Methods, kits, and systems for determining lung cancer status, and methods of treating lung cancer based thereon

Abstract

The present disclosure includes, among other things, methods, kits, and systems for determining a status of lung cancer. In various embodiments, the present disclosure relates to the use of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation as features of a status of lung cancer. In some embodiments, differential modifications and / or differential accessibility are detected and quantified at one or more genomic loci in a biological sample, e.g., cell-free DNA (cfDNA), from a liquid biopsy sample obtained or derived from a subject having lung cancer. In various embodiments, the determined status can be used, e.g., to select a treatment for lung cancer and / or to treat lung cancer.

Description

[0001] Cross-reference to related applications This application claims priority to U.S. Provisional Application No. 63 / 590,215, filed October 13, 2023; U.S. Provisional Application No. 63 / 591,811, filed October 20, 2023; U.S. Provisional Application No. 63 / 575,700, filed April 6, 2024; and U.S. Provisional Application No. 63 / 660,209, filed June 14, 2024; the entire contents of each of these applications are incorporated herein by reference.

[0002] Government support This invention was carried out with government support, based on National Institutes of Health certification P50 CA265826. The government holds certain rights to this invention. Background Technology

[0003] Approximately 80% to 85% of lung cancers are non-small cell lung cancer (NSCLC). The main subtypes of NSCLC are adenocarcinoma (LUAD), squamous cell carcinoma (SCC), and large cell carcinoma (LCC). These subtypes originate from different types of lung cells and are grouped together as NSCLC because their treatment and prognosis are usually similar.

[0004] Approximately 10% to 15% of all lung cancers are small cell lung cancer (SCLC), a highly malignant neuroendocrine tumor with a poor prognosis. Besides primary SCLC, there is also transformed SCLC, which shares similar pathological morphology, molecular characteristics, clinical presentation, and drug sensitivity. However, the pathogenesis and tumor microenvironment of primary and transformed SCLC differ. SCLC transformation is one of the mechanisms by which resistance to chemotherapy, immunotherapy, and targeted therapy develops in NSCLC. It typically occurs in epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma (LUAD) after treatment with tyrosine kinase inhibitors (TKIs) (Sequist et al., Sci Transl Med (2011) 3:75ra26). SCLC transformation can also occur in anaplastic lymphoma kinase (ALK)-positive lung cancer after treatment with ALK inhibitors, and in wild-type EGFR or ALK NSCLC treated with immunotherapy (Ferrer et al., J Thorac Oncol (2019) 14:130-134). Currently, chemotherapy is used to treat transforming SCLC, but its prognosis is not ideal.

[0005] Current methods for classifying lung cancer, particularly SCLC (primary and transformed SCLC), are limited to histology and staging. These methods fail to capture the full complexity of the biology involved in lung cancer and thus only partially characterize the relevant patient population. They also involve invasive tissue biopsies. Invasive biopsies pose risks to patients and may not yield sufficient tissue for a comprehensive examination. More comprehensive and precise diagnostic methods are still needed in the field to determine the status of lung cancer, particularly SCLC (primary or transformed SCLC), including methods independent of tissue biopsies. Improved diagnostic methods will also better support future clinical trials designed to identify patient subgroups that respond to lung cancer therapies. They will also expand our understanding of the underlying biology of lung cancer. This, in turn, can help healthcare practitioners select the most appropriate agents to treat different subtypes of lung cancer, including primary or transformed SCLC. Improved diagnostic methods also help identify and support new treatments in ongoing clinical trials by more accurately identifying the characteristics of lung cancers that respond to treatment, as well as characterizing the mechanisms of resistance to existing therapies (e.g., if a given NSCLC patient develops LUAD due to NSCLC progressing to transformed SCLC, e.g., LUAD-specific treatment). Summary of the Invention

[0006] This disclosure is based, at least in part, on the evidence that the SCLC / LUAD status of a subject's lung cancer can be determined by detecting and quantifying the presence of histone modifications and / or DNA methylation at one or more genomic sites in cell-free DNA (cfDNA) from liquid biopsy samples (e.g., plasma samples obtained from or derived from a subject). This disclosure also covers methods for detecting chromatin accessibility and / or binding of one or more transcription factors at one or more genomic sites, rather than (or in addition to) histone modifications and / or DNA methylation. This disclosure is also based, at least in part, on the evidence that genomic sites differentially modified based on different types of histone modifications (e.g., histone methylation markers such as H3K4me3 and histone acetylation markers such as H3K27ac) and / or DNA methylation can be combined into multimodal classifiers to determine SCLC / LUAD status. These novel unimodal and multimodal classifiers provide minimally invasive methods for determining SCLC / LUAD status that are more accurate, objective, and comprehensive than current tissue-based methods.

