9, EXT1, EXT2, F10, F2, F7, F9, FABP1, FABP4, FABP6, FADS1, FADS2, FAH, FAM153A, FAR1, FAR2, FASN, FAU, FBP1, FBP2, FBXL3, FBXL5, FBXO4, FBXO6, FBXW2, FBXW4, FBXW5, FBXW7, FDFT1, FDPS, FECH, FFAR1, FFAR4, FH, FHIT, FHL2, FIG4, FKBP9, FLAD1, FM01, FMO2, FMO3, FMO4, FMO5, FMOD, FPGS, FPGT, FSHB, FTCD, FTH1, FTMT, FUK, FURIN, FUT8, FXN, G0S2, G6PC, G6PC2, G6PC3, G6PD, GAA, GAD1, GAD2, GAL3ST1, GALC, GALE, GALK1, GALK2, GALM, GALNT1, GALNT10, GALNT11, GALNT12, GALNT13, GALNT14, GALNT15, GALNT16, GALNT18, GALNT2, GALNT3, GALNT5, GALNT6, GALNT7, GALNT8, GALNT9, GALNTL5, GALNTL6, GALT, GAMT, GANAB, GANC, GAPDH, GAPDHS, GART, GATA4, GATM, GBA, GBA2, GBA3, GBE1, GC, GCAT, GCDH, GCG, GCGR, GCK, GCKR, GCLC, GCLM, GCNT1, GCNT3, GCNT4, GCNT6, GDA, GEMIN2, GEMIN4, GEMIN5, GEMIN6, GEMIN7, GFER, GFPT1, GFPT2, GGCT, GGCX, GGPS1, GGT1, GGT5, GGT6, GGT7, GIP, GK, GK2, GLA, GLB1, GLCE, GLDC, GLIPR1, GLO1, GLP1R, GLRX, GLS, GLS2, GLUD1, GLUD2, GLUL, GLYCTK, GM2A, GMDS, GMPPA, GMPPB, GMPR, GMPR2, GMPS, GNA11, GNA14, GNA15, GNAI1, GNAI2, GNAO1, GNAQ, GNAS, GNB1, GNB2, GNB3, GNB4, GNB5, GNE, GNG10, GNG11, GNG12, GNG13, GNG2, GNG3, GNG4, GNG5, GNG7, GNG8, GNGT1, GNGT2, GNMT, GNPAT, GNPDA1, GNPDA2, GNPNAT1, GNS, GOT1, GOT2, GPAA1, GPAM, GPAT2, GPC1, GPC2, GPC3, GPC4, GPC5, GPC6, GPCPD1, GPD1, GPD1L, GPD2, GPHN, GPI, GPR119, GPT, GPT2, GPX1, GPX2, GPX3, GPX4, GPX5, GPX6, GPX7, GRHL1, GRHPR, GRP, GRPEL1, GRPEL2, GSPT2, GSR, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTA5, GSTK1, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO1, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, GUCY1A2, GUCY1A3, GUCY1B3, GUCY2C, GUCY2D, GUCY2F, GUK1, GUSB, GXYLT1, GXYLT2, GYG1, GYG2, GYSI, GYS2, HAAO, HACL1, HADH, HADHA, HADHB, HAGH, HAGHL, HAL, HAO1, HAO2, HAS1, HAS2, HAS3, HCCS, HDAC3, HDC, HEMK1, HEXA, HEXB, HGD, HIBADH, HIBCH, HIF1A, HK1, HK2, HK3, HMBS, HMGCL, HMGCR, HMGCS1, HMGCS2, HMMR, HM0X1, HM0X2, HNMT, HNRNPD, HPD, HPGDS, HPRT1, HPSE, HPSE2, HS2ST1, HS3ST1, HS3ST2, HS3ST3A1, HS3ST3B1, HS3ST4, HS3ST5, HS3ST6, HS6ST1, HS6ST2, HS6ST3, HSCB, HSD11B1, HSD17B1, HSD17B10, HSD17B12, HSD17B3, HSD17B4, HSD17B7, HSD3B1, HSD3B2, HSD3B7, HSPA1B, HSPA8, HSPA9, HSPB1, HSPD1, HSPG2, HYAL1, HYAL2, HYI, IDH1, IDH2, IDH3A, IDH3B, IDH3G, IDI1, IDI2, IDO1, IDO2, IDS, IDUA, IL4H, IMPA1, IMPA2, WSGR Docket No. 63688-708.601

[0338] IMPDH1, IMPDH2, INHA, INHBA, INHBB, INHBC, INHBE, INMT, INPPI, INPP4A, INPP4B, INPP5A, INPP5B, INPP5E, INPP5J, INPP5K, INPPL1, INS, IPMK, IPPK, IQGAP1, ISL1, ISYNA1, ITPA, ITPK1, ITPKA, ITPKB, ITPR2, ITPR3, IVD, IYD, JMJD7-PLA2G4B, KCNB1, KCNC2, KCNG2, KCNJ11, KCNS3, KDSR, KERA, KHK, KHSRP, KIF13A, KIFC3, KMO, KYNU, L2HGDH, LALBA, LAP3, LBR, LCAT, LCLAT1, LCMT1, LCMT2, LCT, LDHA, LDHAL6A, LDHAL6B, LDHB, LDHC, LDHD, LDLR, LDLRAP1, LEP, LGMN, LHB, LIPC, LIPE, LIPF, LIPG, LMAN1, LOC644504, LONP2, LPA, LPCAT1, LPCAT2, LPCAT3, LPCAT4, LPGAT1, LPIN1, LPIN2, LPIN3, LPL, LRAT, LRP2, LSM1, LSM2, LSM3, LSM4, LSM5, LSM6, LSS, LTA4H, LTC4S, LUM, LYPLA1, LYPLA2, LYVE1, MAGOH, MAN1A1, MAN1A2, MAN1B1, MAN1C1, MAN2A1, MANEA, MAOA, MAOB, MAPK1 1, MAPK14, MAPKAPK2, MARCKS, MARS, MARS2, MAT1 A, MAT2A, MAT2B, MBOAT1, MBOAT2, MBOAT7, MCCC1, MCCC2, MCEE, MCFD2, MCTS1, MDH1, MDH2, MEI, ME2, ME3, MED1, MEDIO, MED11, MED12, MED13L, MED14, MED15, MED16, MED17, MED18, MED19, MED20, MED21, MED22, MED23, MED24, MED25, MED26, MED27, MED29, MED30, MED31, MED4, MED6, MED7, MED8, MED9, METTL2B, METTL6, MGAM, MGAT1, MGAT2, MGAT3, MGAT4A, MGAT4B, MGAT4C, MGAT5, MGLL, MGST1, MGST2, MGST3, MIF, MINPP1, MIOX, MLEC, MLX, MLXIPL, MLYCD, MMAB, MOCOS, MOCS1, MOCS2, MOCS3, MOGS, MPI, MPST, MRI1, MSMO1, MTAP, MTHFD1, MTHFD1L, MTHFD2, MTHFD2L, MTHFR, MTM1, MTMR1, MTMR14, MTMR2, MTMR3, MTMR4, MTMR6, MTMR7, MTOR, MTR, MTTP, MTX1, MTX2, MUC12, MUC13, MUC15, MUC16, MUC17, MUC19, MUC2, MUC21, MUC3B, MUC4, MUC5AC, MUC5B, MUC6, MUC7, MUCH, MUT, MVD, MVK, NADK, NADSYN1, NAGK, NAGLU, NAGS, NAMPT, NANP, NANS, NAT1, NAT2, NAT6, NCAN, NCBP1, NCBP2, NCOA1, NCOA2, NCOA3, NCOA6, NCOR1, NCOR2, NDST1, NDST2, NDST3, NDST4, NEU1, NEU2, NEU3, NEW, NFS1, NFYA, NFYB, NIT2, NME1, NME1- NME2, NME2, NME3, NME4, NME5, NME6, NME7, NMNAT1, NMNAT2, NMNAT3, NNMT, NNT, NOP56, NOS1, NOS2, NOS3, NPAS2, NPL, NPR1, NPR2, NQO1, NR1D1, NR2E3, NRF1, NSDHL, NT5C, NT5C1A, NT5C1B, NT5C2, NT5C3A, NT5E, NT5M, NUDT12, NUDT2, NUDT5, NUDT9, NUP107, NUP133, NUP153, NUP155, NUP188, NUP205, NUP210, NUP214, NUP35, NUP37, NUP43, NUP50, NUP54, NUP62, NUP85, NUP88, NUP93, NUPL1, NUPL2, OAT, OAZ1, OAZ2, OAZ3, OCRL, ODC1, OGDH, OGDHL, OGN, OMD, OPLAH, OSBP, OTC, OXCT1, OXCT2, P4HA1, P4HA2, P4HA3, P4HB, PABPC1, PAFAH1B1, PAFAH1B2, PAFAH1B3, PAFAH2, PAH, PAICS, PAIP1, PAM16, PANK1, PANK2, PANK3, PANK4, PAOX, PAPSS1, PAPSS2, PARN, PATL1, PAX6, PC, PCBD1, PCCA, PCCB, PCK1, PCK2, PCSK1, PCYT1A, PCYT1B, PCYT2, WSGR Docket No. 63688-708.601

[0339] PDE10A, PDE11 A, PDE1 A, PDE1B, PDE1C, PDE2A, PDE3A, PDE3B, PDE4A, PDE4B, PDE4C, PDE4D, PDE5A, PDE6A, PDE6B, PDE6C, PDE6D, PDE6G, PDE6H, PDE7A, PDE7B, PDE8A, PDE8B, PDE9A, PDHA1, PDHA2, PDHB, PDHX, PDIA3, PDK1, PDK2, PDK3, PDK4, PDP1, PDP2, PDPR, PDXK, PEMT, PEX11 A, PFAS, PFDN1, PFDN2, PFDN4, PFDN5, PFDN6, PFKFB1, PFKFB2, PFKFB3, PFKFB4, PFKL, PFKM, PFKP, PGAM1, PGAM2, PGAM4, PGAP1, PGD, PGK1, PGK2, PGLS, PGM1, PGM2, PGM2L1, PGM3, PGP, PGS1, PHAX, PHGDH, PHKA1, PHKA2, PHKB, PHKG1, PHKG2, PHOSPHO1, PHPT1, PHYH, PI4K2A, PI4K2B, PI4KA, PI4KB, PIGA, PIGB, PIGC, PIGF, PIGG, PIGH, PIGK, PIGL, PIGM, PIGN, PIGO, PIGP, PIGQ, PIGS, PIGT, PIGU, PIGV, PIGW, PIGX, PIK3C2A, PIK3C2B, PIK3C2G, PIK3C3, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R4, PIK3R5, PIK3R6, PIKFYVE, PIP4K2A, PIP4K2B, PIP4K2C, PIP5K1A, PIP5K1B, PIP5K1C, PIPOX, PISD, PITPNB, PKLR, PKM, PLA2G10, PLA2G12A, PLA2G12B, PLA2G15, PLA2G16, PLA2G1B, PLA2G2A, PLA2G2C, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G4B, PLA2G4C, PLA2G4D, PLA2G4E, PLA2G4F, PLA2G5, PLA2G6, PLA2G7, PLAUR, PLBD1, PLCB1, PLCB2, PLCB3, PLCB4, PLCD1, PLCD3, PLCD4, PLCE1, PLCG1, PLCG2, PLCZ1, PLD1, PLD2, PLD3, PLD4, PLD6, PLIN1, PLIN2, PLTP, PMM1, PMM2, PMPCA, PMPCB, PMVK, PNLIP, PNLIPRP1, PNLIPRP2, PNMT, PNP, PNPLA2, PNPLA3, PNPLA4, PNPLA8, PNPO, PNPT1, POLA1, POLA2, POLDI, POLD2, POLD3, POLD4, POLE, POLE2, POLE3, POLE4, POLR1A, POLR1B, POLR1C, POLR1D, POLR1E, POLR2A, POLR2B, POLR2C, POLR2D, POLR2E, POLR2F, POLR2G, POLR2H, POLR2I, POLR2J, POLR2J2, POLR2J3, POLR2K, POLR2L, POLR3A, POLR3B, POLR3C, POLR3D, POLR3F, POLR3G, POLR3GL, POLR3H, POLR3K, P0M121, POMC, PPAP2A, PPAP2B, PPAP2C, PPARA, PPARG, PPARGC1A, PPARGC1B, PPAT, PPCDC, PPCS, PPM1L, PPOX, PPP1CA, PPP1CB, PPP1CC, PPP2CA, PPP2CB, PPP2R1A, PPP2R1B, PPP2R2A, PPP2R5D, PRDX6, PREB, PRELP, PRIM1, PRIM2, PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACA, PRKACB, PRKACG, PRKAG2, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCA, PRKCD, PRKCSH, PRKD1, PRMT5, PROC, PRODH, PRODH2, PROS1, PROZ, PRPS1, PRPS1L1, PRPS2, PRUNE, PSAP, PSAT1, PSMA1, PSMA2, PSMA3, PSMA4, PSMA5, PSMA6, PSMA7, PSMA8, PSMB1, PSMB10, PSMB2, PSMB3, PSMB4, PSMB5, PSMB6, PSMB7, PSMB8, PSMB9, PSMC1, PSMC2, PSMC3, PSMC4, PSMC5, PSMC6, PSMD1, PSMD10, PSMD11, PSMD12, PSMD13, PSMD14, PSMD2, PSMD3, PSMD4, PSMD5, PSMD6, PSMD7, PSMD8, PSMD9, PSME1, PSME2, PSME4, PSMF1, PSPH, PTDSS1, PTDSS2, PTEN, PTGDS, PTGES, PTGES2, PTGIS, PTGS1, PTGS2, PYCR1, PYCR2, PYCRL, PYGB, PYGL, PYGM, QDPR, QPRT, RAE1, RANBP2, RAP1 A, RAP1B, RAPGEF3, RAPGEF4, RBM8A, RBP2, RDH10, RDH11, WSGR Docket No. 63688-708.601