[0007] Liquid biopsies are now widely used in clinical oncology to detect cancer recurrence and guide treatment decisions. However, most commercially available cfDNA assays only detect tumor genomic alterations, and not all disease states have characteristic genomic alterations that can be detected. For example, the lack of genomic alterations specific to tSCLC limits the application of genomic-based cfDNA methods in detecting small cell transformation in patients with EGFRm LUAD. Among other things, this disclosure provides tools for analyzing a variety of tumor epigenomic features from patient plasma, including DNA methylation, chromatin accessibility, and histone modifications. Among other things, this disclosure demonstrates that epigenomic cfDNA analysis can be used to detect small cell transformation in patients with EGFRm LUAD progression following EGFR TKI. Diagnosing tSCLC via cfDNA analysis would have immediate clinical operability, as guidelines recommend platinum-etoposide chemotherapy for primary SCLC, a regimen that would not normally be used in LUAD patients.

[0008] This disclosure specifically includes techniques for determining SCLC / LUAD status, and techniques for detecting, monitoring, and / or treating lung cancer based on SCLC / LUAD status. In various embodiments, this disclosure relates to measuring histone modifications in samples obtained from or derived from a subject to detect and / or treat lung cancer based on SCLC / LUAD status. This disclosure specifically includes measurements of histone modifications in cell-free DNA (cfDNA) that are characteristic of lung cancer, and in various embodiments, these measurements can be used, for example, for detecting, monitoring, selecting treatments for and / or treating lung cancer based on SCLC / LUAD status. This disclosure specifically includes measurements of histone modifications in cfDNA that are characteristic of SCLC cancer, and in various embodiments, these measurements can be used, for example, for detecting, monitoring, selecting treatments for and / or treating SCLC cancer. This disclosure specifically includes measurements of histone modifications in cfDNA that are characteristic of LUAD cancer, and in various embodiments, these measurements can be used, for example, for detecting, monitoring, selecting treatments for and / or treating SCLC cancer. In some embodiments, measurements of histone modifications in cfDNA can be used to detect or determine resistance to therapy or transformation of lung cancer (e.g., LUAD cancer) or from LUAD to SCLC. In various embodiments, this disclosure includes exemplary genomic sites that are differentially modified in SCLC and LUAD cancers. In various embodiments, the differentially modified genomic sites in cfDNA are or include one or more enhancers. In various embodiments, the differentially modified genomic sites in cfDNA are or include one or more promoters.

[0009] In various embodiments, a genomic site is differentially modified if it is characterized by increased or decreased histone modifications compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer). Increased or decreased histone modifications may be, for example, increased or decreased histone methylation of one or more specific methylation markers (hypermethylation or hypomethylation, respectively), or combinations thereof; increased or decreased panmethylation; increased or decreased histone acetylation of one or more specific acetylation markers (hyperacetylation or hypoacetylation, respectively), or combinations thereof; and / or increased or decreased panacetylation (e.g., pan-H3 acetylation). In various embodiments, histone methylation may be, or includes histone methylation markers selected from H3K4me1, H3K4me2, H3K4me3, or combinations thereof. In various embodiments, histone methylation may be, or includes H3K4me3. In various embodiments, histone acetylation may be or includes a histone acetylation marker selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, or combinations thereof. In various embodiments, histone acetylation may be or includes H3K27ac.