[0340] RDH12, RDH16, RDH5, RDH8, RENBP, RETSAT, RFK, RFT1, RNPS1, RORA, RPE, RPE65, RPEL1, RPIA, RPL10, RPL10A, RPL11, RPL12, RPL13, RPL13A, RPL14, RPL15, RPL17, RPL18, RPL18A, RPL19, RPL21, RPL22, RPL23, RPL23A, RPL24, RPL26, RPL26L1, RPL27, RPL27A, RPL28, RPL29, RPL3, RPL30, RPL31, RPL32, RPL34, RPL35, RPL35A, RPL36, RPL36A, RPL37, RPL37A, RPL38, RPL39, RPL3L, RPL4, RPL41, RPL5, RPL6, RPL7, RPL7A, RPL8, RPL9, RPLPO, RPLP1, RPLP2, RPN1, RPN2, RPS1O, RPS11, RPS12, RPS13, RPS14, RPS15, RPS15A, RPS16, RPS17, RPS18, RPS19, RPS2, RPS20, RPS21, RPS23, RPS24, RPS25, RPS26, RPS27, RPS27A, RPS28, RPS29, RPS3, RPS3A, RPS4X, RPS4Y1, RPS5, RPS6, RPS7, RPS8, RPS9, RPSA, RQCD1, RRM I, RRM2, RRM2B, RXRA, SACM1L, SAMM50, SAR1B, SARDH, SAT1, SAT2, SC5D, SCARB1, SCLY, SCO2, SCP2, SDC1, SDC2, SDC3, SDC4, SDHA, SDHB, SDHC, SDHD, SDS, SEC11A, SEC11C, SEC13, SEC23A, SEC24B, SEC24C, SEC24D, SEC31A, SEC61A1, SEC61A2, SEC61B, SEC61G, SEH1L, SEMA6D, SEPHS1, SEPHS2, SGMS1, SGMS2, SGPL1, SGPP1, SGPP2, SGSH, SHMT1, SHMT2, SI, SIN3A, SIN3B, SLC1OA1, SLC10A2, SLC16A1, SLC16A3, SLC16A4, SLC16A8, SLC19A1, SLC19A2, SLC19A3, SLC22A1, SLC22A2, SLC22A3, SLC23A1, SLC23A2, SLC25A1, SLC25A10, SLC25A11, SLC25A12, SLC25A13, SLC25A15, SLC25A16, SLC25A17, SLC25A2, SLC25A20, SLC25A21, SLC25A32, SLC25A4, SLC25A5, SLC25A6, SLC27A1, SLC27A2, SLC27A5, SLC2A1, SLC2A2, SLC2A3, SLC2A4, SLC2A5, SLC37A4, SLC44A1, SLC44A2, SLC44A3, SLC44A4, SLC44A5, SLC46A1, SLC5A1, SLC5A5, SLC5A6, SLC6A8, SLC9A1, SLCO1A2, SLCO1B1, SLCO1B3, SMARCD3, SMG1, SMG5, SMG6, SMG7, SMG8, SMG9, SMN1, SMN2, SMOX, SMPD1, SMPD2, SMPD3, SMPD4, SMS, SNAP25, SNRPB, SNRPD1, SNRPD2, SNRPD3, SNRPE, SNRPF, SNRPG, SNUPN, SORD, SPCS1, SPCS2, SPCS3, SPHK1, SPHK2, SPTLC1, SPTLC2, SQLE, SQRDL, SRD5A1, SRD5A2, SRD5A3, SREBF1, SREBF2, SRM, SRP14, SRP19, SRP54, SRP68, SRP72, SRP9, SRPR, SRPRB, SRR, SSR1, SSR2, SSR3, SSR4, ST3GAL1, ST3GAL2, ST3GAL3, ST3GAL6, ST6GAL1, ST6GALNAC2, ST6GALNAC3, ST6GALNAC4, ST8SIA2, ST8SIA3, ST8SIA6, STAB2, STAR, STARD4, STARD5, STARD6, STK11, STS, STT3A, STX1A, STXBP1, SUCLA2, SUCLG1, SUCLG2, SULT1A1, SULT1A2, SULT1A3, SULT1A4, SULT1E1, SULT2A1, SULT2B1, SUMF1, SUMF2, SUOX, SYNJ1, SYNJ2, SYT5, TALDO1, TAT, TAZ, TBCA, TBCB, TBCC, TBCD, TBCE, TBL1X, TBL1XR1, TBXAS1, TCP1, TDO2, TEAD1, TEAD2, TEAD3, TEAD4, TECR, TGS1, TH, THTPA, TIAM2, TIMM10, TIMM10B, TIMM13, TIMM17A, TIMM17B, TIMM22, TIMM23B, TIMM44, TIMM50, TIMM8A, TIMM8B, TIMM9, TK1, TK2, TKT, TKTL1, TM7SF2, TMLHE, TNFRSF21, TNFSF13, TNKS1BP1, TNPO1, TOMM20, TOMM22, TOMM40, TOMM5, TOMM7, TOMM70A, TP53, TPH1, TPH2, TPI1, TPK1, TPMT, TPO, TPR, TPTE2, WSGR Docket No. 63688-708.601

[0341] TRAM1, TRDMT1, TREH, TRIB3, TRMT11, TSHB, TST, TSTA3, TUBA1A, TUBA1B, TUBA1C, TUBA3C, TUBA3D, TUBA4A, TUBB1, TUBB2A, TUBB2B, TUBB3, TUBB4A, TUBB4B, TUBB6, TUSC3, TXN, TXNDC12, TXNRD1, TXNRD2, TYMP, TYMS, TYR, TYRP1, UAP1, UBA52, UCK1, UCK2, UCKL1, UGCG, UGDH, UGGT1, UGGT2, UGP2, UGT1A1, UGT1A10, UGT1A3, UGT1A4, UGT1A5, UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT2A1, UGT2A3, UGT2B10, UGT2B11, UGT2B15, UGT2B17, UGT2B28, UGT2B4, UGT2B7, UGT8, UMPS, UPB1, UPF2, UPF3A, UPF3B, UPP1, UPP2, UPRT, UR AD, UROCI, UROD, UROS, USP11, UST, UXS1, VAC14, VAMP2, VAPA, VAPB, VBP1, VC AN, VDAC1, VKORC1, WARS, WARS2, WBSCR17, WBSCR22, WDR77, WWTR1, XDH, XPO1, XRN1, XRN2, YAP1, YWHAB, YWHAZ, ZFP36, ZFP36L1, or ZNRDl.

[0342]

[0272] In some embodiments, the genes may be associated with pathways, for example, pathways in cancer. In some embodiments, the genes may be associated with pathways in a non-cancerous condition, for example Alzheimer’s disease, diabetes, or the like. In some embodiments, the genes may be associated with more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, or 50 pathways. In some embodiments, the genes may be associated with less than or equal to 50, 45, 40, 35, 30, 25, 20, 19, 18, 17, 16, 15, 14, 13,12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 pathways. For example, the genes may comprise one or more genes comprising ABL1, ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, AGT, AGTR1, AKT1, AKT2, AKT3, ALK, APAF1, APC, APC2, APPL1, AR, ARAF, ARHGEF1, ARHGEF11, ARHGEF12, ARNT, ARNT2, AXIN1, AXIN2, BAD, BAK1, BAX, BBC3, BCL2, BCL2L1, BCL2L11, BCR, BDKRB1, BDKRB2, BID, BIRC2, BIRC3, BIRC5, BIRC7, BMP2, BMP4, BRAF, BRCA2, CALM1, CALM2, CALM3, CALML3, CALML4, CALML5, CALML6, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CASP3, CASP7, CASP8, CASP9, CBL, CCDC6, CCNA1, CCNA2, CCND1, CCND2, CCND3, CCNE1, CCNE2, CDC42, CDH1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CEBPA, CHUK, CKS1B, CKS2, COL4A1, COL4A2, COL4A3, COL4A4, COL4A5, COL4A6, CREBBP, CRK, CRKL, CSF1R, CSF2RA, CSF2RB, CSF3R, CTBP1, CTBP2, CTNNA1, CTNNA2, CTNNA3, CTNNB1, CUL1, CUL2, CXCL12, CXCL8, CXCR4, CYCS, DAPK1, DAPK2, DAPK3, DCC, DDB2, DLL1, DLL3, DLL4, DVL1, DVL2, DVL3, E2F1, E2F2, E2F3, EDN1, EDNRA, EDNRB, EGF, EGFR, EGLN1, EGLN2, EGLN3, ELK1, ELOB, ELOC, EML4, EP300, EPAS1, EPO, EPOR, ERBB2, ESRI, ESR2, ETS1, F2, F2R, F2RL3, FADD, FAS, FASLG, FGF1, FGF10, FGF16, FGF17, FGF18, FGF19, FGF2, FGF20, FGF21, FGF22, FGF23, FGF3, FGF4, FGF5, FGF6, FGF7, FGF8, FGF9, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLT3, FLT3LG, FLT4, FN1, FOS, FOXO1, FRAT1, FRAT2, FZD1, FZD10, FZD2, FZD3, FZD4, FZD5, FZD6, FZD7, FZD8, FZD9, GADD45A, GADD45B, WSGR Docket No. 63688-708.601

[0343] GADD45G, GLI1, GLI2, GLI3, GNA11, GNA12, GNA13, GNAI1, GNAI2, GNAI3, GNAQ, GNAS, GNB1, GNB2, GNB3, GNB4, GNB5, GNG10, GNG11, GNG12, GNG13, GNG2, GNG3, GNG4, GNG5, GNG7, GNG8, GNGT1, GNGT2, GRB2, GSK3B, GSTA1, GSTA2, GSTA3, GSTA4, GSTA5, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO1, GSTO2, GSTP1, GSTT1, GSTT2, GSTT2B, HDAC1, HDAC2, HES1, HES5, HEY1, HEY2, HEYL, HGF, HHIP, HIF1A, HM0X1, HRAS, HSP90AA1, HSP90AB1, HSP90B1, IFNA1, IFNA10, IFNA13, IFNA14, IFNA16, IFNA17, IFNA2, IFNA21, IFNA4, IFNA5, IFNA6, IFNA7, IFNA8, IFNAR1, IFNAR2, IFNG, IFNGR1, IFNGR2, IGF1, IGF1R, IGF2, IKBKB, IKBKG, IL12A, IL12B, IL12RB1, IL12RB2, IL13, IL13RA1, IL15, IL15RA, IL2, IL23A, IL23R, IL2RA, IL2RB, IL2RG, IL3, IL3RA, IL4, IL4R, IL5, IL5RA, IL6, IL6R, IL6ST, IL7, IL7R, ITGA2, ITGA2B, ITGA3, ITGA6, ITGAV, ITGB1, JAG1, JAG2, JAK1, JAK2, JAK3, JUN, JUP, KEAP1, KIF7, KIT, KITLG, KLK3, KNG1, KRAS, LAMA1, LAMA2, LAMA3, LAMA4, LAMA5, LAMB1, LAMB2, LAMB3, LAMB4, LAMC1, LAMC2, LAMC3, LEF1, LPAR1, LPAR2, LPAR3, LPAR4, LPAR5, LPAR6, LRP5, LRP6, MAP2K1, MAP2K2, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MAX, MDM2, MECOM, MET, MGST1, MGST2, MGST3, MITF, MLH1, MMP1, MMP2, MMP9, MSH2, MSH3, MSH6, MTOR, MYC, NCOA1, NCOA3, NCOA4, NFE2L2, NFKB1, NFKB2, NFKBIA, NKX3-1, NOS2, NOTCH1, NOTCH2, NOTCH3, NOTCH4, NQO1, NRAS, NTRK1, PAX8, PDGFA, PDGFB, PDGFRA, PDGFRB, PGF, PIK3CA, PIK3CB, PIK3CD, PIK3R1, PIK3R2, PIK3R3, PIM1, PIM2, PLCB1, PLCB2, PLCB3, PLCB4, PLCG1, PLCG2, PLD1, PLD2, PLEKHG5, PMAIP1, PML, POLK, PPARD, PPARG, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB, PRKCG, PTCHI, PTCH2, PTEN, PTGER1, PTGER2, PTGER3, PTGER4, PTGS2, PTK2, RAC1, RAC2, RAC3, RAD51, RAFI, RALA, RALB, RALBP1, RALGDS, RARA, RARB, RASGRP1, RASGRP2, RASGRP3, RASGRP4, RASSF1, RASSF5, RBI, RBX1, RELA, RET, RHOA, ROCK1, ROCK2, RPS6KA5, RPS6KB1, RPS6KB2, RUNX1, RUNX1T1, RXRA, RXRB, RXRG, SHH, SKP1, SKP2, SLC2A1, SMAD2, SMAD3, SMAD4, SMO, SOS1, SOS2, SP1, SPI1, STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, STAT6, STK4, SUFU, TCF7, TCF7L1, TCF7L2, TERC, TERT, TFG, TGFA, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TP53, TPM3, TPR, TRAF1, TRAF2, TRAF3, TRAF4, TRAF5, TRAF6, TXNRD1, TXNRD2, TXNRD3, VEGFA, VEGFB, VEGFC, VEGFD, VHL, WNT1, WNT10A, WNT10B, WNT1 1, WNT16, WNT2, WNT2B, WNT3, WNT3A, WNT4, WNT5A, WNT5B, WNT6, WNT7A, WNT7B, WNT8A, WNT8B, WNT9A, WNT9B, XIAP, ZBTB16, ZBTB17, or a combination thereof.

[0344]

[0273] In some embodiments, the genes may be associated with an organ, a cancer, or both. For example, the genes may be associated with more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, WSGR Docket No. 63688-708.601

[0345] 12, 13, 14, or 15 organs. The genes may be associated with less than or equal to 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 organs. For example, the genes may be associated with more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 cancers. The genes may be associated with less than or equal to 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2 cancers.

[0346]

[0274] In some embodiments, a gene panel that is related to one or more organs, cancers, or both, may be used in the methods and systems disclosed herein. In this example, the gene panels related to one or more organs, cancers, or both, may serve as a holding pen for newly discovered genes relating to an organ, cancer, or both, as well as a confirmatory check on gene panels that are specific to a particular organ, cancer, or both. In some embodiments, the genes in the gene panels related to one or more organs, cancers, or both, may appear in more than one organ, but less than all organs.

[0347]

[0275] In some embodiments, the genes may be associated with a bladder cancer. For example, the genes may comprise one or more genes comprising A2M, A2ML1, AAGAB, AARD, ABAT, ABCA4, ABCA8, ABCA9, ABCB1, ABCB5, ABCC1, ABCC2, ABCC3, ABCC4, ABCC9, ABCD1, ABCD3, ABI3BP, ABL1, ABL2, ABLIM I , ABO, ABRACL, ABT1, ABTB2, AC090945.1, ACACB, AC ADS, ACADVL, ACBD4, ACHE, ACINI, ACKR1, ACOX2, ACOXL, ACP6, ACRBP, ACSF2, ACSL4, ACSS2, ACTA2, ACTC1, ACTG2, ACTN1, ACTN2, ACTN4, ACTR1B, ACTRT3, ACVR1, ACY1, ACYP2, ADAM15, ADAM I 7, ADAM33, ADAM8, ADAM9, ADAMTS1, ADAMTS12, ADAMTS15, ADAMTS4, ADAMTS5, ADAMTS8, ADAMTS9, ADAMTSL3, AD API, ADAR, AD ARBI, ADCY5, ADCY7, ADCY9, ADCYAP1, ADGRA2, ADGRB3, ADGRD1, ADGRG4, ADH1B, ADH1C, ADIPOR2, ADM, ADM5, ADORA2A, ADORA2B, ADRA2A, ADRB3, AEBP2, AES, AFF3, AFP, AFTPH, AGA, AGAP6, AGAP9, AGER, AGRN, AGTR1, AHCY, AHNAK, AHNAK2, A HR, AIFM2, AIFM3, AIM2, AIMP2, AKAP12, AKAP17A, AKAP6, AKAP7, AKNA, AKR1B1, AKR1B15, AKR7A2, AKT1, AKT1S1, AKT3, ALB, ALDH1A1, ALDH1B1, ALDH2, ALDH4A1, ALK, ALKBH1, ALKBH2, ALKBH3, ALKBH5, ALOX12, ALOX15, ALOX15B, ALOX5, ALPG, ALPK1, ALPP, AMBP, AMFR, AMOTL1, AMPD3, ANAPC2, ANAPC4, ANG, ANGEL2, ANGPTL1, ANGPTL2, ANGPTL4, ANGPTL7, ANK2, ANKFY1, ANKMY1, ANKRD10, ANKRD39, ANKRD49, ANKRD52, ANKS1B, ANLN, AN05, AN09, ANPEP, ANTXR2, ANXA1, ANXA11, ANXA2, ANXA2R, ANXA5, ANXA6, AOC2, AOC3, AOX1, AP1AR, AP3D1, AP3M2, AP5Z1, APAF1, APBA3, APBB1, APC, APEX1, APEX2, APH1A, APLN, APLP1, APOA1, APOA2, APOA5, APOBEC3A, APOBEC3B, APOBEC3D, APOBEC3F, APOBEC3G, APOBEC3H, APOCI, APOL1, APOL2, APOL4, APOL6, APOLD1, AQP1, AQP3, AQP9, AR, ARAF, ARAP1, ARGLU1, ARHGAP10, ARHGAP17, ARHGAP20, ARHGAP24, ARHGAP26, ARHGAP27, WSGR Docket No. 63688-708.601

[0348] ARHGAP30, ARHGAP31, ARHGAP35, ARHGAP39, ARHGAP4, ARHGAP45, ARHGAP6, ARHGAP8, ARHGDIB, ARHGEF1, ARHGEF11, ARHGEF18, ARHGEF2, ARHGEF25, ARHGEF26, ARHGEF28, ARHGEF37, ARHGEF39, ARHGEF7, ARHGEF9, ARID1A, ARID3A, ARID5A, ARID5B, ARL14EP, ARL4C, ARL4D, ARL6IP1, ARL6IP4, ARMC9, ARMCX1, ARPC4, ARRDC2, ARSB, ARSI, ARVCF, AS3MT, ASAP1, ASB2, ASB5, ASF1B, ASGR2, ASP A, ASPM, ASXL1, ASXL2, ATAT1, ATF3, ATF7IP2, ATG4B, ATM, ATP13A1, ATP13A3, ATP1A1, ATP1A2, ATP1A4, ATP1B2, ATP2B4, ATP5F1D, ATP6V0A1, ATP6V0B, ATP7B, ATP8B2, ATR, ATRN, ATXN1L, ATXN2L, ATXN7L3, AURKA, AURKB, AURKC, AVIL, AXIN2, AZI2, B3GALT2, B3GNT2, B4GALNT4, B4GALT5, BACE1, BAD, BAG2, BAG6, BAIAP2, BAP1, BARX1, BARX2, BASP1, BATF, BAX, BBC3, BC042052, BCAT1, BCDIN3D, BCHE, BCL1 IB, BCL2, BCL2L1, BCL2L14, BCL2L2, BCL3, BCL6, BCL9L, BCOR, BCR, BCS1L, BDKRB1, BDKRB2, BDNF, BEND5, BGN, BHLHE23, BHLHE41, BHMT2, BID, BINI, BIRC3, BIRC5, BIRC7, BLCAP, BLNK, BLOC1S3, BLTP3A, BMERB1, BMP5, BMPR2, BNC2, BOC, BOK, BPIFB1, BPTF, BRAF, BRCA1, BRCA2, BRI3BP, BRICD5, BRINP1, BRMS1L, BSG, BTG2, BTN2A1, BTN3A1, BUB1, BUB1B, BVES, C11ORF84, C12ORF75, C14ORF159, C15ORF48, C16ORF58, C16ORF89, C17ORF97, C1ORF122, C1ORF131, C1ORF159, C1ORF226, C1QTNF6, C1QTNF7, C1QTNF9, C20ORF187, C20ORF96, C21ORF58, C2CD4B, C3, C3ORF62, C3ORF70, C4A, C4ORF33, C6ORF136, C6ORF15, C6ORF62, C7, C8A, CA2, CA9, CABIN1, CACNA1C, CACNA1H, CACNA2D1, CACNB2, CACNB4, CACNG4, CADM3, CALB1, CALD1, CALHM1, CALM1, CALML5, CALR, CALU, CAMK2A, CANT1, CAP2, CAPN1, CAPN2, CAPNS1, CAPNS2, CAPRIN2, CARD11, CARD8, CARHSP1, CARMI, CASC11, CASC15, CASP14, CASP3, CASP4, CASP6, CASP8, CASP9, CASQ1, CASQ2, CAST, CAV1, CAVIN1, CAVIN2, CBS, CBX1, CBX2, CBX6, CBX7, CC2D2A, CCAR2, CCDC115, CCDC125, CCDC136, CCDC14, CCDC159, CCDC38, CCDC69, CCDC71, CCDC80, CCL14, CCL17, CCL18, CCL19, CCL2, CCL20, CCN1, CCN2, CCN5, CCNA2, CCNB1, CCNB2, CCND1, CCND2, CCNE1, CCNE2, CCNJL, CCNL1, CCNL2, CCNT2, CCRL2, CCT7, CD109, CD200, CD24, CD274, CD2AP, CD300LG, CD302, CD34, CD3D, CD3E, CD4, CD40, CD40LG, CD44, CD47, CD55, CD68, CD82, CD9, CD96, CD99, CD99L2, CDC20, CDC25A, CDC25C, CDC42, CDC42BPA, CDC42BPB, CDC42EP3, CDC42EP5, CDC42SE2, CDC45, CDC6, CDCA2, CDCA3, CDCA4, CDCA5, CDCA7, CDCA8, CDH1, CDH13, CDH17, CDH23, CDH3, CDK1, CDK10, CDK16, CDK18, CDK2, CDK4, CDK5RAP3, CDK6, CDKAL1, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDON, CDSN, CDT1, CDX2, CEACAM1, CEACAM5, CEBPA, CEBPB, CEBPD, CELF2, CELSR3, CEMIP, CENPA, CENPB, CENPE, CENPF, CENPN, CENPU, CEP135, CEP55, CERCAM, CERK, CERS2, WSGR Docket No. 63688-708.601