[0010] In various embodiments, this disclosure relates to measuring DNA methylation in samples obtained from or derived from a subject for the detection and / or treatment of lung cancer based on SCLC / LUAD status. This disclosure particularly includes measurements of DNA methylation in cell-free DNA (cfDNA) that are characteristic of cancer and, in various embodiments, can be used, for example, for the detection, monitoring, selection of treatments for and / or treatment of lung cancer based on SCLC / LUAD status. This disclosure particularly includes measurements of DNA methylation in cfDNA that are characteristic of SCLC cancer and, in various embodiments, can be used, for example, for the detection, monitoring, selection of treatments for and / or treatment of SCLC cancer. This disclosure particularly includes measurements of DNA methylation in cfDNA that are characteristic of LUAD cancer and, in various embodiments, can be used, for example, for the detection, monitoring, selection of treatments for and / or treatment of SCLC cancer. In some embodiments, measurements of DNA methylation in cfDNA can be used to detect or determine resistance to therapy or transformation of lung cancer (e.g., LUAD cancer) (e.g., from LUAD to SCLC). In various embodiments, this disclosure includes exemplary genomic sites that are differentially DNA-methylated in SCLC and LUAD cancers. In various embodiments, a genomic site is differentially modified if it is characterized by an increase or decrease in DNA methylation compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer). In various embodiments, the differentially modified genomic site in cfDNA is or includes one or more enhancers. In various embodiments, the differentially modified genomic site in cfDNA is or includes one or more promoters.

[0011] This invention further relates to measuring chromatin accessibility in cell-free DNA (cfDNA) in various embodiments to determine SCLC / LUAD status. This disclosure particularly includes measurements of chromatin accessibility in cfDNA that are characteristic of SCLC cancer and, in various embodiments, can be used, for example, to detect, monitor, select treatments for SCLC cancer and / or treat SCLC cancer. This disclosure particularly includes measurements of chromatin accessibility in cfDNA that are characteristic of LUAD cancer and, in various embodiments, can be used, for example, to detect, monitor, select treatments for LUAD cancer and / or treat SCLC cancer. In some embodiments, measurements of chromatin accessibility in cfDNA can be used to detect or determine resistance to therapy or transformation of lung cancer (e.g., LUAD cancer) (e.g., from LUAD to SCLC). In various embodiments, this disclosure includes genomic sites that are differentially accessible in SCLC and LUAD cancers. In various embodiments, the differentially accessible genomic sites in cfDNA are or include one or more enhancers. In various implementations, the differentially accessible genomic sites in cfDNA are or include one or more promoters.

[0012] In various embodiments, while not wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds to and / or is related to chromatin accessibility. In various embodiments, while not wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds to and / or is related to chromatin accessibility. In various embodiments, while not wishing to be bound by any particular scientific theory, DNA methylation corresponds to and / or is related to chromatin accessibility.

[0013] In various embodiments, a genomic locus is differentially accessible if it is characterized by increased or decreased chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer). Increased or decreased histone modifications may be, or include, for example, increases or decreases in accessibility as determined by various chromatin accessibility assays known in the art.

[0014] This invention further relates to measuring transcription factor binding in cell-free DNA (cfDNA) in various embodiments to determine SCLC / LUAD status. This disclosure particularly includes transcription factor binding measurements in cfDNA that are characteristic of SCLC cancer and can be used, for example, in various embodiments, for detecting, monitoring, selecting treatments for SCLC cancer and / or treating SCLC cancer. This disclosure particularly includes transcription factor binding measurements in cfDNA that are characteristic of LUAD cancer and can be used, for example, in various embodiments, for detecting, monitoring, selecting treatments for LUAD cancer and / or treating SCLC cancer. In some embodiments, transcription factor binding measurements in cfDNA can be used to detect or determine resistance to therapy or transformation of lung cancer (e.g., LUAD cancer) (e.g., from LUAD to SCLC). In various embodiments, this disclosure includes genomic sites in SCLC and LUAD cancers that are differentially bound by transcription factors. In various embodiments, genomic sites in cfDNA that are differentially bound by transcription factors are or include one or more enhancers. In various embodiments, genomic sites in cfDNA that are differentially bound by transcription factors are or include one or more promoters.

[0015] In various embodiments, while not wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds to and / or is associated with transcription factor binding. In various embodiments, while not wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds to and / or is associated with transcription factor binding. In various embodiments, while not wishing to be bound by any particular scientific theory, DNA methylation corresponds to and / or is associated with transcription factor binding.