[0349] CES1, CFAP251, CFD, CFI, CFL2, CGB1, CGB5, CGGBP1, CGNL1, CGREF1, CH25H, CHAF1B, CHCHD1, CHD4, CHD6, CHEK1, CHERP, CHGA, CHI3L1, CHIA, CHIT1, CHMP4B, CHMP4C, CHPF, CHPF2, CHRDL1, CHRDL2, CHRM2, CHRM3, CHST11, CHST4, CHTF18, CHTOP, CIB1, CIC, CILP, CIMAP 1C, CIMAP2, CIP2A, CIR1, CISDI, CISH, CIT, CKAP2L, CKAP4, CKB, CKMT2, CKS2, CLASRP, CLCA4, CLCF1, CLDN15, CLDN3, CLDN5, CLDN6, CLDN9, CLEC10A, CLEC12A, CLEC2D, CLEC3A, CLEC3B, CLHC1, CLIC3, CLIC4, CLIP3, CLIP4, CLK1, CLK2, CLK3, CLPTM1, CLPTM1L, CLPTML, CLSTN3, CLTC, CLU, CLUH, CMA1, CMC1, CMPK1, CMTM5, CMTR1, CNFN, CNGA3, CNKSR1, CNKSR3, CNN1, CNN3, CNNM3, CNOT1, CNOT3, CNOT8, CNOT9, CNRIP1, CNTN1, CNTNAP2, COA5, COA6, COL10A1, COL11A1, COL11A2, COL13A1, COL14A1, COL15A1, COL19A1, COL21A1, COL2A1, COL4A1, COL4A2, COL4A4, COL4A6, COL5A2, COL5A3, COL6A1, COL7A1, COLEC12, COLGALT1, C0MMD7, COMP, COMT, COPZ2, CORO1B, COX19, COX2, COX5B, COX7A1, COX7B, CP A3, CPA4, CPB2, CPE, CPEB1, CPEB2, CPEB4, CPED1, CPLX2, CPNE6, CPNE7, CPQ, CPSF7, CPT1B, CPVL, CPXM2, CRB3, CRCT1, CREB1, CREBBP, CREBRF, CREM, CRH, CRISP3, CRISPLD2, CRLF3, CRLS1, CRNN, CROT, CRP, CRTAC1, CRTC2, CRY2, CRYAB, CRYGS, CRYM, CSAD, CSAG1, CSAG2, CSAG3, CSDC2, CSE1L, CSF2, CSF3, CSGALNACT1, CSK, CSNK1G2, CSNK2A3, CSPG4, CSRNP1, CSRNP2, CSRP1, CST1, CST3, CST4, CST6, CSTA, CTAG1A, CTAG1B, CTB-50L17.10, CTBP1, CTDSP1, CTDSP2, CTNNA1, CTNNA3, CTNNB1, CTNND1, CTPS2, CTSB, CTSE, CTSG, CTSV, CTSZ, CTU1, CUL1, CUL9, CWC27, CXCL10, CXCL11, CXCL12, CXCL13, CXCL2, CXCL3, CXCL5, CXCL8, CXCL9, CXCR2, CXCR4, CXORF38, CXORF49B, CYB5R3, CYBB, CYBRD1, CYFIP1, CYGB, CYP11A1, CYP1A1, CYP1A2, CYP1B1, CYP21A2, CYP2A13, CYP2A6, CYP2D6, CYP2E1, CYP2W1, CYP3A4, CYP4B1, CYP4F12, CYP4F8, CYSRT1, CYTH1, CYTH2, CYTH3, CYTL1, DAAM2, DAB2, DAB2IP, DACT3, DAG1, DAPK1, DAPK2, DAPK3, DAPL1, DAZ1, DAZAP1, DBC1, DBNDD1, DCAF15, DCAF16, DCAF8, DCBLD1, DCC, DCHS1, DCHS2, DCK, DCLK1, DCN, DCTN6, DCUN1D3, DDB1, DDIT3, DDR2, DDX17, DDX39B, DDX42, DECR1, DEDD2, DEGS1, DEGS2, DENND1C, DENND2A, DENND2D, DENND4B, DEPDC1, DEPDC1B, DEPDC5, DES, DFFB, DGCR2, DGKB, DGKG, DGUOK, DHCR24, DHCR7, DHRS2, DHX37, DHX38, DIAPH1, DICER1, DIDOI, DISP1, DIXDC1, DKK1, DLC1, DLG2, DLGAP5, DLK1, DLL1, DLST, DMD, DMGDH, DMPK, DNAJB4, DNAJB5, DNASE1, DNM2, DNMBP, DNMT1, DNMT3A, DNMT3B, DOC2A, DOCK11, DOCK8, DOK5, DOK6, DOK7, DOLK, DOT1L, DPMI, DPM3, DPT, DPYSL2, DPYSL3, DPYSL4, DRAM1, DSC2, DSC3, DSG1, DSG3, DSP, DSTN, DSTYK, DTL, DTNA, DUSP1, DUSP2, DUSP4, DUSP5, DUSP8, DVL3, DYM, WSGR Docket No. 63688-708.601

[0350] DYNC1I1, DYSF, E2F1, E2F2, E2F3, E2F7, EBF1, ECGF1, ECHDC2, ECHDC3, ECM1, ECRG4, ECT2, EDNRA, EDNRB, EED, EEF1A2, EEF1D, EEF1G, EEF2, EFEMP1, EFHD2, EFNA1, EFS, EGF, EGFR, EGR1, EGR2, EGR3, EHBP1, EHBP1L1, EHD1, EHD4, EHMT2, EIF2S1, EIF3A, EIF3B, EIF3C, EIF3G, EIF3J, EIF4E, EIF4EBP1, EIF4G1, EIF4H, EIF5A2, ELANE, ELAVL3, ELF4, ELL, ELM0D3, ELN, EL0VL4, EMC1, EMCN, EME2, EMILIN1, EML1, EML3, EMP1, EMP2, END0D1, ENDOU, ENG, ENGASE, ENO2, ENPEP, ENTREP1, EOMES, EP300, EPB41L4A, EPC AM, EPDR1, EPGN, EPHA2, EPHA3, EPHA7, EPHB1, EPHB2, EPHB4, EPHB6, EPHX1, EPHX2, EPM2A, EPN2, EPS8L3, EPSTI1, ERBB2, ERBB3, ERBB4, ERC1, ERCC1, ERCC2, ERCC4, ERCC5, ERCC6, ERF, ERGIC1, ESMI, ESPL1, ESRI, ESR2, ESRRA, ESYT1, ESYT2, ETF1, ETNK1, ETV4, ETV6, ETV7, EVA1A, EVA1C, EVC, EWSR1, EXO1, EXOCI, EXOC3L4, EXOC7, EXPH5, EZH2, EZR, F10, F13A1, F2, F7, F8, FAAH2, FABP1, FABP2, FABP4, FABP7, FADS1, FADS2, FAIM2, FAM107A, FAM111A, FAM111B, FAM120A, FAM129B, FAM135B, FAM13A, FAM13B, FAM149A, FAM162A, FAM168A, FAM168B, FAM171B, FAM175B, FAM180B, FAM193B, FAM200B, FAM43A, FAM53B, FAM72B, FAM72D, FAM76B, FAM83B, FAM98C, FANCA, FANCC, FANCD2, FANCI, FANCL, FAP, FARSB, FAS, FASLG, FASTKD3, FAT4, FAXDC2, FBLN2, FBLN5, FBN1, FBN2, FBP1, FBRS, FBRSL1, FBXL15, FBXL19, FBXL22, FBXL6, FBXL7, FBXO18, FBXO30, FBXO46, FBXO6, FBXW7, FBXW8, FCER1A, FCGR2A, FCGR2B, FCGR2C, FCGR3A, FCHSD1, FCRLB, FDCSP, FEN1, FERMT1, FERMT2, FGA, FGB, FGD5, FGF10, FGF11, FGF19, FGF2, FGF7, FGF9, FGFBP1, FGFR1, FGFR2, FGFR3, FGFR4, FGL2, FHIT, FHL1, FIGF, FILIP1, FILIP1L, FIRRM, FIZ1, FJX1, FKBP10, FKBP14, FKBP9, FKTN, FLCN, FLII, FLNA, FLNC, FLT1, FMN1, FMNL1, FMOD, FN1, FNBP1, FNBP4, FNDC1, FNDC4, FOLR1, FOS, FOSB, FOSL1, FOSL2, FOXA1, FOXD1, FOXF1, FOXF2, FOXI1, F0XM1, FOXN3, FOXO1, FOXP2, FOXQ1, FRY, FTCD, FUBP3, FUNDCI, FURIN, FUS, FUT4, FXN, FXYD1, FXYD4, FXYD6, FYCO1, FZD7, G2E3, G6PD, GAA, GABI, GABBR2, GABPA, GADD45A, GADD45B, GAGE12J, GAGE2D, GAGE4, GAK, GAL, GALC, GALK1, GALM, GALNT14, GALNT15, GALNT17, GALNT18, GALNT6, GAN, GANAB, GARNL3, GAS6, GAS7, GATA2, GAT A3, GATA5, GATA6, GATAD2A, GBA2, GBF1, GBP2, GBP5, GBP6, GC, GCC2, GCH1, GCLC, GCLM, GCN1, GCNT1, GCNT3, GC0M1, GDF10, GEM, GEMIN7, GEMIN8, GFRA1, GGH, GGN, GHR, GHRH, GINS1, GINS2, GIPC1, GJB1, GJC1, GKN1, GLB1, GLG1, GLI1, GLI2, GLI3, GLIPR1, GLP2R, GLTSCR2, GLUD1, GLYCTK, GMIP, GNA12, GNAL, GNAO1, GNAS, GNAT3, GNAZ, GNB2, GNG11, GNG4, GNG7, GNLY, GOLGA8A, GOLGA8B, GOLT1A, GPAT2, GPBP1, GPC2, GPC6, GPHN, GPI, GPH4BP1, GPM6B, GPR107, GPR160, GPR183, GPR84, GPR87, GPRASP1, GPRASP2, WSGR Docket No. 63688-708.601

[0351] GPRIN1, GPS1, GPX1, GPX5, GRAMD1A, GRB7, GREM2, GRIK2, GRIN2B, GRIN2D, GRINA, GRIP API, GRK2, GRN, GRP, GSAP, GSDMB, GSN, GSTA1, GSTK1, GSTM1, GSTM2, GSTM3, GSTM5, GST01, GSTO2, GSTP1, GSTT1, GSTZ1, GTF2I, GTF2IP4, GTF3C1, GTSE1, GTSF1, GUCA1C, GUCA2A, GULP1, GXYLT1, GXYLT2, GYPC, GYS2, GZMB, Hl-2, H2AC18, H2AC25, H2AX, H2BC12, H2BC21, H2BC5, H4C14, HAAO, HAGH, HAL, HANOI, HAND2, HAS1, HAS3, HAUS3, HAUS4, HAVCR1, HBB, HBEGF, HCFC1, HCN3, HDAC1, HDAC2, HDAC4, HDAC6, HDAC7, HDAC8, HDAC9, HOC, HDGF, HDLBP, HEBP2, HEG1, HELT, HELZ2, HEP AC AM, HEPH, HEPHL1, HERE UD I, HES1, HES2, HES6, HEXB, HEYL, HGFAC, HHIP, HIC2, HID1, HIF1A, HIF3A, HILPDA, HIP1R, HIPK3, HIRA, HJURP, HLA-A, HLA-B, HLA-DMA, HLA-E, HLA-G, HLF, HMCN2, HMG20B, HMGA2, HMGB1, HMGB3, HMGN5, HMMR, HNMT, HNRNPC, HNRNPK, HNRNPL, HNRNPM, HNRNPU, HNRNPUL1, HNRNPUL2-BSCL2, HOTAIR, H0XA9, HOXB3, HOXB5, HOXB7, HP, HPGD, HPGDS, HPR, HPSE2, HPX, HRAS, HRH2, HS3ST1, HS6ST2, HSCB, HSD17B1, HSD17B10, HSD17B2, HSD17B6, HSD3B1, HSH2D, HSPA12A, HSPA1 A, HSPA1B, HSPA2, HSPA4, HSPA4L, HSPA5, HSPA8, HSPB2, HSPB6, HSPB7, HSPB8, HSPG2, HTC2, HTR4, HTR5A, HTRA1, HTT, HUWE1, HYAL3, HYI, HY0U1, IBSP, ICAM1, IDE, IDH1, IDO1, IDUA, IER3, IER5L, IFI27, IFI6, IFIT3, IFNA1, IFNA13, IFNA2, IFNB1, IFNG, IFNL2, IFT140, IFT27, IGF1, IGF1R, IGF2, IGF2BP1, IGF2BP2, IGF2BP3, IGF2R, IGFBP3, IGFBP5, IGFBP7, IGFL1, IGFL2, IGHV1-12, IGKV1D-37, IGSF10, IGSF21, IGSF9, IGSF9B, IKBKB, IL10, IL13, IL1B, IL1RAP, IL1RN, IL2, IL33, IL4, IL4R, IL6, IL6ST, IL8, IL9R, ILF3, ILK, IMPDH1, INA, INCENP, INF2, INHBA, INMT, INPPI, INPP4B, INPPL1, INSIGI, INSYN1, INTS1, IP6K2, IPO4, IPO9, IPPK, IQGAP3, IQSEC2, IRAG1, IRAKI, IRAK2, IRAK4, IRF3, IRF5, IRF9, ISCU, ISG15, ISL1, IST1, ISY1- RAB43, ITGA1, ITGA5, ITGA7, ITGA8, ITGA9, ITGAE, ITGB1BP2, ITGB3, ITGBL1, ITIH1, ITIH5, ITLN1, ITM2A, ITPKB, ITPKC, ITPR1, ITPR3, IVL, JAG1, JAM2, JAM3, JAZF1, JCAD, JCHAIN, JPH2, JRK, JUN, JUNB, KANK1, KANK2, KANSL2, KAT2A, KAT2B, KATNAL1, KCNA5, KCNB1, KCND2, KCND3, KCNE4, KCNG1, KCNH2, KCNH6, KCNJ15, KCNJ8, KCNK17, KCNK3, KCNK5, KCNMA1, KCNMB1, KCNMB2, KCNN3, KCNN4, KDM2A, KDM4E, KDM5C, KDM6A, KDR, KHNYN, KHSRP, KIAA0100, KIAA0408, KIAA0513, KIAA2013, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF1A, KIF20A, KIF23, KIF26B, KIF2C, KIF4A, KIFC1, KIFC2, KIN, KIRREL1, KISSI, KISS1R, KIT, KLC3, KLF13, KLF16, KLF17, KLF2, KLF4, KLF5, KLF6, KLF9, KLHDC4, KLHDC7A, KLHDC7B, KLHL13, KLHL14, KLHL29, KLHL41, KLHL42, KLHL5, KLK11, KLK12, KLK13, KLK2, KLK3, KLK5, KLK6, KLK8, KMT2A, KMT2C, KMT2D, KNTC1, KPNA2, KRAS, KRT13, KRT14, KRT16, KRT19, KRT20, KRT23, KRT31, KRT4, KRT5, WSGR Docket No. 63688-708.601

[0352] KRT6B, KRT7, KRT78, KRT79, KRT81, KRT86, KRTAP5-9, KY, LACTBL1, LAMA2, LAMA4, LAMC1, LAMC2, LAMC3, LAMP1, LARP1, LARP7, LASPI, LAT, LATS2, LBP, LCOR, LDB1, LDB2, LDB3, LDLR, LDLRAD3, LEAP2, LENG8, LEPR, LEPREL1, LETMD1, LGALS1, LGALS3, LGALS4, LGALS7, LGI2, LGI4, LHFPL6, LIF, LIFR, LIG1, LIG3, LIG4, LIMD2, LIME1, LIMS2, LIN28A, LINC00504, LINC02645, LINC02871, LIPG, LIPT1, LL22NC03-75H12.2, LMCD1, LMLN, LMNA, LMNB1, LMNB2, LM03, LM0D1, LM0D3, LOCI 10806263, LOC339593, LONRF2, LOX, LOXL1, LOXL4, LPAR1, LPL, LPP, LRCH2, LRFN5, LRIG1, LRP1, LRP10, LRP2, LRP5, LRP8, LRPAP1, LRRC15, LRRC17, LRRC2, LRRC32, LRRC34, LRRC3B, LRRC59, LRRK2, LRRN4CL, LSM11, LSM7, LSP1, LSS, LTB4R, LTB4R2, LTBP1, LTBP2, LTBP4, LTF, LUC7L3, LUM, LY6E, LY6K, LY75, LYNX1, LYPD6, LYPLAL1, LYRM1, LYVE1, LZTS1, MAB21L4, MAD1L1, MAD2L1, MADD, MAF1, MAFF, MAFG, MAFK, MAG, MAGEA1, MAGEA11, MAGEA2, MAGEA3, MAGEA4, MAGEA6, MAGEA9, MAGEA9B, MAGEB2, MAGECI, MAGEC2, MAGED4, MAGED4B, MAL, MAMDC2, MAML1, MAN2B1, MAOB, MAP1A, MAP1B, MAP1LC3B, MAP IS, MAP2K1, MAP2K2, MAP2K3, MAP2K7, MAP3K1, MAP3K10, MAP3K20, MAP3K3, MAP7D3, MAPK1, MAPK10, MAPK15, MAPK3, MAPK4, MAPK8, MAPK8IP3, MAPKAPK2, MAPRE2, MAPT, MARCKSL1, MARCO, MASP1, MAT1A, MAT2A, MATN2, MAZ, MBL2, MBOAT2, MBOAT7, MCAM, MCC, MCF2L, MCFD2, MCL1, MCM10, MCM2, MCM3AP, MDH2, MDK, MDM2, MDM4, ME3, MECR, MED12, MEDAG, MEF2C, MEIS1, MEIS2, MELK, MELTF, MEOX1, MEOX2, MEST, MET, METAP 1, METRNL, METTL18, METTL24, METTL3, MEX3A, MFAP2, MFAP4, MFAP5, MFSD11, MFSD2A, MFSD8, MGAT1, MGAT4B, MGLL, MGMT, MGP, MIA, MIB1, MICAL1, MICU3, MID1IP1, MID2, MINK1, MIR100, MIR10A, MIR145, MIR205, MIR21, MIR210, MIR29C, MIR33B, MIR34A, MIR34B, MIR3654, MIR4324, MIR532, MIR96, MIR99A, MITD1, MITF, MKI67, MKNK2, MKX, MLEC, MLH1, MLH3, MLLT3, MLLT6, MLPH, MLRL, MLXIP, MMAA, MMD, MME, MMP1, MMP10, MMP11, MMP13, MMP14, MMP15, MMP19, MMP2, MMP23B, MMP27, MMP3, MMP7, MMP9, MMRN1, MMS19, MOGS, MORN5, MPDZ, MPHOSPH8, MPO, MPP2, MPST, MPZ, MRAS, MRC1, MRFAP1L1, MRGPRF, MRPL28, MRPL38, MRPL42, MRPS6, MS4A15, MSANTD2, MSC, MSH2, MSH3, MSH6, MSI1, MSL3, MSLN, MSMB, MSRB3, MST1, MST1R, MT1A, MT1F, MT1H, MT2A, MT3, MTA1, MTA2, MTG1, MTHFD1L, MTHFD2, MTHFR, MTIF3, MTOR, MTR, MTURN, MUC1, MUC16, MUC17, MUC2, MUC21, MUC6, MUCL3, MUSTN1, MUTYH, MVD, MVP, MXI1, MXRA5, MXRA7, MXRA8, MY ADM, MYBBP1A, MYBL2, MYBPH, MYC, MYCN, MYEOV, MYF5, MYH10, MYH11, MYH2, MYH3, MYH7B, MYH9, MYL9, MYLIP, MYLK, MYNN, MYO15B, MYO1C, MYOID, MYO1E, MYO5A, MYO9B, MYOC, WSGR Docket No. 63688-708.601

[0353] MYOCD, MYODI, MYOF, MYOG, ...

Claims

1. WSGR Docket No. 63688-708.601CLAIMSWhat is claimed is:

1. A method of determining a cancer status of a subject, the method comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells or progenitor cells; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or an absence of a cancer in an organ or a tissue.

2. The method of claim 1, wherein the stem cells comprise cancer stem cells, very small embryonic-like stem cells, or pluripotent stem cells.

3. The method of claim 1, wherein the progenitor cells comprise tissue committed progenitor cells.

4. The method of any one of claims 1 to 3, wherein the biological sample comprises a blood sample, a fraction of the blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample.

5. The method of claim 4, wherein the biological sample comprises the blood sample.

6. The method of claim 4, wherein the biological sample comprises the fraction of the blood sample.

7. The method of claim 4, wherein the biological sample comprises the plasma sample.

8. The method of claim 4, wherein the biological sample comprises the serum sample.

9. The method of any one of claims 1 to 8, wherein the subject is suspected of having the cancer.

10. The method of any one of claims 1 to 8, wherein the subject is not suspected of having cancer.

11. The method of any one of claims 1 to 10, wherein the cancer status comprises a presence or an absence of the cancer.

12. The method of any one of claims 1 to 11, wherein the cancer comprises breast cancer, liver cancer, ovarian cancer, lung cancer, leukemia, lymphoma, renal cancer, bladderWSGR Docket No. 63688-708.601 cancer, brain cancer, head and neck cancer, prostate cancer, pancreatic cancer, cervical cancer, colon cancer, testicular cancer, thyroid cancer, bile duct cancer, or esophageal cancer.

13. The method of any one of claims 1 to 12, wherein the cancer comprises stage 0 cancer, stage I cancer, stage II cancer, stage III cancer, or stage IV cancer.

14. The method of any one of claims 1 to 13, wherein the extracted nucleic acids comprise deoxyribonucleic acid (DNA).

15. The method of any one of claims 1 to 14, wherein the extracted nucleic acids comprise ribonucleic acid (RNA).

16. The method of claim 15, wherein the RNA comprises messenger RNA (mRNA), transfer RNA (tRNA), or ribosomal RNA (rRNA).

17. The method of any one of claims 1 to 16, wherein the enriching the population of cells comprises performing a cell sorting assay.

18. The method of claim 17, wherein the cell sorting assay divides the population of cells into one or more subpopulations.

19. The method of claim 18, wherein the one or more subpopulations of cells comprise cancer stem cells, very small embryonic-like stem cells, pluripotent stem cells, or tissue committed progenitor cells.

20. The method of any one of claims 17 to 19, wherein the cell sorting assay comprises flow cytometry, density gradient centrifugation, magnetic activated cell sorting (MACs), molecular coated beads, cell separation technology, single cell RNA sequencing, a cell culturing assay, a cell plasmid assay, or a combination thereof.

21. The method of any one of claims 1 to 20, wherein the assaying the extracted nucleic acids comprises sequencing the extracted nucleic acids.

22. The method of claim 21, wherein the sequencing comprises next generation sequencing (NGS).

23. The method of claim 21, wherein the sequencing comprises whole transcriptome sequencing, whole genome sequencing, or whole exome sequencing.

24. The method of claim 21, wherein the sequencing comprises pyrosequencing, RNA sequencing, sequencing by synthesis (SBS), or nanopore sequencing.

25. The method of any one of claims 1 to 24, wherein the transcriptomic profile of the subject comprises one or more cancer-associated genes.

26. The method of any one of claims 1 to 24, wherein the genomic profile of the subject comprises one or more cancer-associated genes.WSGR Docket No. 63688-708.60127. The method of any one of claims 1 to 24, wherein the exomic profile of the subject comprises one or more cancer-associated genes.