[0016] In various embodiments, if a genomic locus is characterized by increased or decreased transcription factor binding compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the genomic locus is differentially bound by transcription factors. Increased or decreased transcription factor binding may be, for example, an increase or decrease in transcription factor binding as determined by various transcription factor binding assays known in the art.

[0017] In one aspect, this disclosure provides a method for determining the SCLC / LUAD status of a subject's lung cancer, the method comprising: quantifying at one or more genomic sites in a biological sample obtained from or derived therefrom, optionally from a liquid biopsy sample, one of the following: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) binding to one or more transcription factors, and / or (iv) DNA methylation.

[0018] In some embodiments, a histone modification assay is used to quantify one or more histone modifications, said assay measuring one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, H3K4me3, and panacetylation. In some embodiments, the histone modification assay detects H3K4me3 modification. In some embodiments, the histone modification assay detects H3K27ac modification. In some embodiments, the histone modification assay is selected from ChIP-seq (chromatin immunoprecipitation sequencing), CUT&RUN (target cleavage and nuclease release) sequencing, and CUT&Tag (target cleavage and fragmentation labeling) sequencing.

[0019] In some implementations, chromatin accessibility is quantified using chromatin accessibility assays selected from ATAC-seq (transposon accessibility chromatin sequencing assay), NOMe-seq (nucleosome occupancy and methylome sequencing), FAIRE-seq (formaldehyde-assisted separation of regulatory elements sequencing), MNase-seq (micrococcal nuclease digestion sequencing), and DNase hypersensitivity assays.

[0020] In some embodiments, a transcription factor binding assay is used to quantify the binding of one or more transcription factors. In some embodiments, the transcription factor binding assay is selected from ChIP-seq (chromatin immunoprecipitation sequencing), CUT&RUN (target cleavage and nuclease release) sequencing, and CUT&Tag (target cleavage and fragmentation labeling) sequencing. In some embodiments, the transcription factor binding assay is used to quantify the binding of one or more transcription factors, said assay detecting the binding of one or more of p300, mediator complex, cohesin complex, RNA pol II, FOXA1, ESR1, PR, MYC, EN1, FOXM1, KLF4, AP-2, RARA, or RUNX1.

[0021] In some implementations, DNA methylation is quantified using bisulfite sequencing (BS-Seq), whole-genome bisulfite sequencing (WGBS), methylated DNA immunoprecipitation sequencing (MeDIP-seq), or methyl-CpG-binding domain sequencing (MBD-seq).

[0022] In some embodiments, the method includes quantifying two or more of the following at one or more genomic sites in cell-free DNA (cfDNA) obtained from or derived from a liquid biopsy sample of a subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) transcription factor binding, and / or (iv) DNA methylation. In some embodiments, the method includes quantifying two or more histone modifications, for example, quantifying H3K4me3 and H3K27ac modifications. In some embodiments, the method includes quantifying one or more histone modifications and DNA methylation, for example, quantifying H3K4me3 and / or H3K27ac modifications and DNA methylation. In some embodiments, the method includes quantifying H3K4me3 modification, H3K27ac modification, and DNA methylation.

[0023] In some embodiments, the biological sample is a liquid biopsy sample, such as a plasma sample, serum sample, or urine sample. In some embodiments, the method includes isolating DNA (e.g., cfDNA) from a liquid biopsy sample (e.g., a plasma sample) of 1 mL, 2 mL, 3 mL, 4 mL, or 5 mL.

[0024] In some implementations, the quantification of one or more histone modifications at one or more genomic sites, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation, compared to a reference, indicates that the subject has SCLC.

[0025] In some implementations, quantification of one or more histone modifications at one or more genomic sites, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation, compared to a reference, indicates that a subject has LUAD.

[0026] In some implementations, the sample is a liquid biopsy sample containing cfDNA, and the method includes: (a) Quantify H3K4me3 modification at one or more genomic loci using an assay that includes enriching cfDNA containing one or more H3K4me3 modifications and sequencing the cfDNA enriched for H3K4me3 modifications (e.g., using cfChIP-seq assay). (b) Quantifying H3K27ac modifications at one or more genomic loci using an assay that includes enriching cfDNA containing one or more H3K27ac modifications and sequencing the H3K27ac-enriched cfDNA (e.g., using cfChIP-seq assay); and / or; (c) Quantify methylated DNA using a assay that includes enriching methylated cfDNA and sequencing the enriched cfDNA to determine the sequence count of sequences having one or more methylated nucleotides (e.g., using an MBD-seq assay).

[0027] In some implementation schemes, (a) Enriching cfDNA containing H3K4me3 modification using a method that includes incubating the sample with an agent that binds to H3K4me3 modification (e.g., an antibody); (b) Enriching cfDNA containing H3K27ac modification using methods including incubating the sample with an agent that binds to H3K27ac modification (e.g., an antibody); and / or (c) Enrich methylated cfDNA using a method that includes incubating the sample with an agent that binds methylated DNA (e.g., an antibody or a methyl-binding domain).

[0028] In some embodiments, an agent that binds to H3K4me3 modification, an agent that binds to H3K27ac modification, and / or an agent that binds to methylated DNA (e.g., via covalent or non-covalent bonds) is attached to a physical support (e.g., beads, magnetic beads, agarose beads, or magnetic epoxy beads) and then incubated with the sample.

[0029] In some implementations, if the method includes incubation with two or more of the following: (a) an agent that binds to H3K4 modification, (b) an agent that binds to H3K27ac modification, and (c) an agent that binds to methylated DNA, the sample is incubated with the two or more agents in the following manner: (1) sequentially, or (2) in parallel (e.g., where the sample is divided into several portions and each portion is incubated with a different agent).

[0030] In some implementations, sequencing is performed using next-generation sequencing methods.

[0031] In some implementations, the method includes attaching (e.g., linking) an adaptor to cfDNA obtained from a subject (e.g., after enriching cfDNA for cfDNA containing one or more H3K4me3 modifications, cfDNA containing one or more H3K27ac modifications, and / or methylated cfDNA).

[0032] In some implementations, the method includes amplifying multiple transformed DNA fragments after attaching an adaptor to multiple DNA fragments.

[0033] In some embodiments, sequence reads are mapped to a reference genome. In some embodiments, non-unique mappings and redundant sequence reads are discarded before quantifying one or more epigenetic biomarkers. In some embodiments, sequence reads are mapped to a reference genome, wherein one or more genomic loci correspond to sequence read peaks, where sequence read peaks correspond to regions in the genome where the number of sequence reads is higher than the local background. In some embodiments, peaks in high-noise regions are ignored when identifying genomic loci where the number of sequence reads is higher than the local background and / or when identifying genomic loci associated with the SCLC / LUAD disease state. In some embodiments, peaks in leukocyte regions are ignored when identifying genomic loci where the number of sequence reads is higher than the local background and / or when identifying genomic loci associated with the SCLC / LUAD disease state. In some embodiments, peaks in regions that may be artifacts are removed. In some embodiments, peaks shorter than 50 bp are removed.

[0034] In some embodiments, H3K4me3 modification, H3K27ac modification, and / or DNA methylation are quantified by summing the number of sequence reads that overlap with one or more genomic sites with at least one nucleotide. In some embodiments, sequence reads are adjusted according to sequencing depth (e.g., normalizing sequence read quantiles to a common reference distribution) and / or ChIP quality before summing. In some embodiments, sequence counts are normalized to aggregated counts of a set of regions (e.g., 10,000 regions) in a given sample that have previously been identified as having DNAse hypersensitivity in most cell types. In some embodiments, an estimate of the local background signal is subtracted from the sequence reads at each genomic site before summing.

[0035] In some embodiments, the method includes comparing measurements of one or more epigenetic biomarkers to reference values. In some embodiments, the reference value is a predetermined threshold, a measurement of a liquid biopsy sample, a measurement of a liquid biopsy sample obtained from a cohort of subjects, and / or a normalized value. In some embodiments, the predetermined threshold or normalized value has been previously demonstrated to distinguish between LUAD and SCLC subjects (e.g., by an AUROC greater than 0.5). In some embodiments, the reference value is a measurement of a liquid biopsy sample obtained from a cohort of subjects previously identified as having LUAD or SCLC. In some embodiments, a cohort of subjects has been previously identified as having lung cancer (e.g., LUAD or SCLC).