28. The method of any one of claims 1 to 27, wherein the computer processing further comprises determining a transcriptome assessment score from the transcriptomic profile of the subject, wherein the determining the transcriptome assessment score comprises:(i) identifying at least one control sample from at least one control subject; and(ii) determining one or more differentially expressed genes (DEGs) relative to the at least one control sample.

29. The method of claim 28, wherein the identifying at least one control sample is based at least in part on an age of the at least one control subject, a gender of the at least one control subject, a total million reads (TMR) of the at least one control sample, a RNA Integrity Number (RIN) of the at least one control sample, an absence of comorbidities or diseases in the at least one control subject, or a combination thereof.

30. The method of claim 29, wherein the age of the at least one control subject is within 10 years of an age of the subject.

31. The method of claim 29 or 30, wherein the gender of the at least one control subject is the same as a gender of the subject.

32. The method of any one of claims 29 to 31, wherein the TMR of the at least one control sample is within 10 million reads of a TMR obtained from the biological sample.

33. The method of any one of claims 29 to 32, wherein the RIN of the at least one control sample is at least 7.

34. The method of any one of claims 28 to 33, wherein the one or more DEGs comprises one or more genes in one or more pathways in cancer or one or more cancer gene panels.

35. The method of claim 34, wherein the one or more pathways in cancer comprises component pathways comprising p53 signaling pathway, Ras signaling pathway, Calcium signaling pathway, cAMP signaling pathway, Hippo signaling pathway, JAK- STAT signaling pathway, MAPK signaling pathway, mTOR signaling pathway, Notch signaling pathway, PI3K-Akt signaling pathway, TGF-beta signaling pathway, VEGF signaling pathway, Wnt signaling pathway, or a combination thereof.

36. The method of claim 34 or 35, wherein the one or more cancer gene panels comprises at least one biomarker comprising metabolic markers, inflammatory markers, metastatic markers, DNA repair genes, proto oncogenes, frequently mutated genes, cancer stem cell markers, epigenetic regulator genes, cell cycle genes, immune regulators, cancerWSGR Docket No. 63688-708.601 diagnostic markers, tumor suppressor genes, immune checkpoints, or a combination thereof.

37. The method of any one of claims 28 to 36, wherein the determining the transcriptome assessment score comprises assigning a risk threshold to a DEG of the one or more DEGs.

38. The method of any one of claims 28 to 37, wherein the determining the transcriptome assessment score further comprises assigning a pathway in cancer risk category to a cancer pathway of one or more cancer pathways, based at least in part on the risk threshold of the DEG in the one or more cancer pathways; assigning a PIC component pathway risk category based at least in part on the risk threshold of the DEG, wherein the one or more DEGs is in the one or more PIC component pathways; and assigning a cancer gene panel risk category to a cancer gene panel of the one or more cancer gene panels, based at least in part on the risk threshold of the DEG in the one or more cancer gene panels.

39. The method of claim 37 or Error! Reference source not found., wherein the risk category is selected from the group consisting of a high risk, a moderate risk, a low risk, and a negligible risk.

40. The method of any one of claims 37 to 39, wherein the determining the transcriptome assessment score further comprises (I) determining a pathway in cancer risk score based at least in part on the risk category of the one or more cancer pathways, (II) determining a PIC component pathway risk category based at least in part on the risk category of the one or more PIC component pathways, and (III) determining a cancer gene panel risk score based at least in part on the risk category of the one or more cancer gene panels, or a combination of (I), (II), and (III).

41. The method of claim 40, wherein the determining the pathway in cancer risk score comprises determining a weighted sum of each risk category of the one or more pathways in cancer, determining the component pathway risk score comprises determining a weighted sum of each risk category of the one or more PIC component pathways, and wherein determining the cancer gene panel risk score comprises determining a weighted sum of the one or more cancer gene panels.

42. The method of claim 41, wherein the determining the transcriptome assessment score comprises determining a weighted sum of the pathway in cancer risk score, component pathway risk score, and the cancer gene panel risk score.

43. The method of any one of claims 28 to 42, wherein the determining the transcriptome assessment score comprises using of a machine learning model to obtain a wholeWSGR Docket No. 63688-708.601 transcriptome score, wherein the whole transcriptome score is based at least in part on Fragments Per Kilobase of transcript per Million mapped reads (FPKM) from the transcriptomic profile of the subject.

44. The method of claim 43, wherein the machine learning model comprises a trained machine learning algorithm.

45. The method of claim 44, wherein the trained machine learning algorithm is selected from the group consisting of K-Neighbors Classifier, NuSVC, Multi-Layer Perceptron (MLP) Classifier, Decision Tree Classifier, Random Forest Classifier, Logistic Regression, Gaussian Naive Bayes (NB) Classifier, Linear Discriminant Analysis, Quadratic Discriminant Analysis, and Support Vector Classifier (SVC).

46. The method of any one of claims 43 to 45, wherein the whole transcriptome score is based at least in part on a set of gene expression levels comprising all genes detected, a second set of gene expression levels comprising cancer pathway genes, and a third set of gene expression levels comprising signaling pathway genes.

47. The method of any one of claims 43 to 46, wherein the whole transcriptome score is based on determining a classification of the subject by the machine learning model, wherein the classification is selected from the group consisting of: a control, a control indeterminant, a cancer survivor, a cancer subject on treatment, a cancer subject that is treatment naive, and cancer treatment naive indeterminant.

48. The method of claim 47, wherein the classification of control indicates that the subject never had the cancer.

49. The method of claim 47 or 48, wherein the classification of control indeterminate indicates that the subject does not have the cancer but comprises some other pathology that is not the cancer.

50. The method of any one of claims 47 to 49, wherein the classification of the cancer survivor indicates that the subject had the cancer and completed a cancer treatment more than 6 months prior and is PET negative.

51. The method of any one of claims 47 to 50, wherein the classification of the cancer subject on treatment indicates that the subject is or within 6 months since undergoing a cancer treatment.

52. The method of any one of claims 47 to 51, wherein the classification of the cancer treatment naive indicates that the subject is cancer treatment naive.

53. The method of any one of claims 47 to 52, wherein the classification of the cancer treatment naive indeterminant indicates that the subject has the cancer and is cancer treatment naive.WSGR Docket No. 63688-708.60154. The method of any one of claims 1 to 53, wherein the computer processing comprises determining an exome assessment score from the exomic profile of the subject, wherein the determining the exome assessment score comprises: extracting at least one feature from the exomic profile of the subject; and applying at least one trained machine learning algorithm to the at least one feature to classify the subject into a category of one or more categories.

55. The method of claim 54, wherein the at least one feature comprises a count of A, T, G, C, AT, and GC; a count of guanine rich DNA fragments; a count of insertion and deletions; a count of single base substitutions; a count of double base substitutions; or a combination thereof.

56. The method of claim 54 or 55, wherein the one or more categories comprises a control, a control indeterminant, a cancer survivor, a cancer subject on treatment, a cancer treatment naive, or a cancer treatment naive indeterminant.

57. The method of any one of claims 54 to 56, wherein the at least one trained machine learning algorithm is selected from the group consisting of K-Neighbors Classifier, NuSVC, Multi-Layer Perceptron (MLP) Classifier, Decision Tree Classifier, Random Forest Classifier, Logistic Regression, Gaussian Naive Bayes (NB) Classifier, Linear Discriminant Analysis, Quadratic Discriminant Analysis, and Support Vector Classifier (SVC).

58. The method of any one of claims 54 to 57, wherein the applying the at least one trained machine learning algorithm further comprises scaling a prediction value of the category based on a range of prediction values for the one or more categories.

59. The method of any one of claims 1 to 58, wherein the computer processing comprises analyzing at least one somatic mutation from the exomic profile of the subject.

60. The method of claim 59, wherein the analyzing the at least one somatic mutation comprises identifying a somatic mutation having a variant allele frequency of less than 0.1%.

61. The method of claim 59 or 60, wherein the analyzing the at least one somatic mutation comprises identifying a somatic mutation associated with the cancer.

62. The method of any one of claims 1 to 61, wherein the computer processing comprises analyzing at least one germline mutation from the exomic profile of the subject.

63. The method of claim 62, wherein the analyzing the at least one germline mutation comprises identifying a germline mutation having a variant allele frequency of at leastWSGR Docket No. 63688-708.60164. The method of claim 62 or 63, wherein the analyzing the at least one germline mutation comprises identifying a germline mutation associated with the cancer.

65. The method of any one of claims 1 to 64, further comprising determining an organ or a tissue impacted by the cancer.

66. The method of claim 65, wherein the organ or the tissue impacted by the cancer comprises one or more tumors.

67. The method of claim 65, wherein the organ or the tissue impacted by the cancer does not comprise a tumor.

68. The method of claim 67, wherein the tumor is a malignant tumor or a benign tumor.

69. The method of any one of claims 65 to 68, wherein the tissue impacted by the cancer comprises one or more tissues impacted by the cancer.

70. The method of any one of claims 65 to 69, wherein the organ or the tissue impacted by the cancer comprises an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, a bone marrow, testis, a liver, a kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, or a lymphoid organ.

71. The method of any one of claims 1 to 70, wherein the cancer status comprises a cancer remission status.

72. The method of any one of claims 1 to 70, wherein the cancer status comprises a cancer recurrence status.

73. The method of any one of claims 1 to 70, wherein the cancer status comprises a risk of the subject having the cancer.

74. The method of claim 73, further comprising determining the risk of the subject having the cancer with an accuracy of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more.

75. The method of claim 73, further comprising determining the risk of the subject having the cancer with a sensitivity of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more.

76. The method of claim 73, further comprising identifying the subject as having an elevated risk of having the cancer.

77. The method of claim 73, further comprising identifying the subject as not having an elevated risk of having the cancer.WSGR Docket No. 63688-708.60178. The method of any one of claims 1 to 77, further comprising, responsive to the cancer status determined in f), administering a treatment to the subject, thereby treating the cancer.

79. The method of any one of claims 1 to 78, further comprising, responsive to an organ or a tissue health of the organs or tissues, as determined as part of the cancer status determined in f), administering a treatment to the subject, thereby treating the cancer.

80. The method of claim 78 or 79, wherein the treatment comprises surgical resection, chemotherapy, targeted therapy, systemic therapy, radiation therapy, immunotherapy, or a combination thereof.

81. The method of any one of claims 11 to 80, wherein the cancer status comprises the absence of the cancer.

82. The method of claim 81, wherein the absence of the cancer is determined at least in part by a presence of one or more non-cancerous conditions.

83. The method of claim 82, wherein the one or more non-cancerous conditions comprise a liver condition, a brain condition, a breast condition, a lung condition, a prostate condition, a bladder condition, a kidney condition, a bone condition, a pancreas condition, a stomach condition, a skin condition, an ovary condition, or a colon condition.

84. The method of claim 82 or 83, further comprising, responsive to the absence of the cancer, modifying a treatment to the subject.

85. The method of claim 84, wherein the modifying the treatment comprises modifying a treatment dose of the treatment.

86. A method of determining a health status of an organ or a tissue of a subject, the method comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells or progenitor cells; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the health status of the organ or the tissue of the subject.WSGR Docket No. 63688-708.60187. The method of claim 86, wherein the computer processing further comprises:(i) identifying at least one control sample from at least one control subject; and(ii) determining one or more differentially expressed genes (DEGs) relative to the at least one control sample.

88. The method of claim 87, wherein the identifying the at least one control sample is based at least in part an age of the at least one control subject, a gender of the at least one control subject, a total million reads (TMR) of the at least one control sample, a RNA Integrity Number (RIN) of the at least one control sample, an absence of comorbidities or diseases in the at least one control subject, or a combination thereof.

89. The method of claim 88, wherein the age of the at least one control subject is within 10 years of an age of the subject.

90. The method of claim 88 or 89, wherein the gender of the at least one control subject is the same as a gender of the subject.

91. The method of any one of claims 88 to 90, wherein the TMR of the at least one control sample is within 10 million reads of a TMR obtained from the biological sample.

92. The method of any one of claims 88 to 91, wherein the RIN of the at least one control sample is at least 7.

93. The method of any one of claim 87 to 92, wherein the computer processing comprises analyzing the one or more DEGs, wherein the one or more DEGs is in one or more gene panels for dysregulation of cell function.

94. The method of claim 93, wherein the one or more gene panels comprises a gene panel for epigenetic dysregulation, a gene panel for genetic dysregulation, a gene panel for pathway dysregulation, a gene panel for disease-based dysregulation, or a combination thereof.

95. The method of claim 94, wherein the gene panel for disease-based dysregulation comprises genes associated with diabetes, endometriosis, neurodegeneration, Alzheimer’s disease, lung disease, hepatitis, or psoriasis.

96. The method of any one of claims 93 to 95, wherein the computer processing comprises assigning a risk category to each gene panel of the one or more gene panels.

97. The method of claim 96, wherein the computer processing comprises determining an adverse dysregulation of an organ or disease pathway based at least in part on the risk category of each gene panel.

98. The method of any one of claims 93 to 97, wherein the computer processing comprises determining one or more adversely dysregulated genes in the one or more gene panels.WSGR Docket No. 63688-708.60199. The method of claim 98, wherein the determining the one or more adversely dysregulated genes in the one or more gene panels comprises assigning one or more risk thresholds to the one or more adversely dysregulated genes.

100. The method of claim 99, wherein the computer processing comprises determining an adverse dysregulation of an organ or disease pathway based at least in part on the one or more risk thresholds.

101. The method of claim 99 or 100, wherein the determining the health status of the organ or the tissue of the subject is based at least in part on the determining the adverse dysregulation.

102. The method of any one of claims 86 to 101, wherein the determining in f) comprises detecting a presence or an absence of a non-cancerous condition.

103. The method of claim 102, wherein the non-cancerous condition comprises a liver condition, a brain condition, a breast condition, a lung condition, a prostate condition, a bladder condition, a kidney condition, a bone condition, a pancreas condition, a stomach condition, a skin condition, an ovary condition or a colon condition.

104. The method of any one of claims 86 to 103, wherein the determining in f) comprises detecting an absence of a cancer in the organ or the tissue of the subject.

105. A method of determining an effect of a therapeutic on a subject, the method comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point; b) enriching a first population of cells in the first biological sample, wherein the first population of cells comprises stem cells or progenitor cells; c) extracting first nucleic acids from the enriched first population of cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject or a first exomic profile of the subject; e) administering the therapeutic to the subject; f) obtaining a second biological sample obtained or derived from the subject at a second time point subsequent to the administering; g) enriching a second population of cells in the second biological sample, wherein the second population of cells comprises stem cells or progenitor cells; h) extracting second nucleic acids from the enriched second population of cells;WSGR Docket No. 63688-708.601 i) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; j) computer processing (1) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject, and (2) the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject; and k) determining, based at least in part on the computer processing, the effect of the therapeutic on the subject.

106. The method of claim 105, wherein determining the effect of the therapeutic on the subject comprises determining a cancer status of the subject or a health condition of the subject.

107. The method of claim 105, wherein the stem cells comprise cancer stem cells, very small embryonic-like stem cells, or pluripotent stem cells.

108. The method of claim 107, wherein the progenitor cells comprise tissue committed progenitor cells.

109. The method of any one of claims 105 to 108, wherein the enriching the first population of cells and the second population of cells comprises performing a cell sorting assay.

110. The method of claim 109, wherein the cell sorting assay divides the population of cells into one or more subpopulations of cells.

111. The method of claim 110, wherein the one or more subpopulations of cells comprise cancer stem cells, very small embryonic-like stem cells, pluripotent stem cells, or tissue committed progenitor cells.

112. The method of claim 109, wherein the cell sorting assay comprises flow cytometry, density gradient centrifugation, magnetic activated cell sorting (MACs), use of molecular coated beads, cell separation technology, single cell RNA sequencing, a cell culturing assay, or a cell plasmid assay.

113. A method of assessing an effect of a therapeutic, the method comprising: a) assaying a first expression profile of a first biological sample obtained or derived from a subject at a first time point to thereby produce a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; b) administering the therapeutic to the subject;WSGR Docket No. 63688-708.601 c) assaying a second expression profile of a second biological sample obtained or derived from the subject at a second time point subsequent to the administering the therapeutic of b) to thereby produce a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; d) comparing, using at least a computer, the first and second transcriptomic profiles of the subject, genomic profiles of the subject, or exomic profiles of the subject; and e) assessing the effect of the therapeutic based at least in part of the comparing.

114. The method of claim 113, wherein the therapeutic comprises a treatment for a cancer.

115. The method of claim 113, wherein the therapeutic comprises a treatment for a health condition.

116. The method of any one of claims 113 to 115, wherein the biological sample comprises a blood sample, a fraction of the blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample.

117. The method of claim 116, wherein the biological sample comprises the blood sample.

118. The method of claim 116, wherein the biological sample comprises the fraction of the blood sample.

119. The method of claim 116, wherein the biological sample comprises the plasma sample.

120. The method of claim 116, wherein the biological sample comprises the serum sample.

121. The method of claim 113, wherein the subject is suspected of having a cancer.

122. The method of claim 121, wherein the cancer comprises breast cancer, liver cancer, ovarian cancer, lung cancer, renal cancer, leukemia, lymphoma, bladder cancer, prostate cancer, pancreatic cancer, cervical cancer, color cancer, testicular cancer, thyroid cancer, bile duct cancer, or esophageal cancer.

123. The method of claim 121 or 122, wherein the cancer comprises stage 0 cancer, stage I cancer, stage II cancer, stage III cancer, or stage IV cancer.

124. A method of determining a cancer status of a subject, the method comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample;WSGR Docket No. 63688-708.601 c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; j) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; k) enriching a third population of stem cells or progenitor cells in the third biological sample; l) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; m) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; n) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject; and o) determining, based at least in part on the computer processing, the cancer status of the subject.WSGR Docket No. 63688-708.601125. The method of claim 124, wherein the second time point is at least 15 days subsequent to the first time point.

126. The method of claim 124, wherein the second time point is less than 4 months subsequent to the first time point.

127. The method of claim 124, wherein the third time point is at least 15 days subsequent to the second time point.

128. The method of claim 124, wherein the third time point is less than 4 months subsequent to the second time point.

129. The method of any one of claims 124 to 128, wherein the subject is a cancer survivor.

130. A method of determining a cancer status of a subject, the method comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; j) enriching a third population of stem cells or progenitor cells in the third biological sample; k) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells;WSGR Docket No. 63688-708.601 l) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; m) averaging (i) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, (ii) the second genomic profile of the subject, or the second exomic profile of the subject and (iii) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; n) obtaining a fourth biological sample obtained or derived from the subject at a fourth time point that is subsequent to the first, second, and third time points; o) enriching a fourth population of stem cells or progenitor cells in the fourth biological sample; p) extracting fourth nucleic acids from the enriched fourth population of stem cells or progenitor cells; q) assaying the extracted third nucleic acids to generate at least one of a fourth transcriptomic profile of the subject, a fourth genomic profile of the subject, or a fourth exomic profile of the subject; r) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the fourth transcriptomic profile of the subject, the fourth genomic profile of the subject, or the fourth exomic profile of the subject; and s) determining, based at least in part on the computer processing, the cancer status of the subject.

131. The method of claim 130, wherein the subject is a cancer survivor.

132. A composition comprising: the therapeutic of any one of claims 105 to 123.

133. A kit comprising: (a) the composition of claim 132; and (b) instructions for use of the composition according to any one of methods 1 to 104.

134. A non-transitory computer-readable memory storing one or more instructions executable by one or more processors, that when executed by the one or more processors cause the one or more processors to perform processing comprising: a) obtaining a biological sample obtained or derived from the subject;WSGR Docket No. 63688-708.601 b) enriching a population of stem cells or progenitor cells in the biological sample; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or absence of cancer in an organ or a tissue.

135. A computer system for determining a cancer status of a subject, the system comprising: a) a non-transitory memory; and b) a processor in communication with the non-transitory memory, the processor configured to execute the following operations in order to effectuate a method comprising the operations of: i. obtaining a biological sample obtained or derived from the subject; ii. enriching a population of stem cells or progenitor cells in the biological sample; iii. extracting nucleic acids from the enriched population of stem cells or progenitor cells; iv. assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; v. computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and vi. determining, based at least in part on the computer processing, the cancer status of the subject, wherein the cancer status comprises a presence or absence of cancer in an organ or a tissue.

136. A non-transitory computer-readable memory storing one or more instructions executable by one or more processors, that when executed by the one or more processors cause the one or more processors to perform processing comprising: a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status;WSGR Docket No. 63688-708.601 b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, or a baseline exomic profile; j) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; k) enriching a third population of stem cells or progenitor cells in the third biological sample; l) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; m) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; n) computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject; andWSGR Docket No. 63688-708.601 o) determining, based at least in part on the computer processing, the cancer status of the subject.

137. A computer system for determining a cancer status of a subject, the system comprising: a) a non-transitory memory; and b) a processor in communication with the non-transitory memory, the processor configured to execute the following operations in order to effectuate a method comprising the operations of: i. obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a cancer negative status; ii. enriching a first population of stem cells or progenitor cells in the first biological sample; iii. extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; iv. assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile, a first genomic profile, or a first exomic profile of the subject; v. obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; vi. enriching a second population of stem cells or progenitor cells in the second biological sample; vii. extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; viii. assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile, a second genomic profile, or a second exomic profile of the subject; ix. averaging the at least one of the first transcriptomic profile, the first genomic profile, or the first exomic profile of the subject with the at least one of the second transcriptomic profile, the second genomic profile, or the second exomic profile of the subject to obtain at least one of a baseline transcriptomic profile, a baseline genomic profile, or a baseline exomic profile; x. obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points;WSGR Docket No. 63688-708.601 xi. enriching a third population of stem cells or progenitor cells in the third biological sample; xii. extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; xiii. assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile, a third genomic profile, or a third exomic profile of the subject; xiv. computer processing (1) the at least one of the baseline transcriptomic profile, the baseline genomic profile, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile, the third genomic profile, or the third exomic profile of the subject; and xv. determining, based at least in part on the computer processing, the cancer status of the subject.

138. A method of determining a health condition of a subject, the method comprising: a) obtaining a biological sample obtained or derived from the subject; b) enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells or progenitor cells; c) extracting nucleic acids from the enriched population of cells; d) assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, or an exomic profile of the subject; e) computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, or the exomic profile of the subject; and f) determining, based at least in part on the computer processing, the health condition of the subject, wherein the health condition comprises a presence or an absence of an organ or a tissue impacted by the health condition.

139. The method of claim 138, wherein the stem cells comprise very small embryonic- like stem cells, or pluripotent stem cells.

140. The method of claim 138, wherein the progenitor cells comprise tissue committed progenitor cells.

141. The method of any one of claims 138 to 140, wherein the biological sample comprises a blood sample, a fraction of the blood sample, a plasma sample, a serum sample, a urine sample, or a saliva sample.

142. The method of claim 141, wherein the biological sample comprises the blood sample.WSGR Docket No. 63688-708.601143. The method of claim 141, wherein the biological sample comprises the fraction of the blood sample.

144. The method of claim 141, wherein the biological sample comprises the plasma sample.

145. The method of claim 141, wherein the biological sample comprises the serum sample.

146. The method of any one of claims 138 to 145, wherein the subject is suspected of having the health condition.

147. The method of any one of claims 138 to 145, wherein the subject is not suspected of having the health condition.

148. The method of any one of claims 138 to 147, wherein the health condition comprises a presence or an absence of the health condition.

149. The method of any one of claims 138 to 148, wherein the health condition comprises a cardiac health condition, a neurodevelopmental disease, diabetes, or endometriosis.

150. The method of claim 149, wherein the health condition comprises the cardiac health condition.

151. The method of claim 149, wherein the health condition comprises the neurodevelopmental disease.

152. The method of claim 149, wherein the health condition comprises the diabetes.

153. The method of claim 149, wherein the health condition comprises the endometriosis.

154. The method of any one of claims 138 to 153, wherein the health condition comprises a pancreatic health condition, a lung health condition, an upper respiratory tract health condition, a bone health condition, a bone marrow health condition, a testicular health condition, a liver health condition, a renal health condition, a skin health condition, an ovarian health condition, a breast health condition, a urinary bladder health condition, a gastrointestinal health condition, a small intestine health condition, an esophageal health condition, a salivary gland health condition, a stomach health condition, a brain health condition, a neurodegenerative health condition, a prostate health condition, a lymphatic system health condition, an adrenal gland health condition, a parathyroid health condition, a pituitary health condition, an eye health condition, a endometrial health condition, a gall bladder health condition, a tongue health condition, a thyroid health condition, a hair health condition, a nail health condition, a lipid-related health condition, an auto-immune health condition, a cardiac health condition, a bloodWSGR Docket No. 63688-708.601 health condition, a colon health condition, a bowel health condition, a uterus health condition, a biliary tract health condition, a central nervous system (CNS) health condition, a spinal cord health condition, a larynx health condition, a gastroesophageal health condition, a peripheral nervous system (PNS) health condition, a tooth health condition, a cartilage health condition, a reproductive system health condition, a duodenum health condition, a nasopharynx health condition, an appendix health condition, a cervical health condition, a lymph node health condition, a neuromuscular system health condition, a thymus health condition, an immunity health condition, a penile health condition, an adrenal cortex health condition, a fallopian tube health condition, a uveal health condition, a ciliary body health condition, a sweat gland health condition, a placenta health condition, a sebaceous gland health condition, a nasal health condition, a gonad health condition, an endocrine health condition, or an ear health condition.

155. The method of any one of claims 138 to 154, wherein the extracted nucleic acids comprise deoxyribonucleic acid (DNA).

156. The method of any one of claims 138 to 154, wherein the extracted nucleic acids comprise ribonucleic acid (RNA).

157. The method of any one of claims 138 to 154, further comprising enriching the population of cells.

158. The method of claim 157, wherein enriching the population of cells comprises performing a cell sorting assay.

159. The method of claim 158, wherein the cell sorting assay divides the population of cells into one or more subpopulations.

160. The method of claim 159, wherein the one or more subpopulations of cells comprise very small embryonic-like stem cells, pluripotent stem cells, or tissue committed progenitor cells.

161. The method of any one of claims 158 to 160, wherein the cell sorting assay comprises flow cytometry, density gradient centrifugation, magnetic activated cell sorting (MACs), molecular coated beads, cell separation technology, single cell RNA sequencing, a cell culturing assay, a cell plasmid assay, or a combination thereof.

162. The method of any one of claims 138 to 161, wherein assaying the extracted nucleic acids comprises sequencing the extracted nucleic acids.

163. The method of claim 162, wherein the sequencing comprises next generation sequencing (NGS).WSGR Docket No. 63688-708.601164. The method of claim 162, wherein the sequencing comprises whole transcriptome sequencing, whole genome sequencing, or whole exome sequencing.

165. The method of claim 162, wherein the sequencing comprises pyrosequencing, RNA sequencing, sequencing by synthesis (SBS), or nanopore sequencing.

166. The method of any one of claims 138 to 165, wherein the transcriptomic profile of the subject comprises one or more genes associated with the health condition.

167. The method of any one of claims 138 to 165, wherein the genomic profile of the subject comprises one or more genes associated with the health condition.

168. The method of any one of claims 138 to 165, wherein the exomic profile of the subject comprises one or more genes associated with the health condition.

169. The method of any one of claims 138 to 168, wherein the computer processing comprises comparing the transcriptomic profile of the subject to a reference transcriptomic control.

170. The method of any one of claims 138 to 168, wherein the computer processing comprises comparing the genomic profile of the subject to a reference genomic control.

171. The method of any one of claims 138 to 168, wherein the computer processing comprises comparing the exomic profile of the subject to a reference exomic control.

172. The method of any one of claims 138 to 171, wherein the computer processing comprises analyzing one or more pathways.

173. The method of claim 172, wherein the one or more pathways comprise p53 signaling pathway, Ras signaling pathway, Calcium signaling pathway, cAMP signaling pathway, Hippo signaling pathway, JAK-STAT signaling pathway, MAPK signaling pathway, mTOR signaling pathway, Notch signaling pathway, PI3K-Akt signaling pathway, TGF-beta signaling pathway, VEGF signaling pathway, Wnt signaling pathway, or a combination thereof.

174. The method of claim 173, wherein the one or more pathways comprise health condition-associated pathways.

175. The method of claim 174, wherein the one or more health-condition associated pathways comprises a urea pathway, a cytochrome p450 drug metabolism pathway, a surfactant pathway, a proteoglycan pathways, a collagen synthesis pathway, a keratan sulfate pathway, a uric acid synthesis pathway, a glycan biosynthesis pathway, an insulin pathway, a glucagon synthesis pathway, an insulin resistance pathway, a hemoglobin pathway, a ceramide pathway, a phosphatidylcholine pathway, a myelin synthesis pathway, a melanin synthesis pathway, a dermatan sulfate pathway, an androgen biosynthesis pathway, a progesterone synthesis pathway, an estrogen synthesis pathway,WSGR Docket No. 63688-708.601 a testosterone metabolism pathway, a thyroid hormone synthesis pathway, a fatty acid metabolism pathway, an adrenaline pathway, a cortisol synthesis pathway, a hyaluronan synthesis pathway, a chondroitin sulfate metabolism pathway, or a creatinine pathway, or a combination thereof.

176. The method of any one of claims 173 to 175, further comprising determining one or more upregulated genes and one or more downregulated genes in the one or more pathways.

177. The method of claim 176, wherein the one or more upregulated genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes.

178. The method of claim 176, wherein the one or more downregulated genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes.

179. The method of claim 176, further comprising comparing the one or more upregulated genes and the one or more downregulated genes to a reference biological sample obtained or derived from a subject known not to have the health condition.

180. The method of any one of claims 174 to 179, further comprising determining one or more adverse genes and one or more non-adverse genes in the one or more pathways.

181. The method of claim 180, wherein the one or more adverse genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, aboutWSGR Docket No. 63688-708.6013,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes.

182. The method of claim 180, wherein the one or more non-adverse genes comprise about 10 genes, about 20 genes, about 30 genes, about 40 genes, about 50 genes, about 60 genes, about 70 genes, about 80 genes, about 90 genes, about 100 genes, about 150 genes, about 200 genes, about 250 genes, about 300 genes, about 350 genes, about 400 genes, about 450 genes, about 500 genes, about 1,000 genes, about 2,000 genes, about 3,000 genes, about 4,000 genes, about 5,000 genes, about 6,000 genes, about 7,000 genes, about 8,000 genes, about 9,000 genes, about 10,000 genes, about 15,000 genes, about 20,000 genes, about 25,000 genes, about 50,000 genes, about 75,000 genes, or about 100,000 genes.

183. The method of claim 180, further comprising comparing the one or more adverse genes and the one or more non-adverse genes to a reference biological sample obtained or derived from a subject known not to have the health condition.

184. The method of any one of claims 138 to 183, wherein the computer processing comprises use of a machine learning model.

185. The method of claim 184, wherein the machine learning model comprises use of a trained machine learning algorithm.

186. The method of claim 138, wherein the organ or the tissue impacted by the health condition comprises an adrenal gland, a parathyroid gland, an eye, an endometrium, a gall bladder, a bone, a pancreas, lungs, a bone marrow, testis, a liver, a kidney, skin, an ovary, a thyroid, a colon / rectum, a breast, a urinary bladder, a gastrointestinal organ or tissue, a small intestine, an esophagus, a salivary gland, a tongue, a stomach, a brain, a prostate, or a lymphoid organ.

187. The method of any one of claims 138 to 186, wherein the health condition comprises a risk of the subject having the health condition.

188. The method of claim 187, further comprising determining the risk of the subject having the health condition with an accuracy of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more.

189. The method of claim 187, further comprising determining the risk of the subject having the health condition with a sensitivity of 50% or more, 60% or more, 70% or more, 80% or more, or 90% or more.WSGR Docket No. 63688-708.601190. The method of claim 138, further comprising identifying the subject as having an elevated risk of having the health condition.

191. The method of claim 138, further comprising identifying the subject as not having an elevated risk of having the health condition.

192. The method of any one of claims 138 to 191, further comprising, responsive to the health condition determined in f), administering a treatment to the subject thereby treating the cancer.

193. The method of claim 192, wherein the treatment comprises surgical resection, chemotherapy, targeted therapy, systemic therapy, radiation therapy, immunotherapy, or a combination thereof.

194. The method of claim 138, further comprising, responsive to the absence of the health condition, modifying a treatment to the subject.

195. The method of claim 194, wherein the modifying the treatment comprises modifying a treatment dose of the treatment.

196. A method of determining a health condition of a subject, the method comprising; a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a health condition negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells; h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) averaging the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the atWSGR Docket No. 63688-708.601 least one of the second transcriptomic profile of the subject, the second genomic profile of the subject, or the second exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; j) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; k) enriching a third population of stem cells or progenitor cells in the third biological sample; l) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; m) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; n) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject; and o) determining, based at least in part on the computer processing, the health condition of the subject.

197. A method of determining a health condition of a subject, the method comprising; a) obtaining a first biological sample obtained or derived from the subject at a first time point, wherein the subject comprises a health condition negative status; b) enriching a first population of stem cells or progenitor cells in the first biological sample; c) extracting first nucleic acids from the enriched first population of stem cells or progenitor cells; d) assaying the extracted first nucleic acids to generate at least one of a first transcriptomic profile of the subject, a first genomic profile of the subject, or a first exomic profile of the subject; e) obtaining a second biological sample obtained or derived from the subject at a second time point that is subsequent to the first time point; f) enriching a second population of stem cells or progenitor cells in the second biological sample; g) extracting second nucleic acids from the enriched second population of stem cells or progenitor cells;WSGR Docket No. 63688-708.601 h) assaying the extracted second nucleic acids to generate at least one of a second transcriptomic profile of the subject, a second genomic profile of the subject, or a second exomic profile of the subject; i) obtaining a third biological sample obtained or derived from the subject at a third time point that is subsequent to the first and second time points; j) enriching a third population of stem cells or progenitor cells in the third biological sample; k) extracting third nucleic acids from the enriched third population of stem cells or progenitor cells; l) assaying the extracted third nucleic acids to generate at least one of a third transcriptomic profile of the subject, a third genomic profile of the subject, or a third exomic profile of the subject; m) averaging (i) the at least one of the first transcriptomic profile of the subject, the first genomic profile of the subject, or the first exomic profile of the subject with the at least one of the second transcriptomic profile of the subject, (ii) the second genomic profile of the subject, or the second exomic profile of the subject and (iii) the at least one of the third transcriptomic profile of the subject, the third genomic profile of the subject, or the third exomic profile of the subject, to obtain at least one of a baseline transcriptomic profile of the subject, a baseline genomic profile of the subject, or a baseline exomic profile of the subject; n) obtaining a fourth biological sample obtained or derived from the subject at a fourth time point that is subsequent to the first, second, and third time points; o) enriching a fourth population of stem cells or progenitor cells in the fourth biological sample; p) extracting fourth nucleic acids from the enriched fourth population of stem cells or progenitor cells; q) assaying the extracted third nucleic acids to generate at least one of a fourth transcriptomic profile of the subject, a fourth genomic profile of the subject, or a fourth exomic profile of the subject; r) computer processing (1) the at least one of the baseline transcriptomic profile of the subject, the baseline genomic profile of the subject, or the baseline exomic profile of the subject, and (2) the at least one of the fourth transcriptomic profile of the subject, the fourth genomic profile of the subject, or the fourth exomic profile of the subject; andWSGR Docket No. 63688-708.601 s) determining, based at least in part on the computer processing, the health condition of the subject.

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