[0036] In some implementations, the method includes calculating the sequence read density at one or more genomic loci. In some implementations, the sequence read density can be calculated in the following manner: (a) Summing the background-adjusted sequence counts at each of one or more genomic loci and dividing by the sum of the kilobases at one or more genomic loci; or (b) For each genomic locus, divide the background adjustment fragment count by the number of kilobases of the genomic locus, and then sum over each locus.

[0037] In some implementations, one or more genomic loci include one or more genomic loci with increased levels of one or more of the following epigenetic biomarkers: (a) a sample obtained from a subject with SCLC compared to a sample obtained from a subject with LUAD; and / or (b) a sample obtained from a subject with LUAD compared to a sample obtained from a subject with SCLC.

[0038] In some embodiments, the method described herein includes calculating the SCLC / LUAD ratio score. In some embodiments, the SCLC / LUAD ratio score can be calculated by methods including the following: (a) SCLC sequence read density is calculated by summing background-adjusted sequence counts at each of one or more genomic loci where the level of one or more epigenetic biomarkers is increased in a sample obtained from a subject with LUAD, compared to a sample obtained from a subject with SCLC; (b) The LUAD sequence read density was calculated by summing the background-adjusted sequence counts at each of one or more genomic loci where the level of one or more epigenetic biomarkers was increased in samples obtained from subjects with LUAD, compared to samples obtained from subjects with SCLC; and (c) Divide the SCLC sequence read density by the LUAD sequence read density.

[0039] In some embodiments, the method includes determining SCLC / LUAD ratio scores for one or more epigenetic biomarkers. In some embodiments, the method includes determining SCLC / LUAD ratio scores for two or more epigenetic biomarkers. In some embodiments, the method includes determining SCLC / LUAD ratio scores for two or more epigenetic biomarkers and combining the two or more SCLC / LUAD ratio scores. In some embodiments, the method includes determining the SCLC / LUAD ratio score for each of H3K4me3 modification, H3K27ac modification, and methylated DNA, and combining each of the ratio scores. In some embodiments, fitted values ​​determined by logistic regression may be used to combine two or more ratio scores.

[0040] In some embodiments, the method includes comparing one or more quantified epigenetic biomarkers to reference values, wherein an increase or decrease in one or more epigenetic biomarkers compared to the reference values ​​indicates that a subject has SCLC or LUAD. In some embodiments, the reference values ​​are predetermined thresholds, measurements from liquid biopsy samples, and / or normalized values. In some embodiments, the reference values ​​are measurements from liquid biopsy samples obtained from a group of subjects previously identified as having LUAD or not having cancer. In some embodiments, predetermined thresholds and normalized values ​​have been previously demonstrated to distinguish between LUAD and SCLC subjects (e.g., providing an AUROC value of at least 0.5). In some embodiments, a group of subjects has been previously identified as having lung cancer (e.g., LUAD or SCLC).

[0041] In some embodiments, quantification of one or more histone modifications at one or more genomic sites, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation, compared to a reference, indicates that a subject has SCLC cancer (e.g., primary SCLC cancer or transformed SCLC cancer). In some embodiments, the reference value is a predetermined threshold, a measurement of a liquid biopsy sample, and / or a normalized value, optionally wherein the reference value is a measurement of a liquid biopsy sample obtained from a group of subjects previously diagnosed with LUAD cancer.

[0042] In some implementations, the subject has been previously identified as having lung cancer, has an increased susceptibility to lung cancer, and / or the method further includes determining whether the subject has lung cancer. In some implementations, the subject has an increased susceptibility to SCLC.

[0043] In some embodiments, quantification of one or more histone modifications at one or more genomic sites, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation, compared to a reference, indicates that a subject has LUAD cancer. In some embodiments, the reference value is a predetermined threshold, a measurement of a liquid biopsy sample, and / or a normalized value, optionally wherein the reference value is a measurement of a liquid biopsy sample obtained from a group of subjects previously diagnosed with SCLC cancer.

[0044] In some embodiments, the lung cancer is metastatic lung cancer. In some embodiments, the lung cancer exhibits loss of TP53 and / or RB1 (e.g., containing one or more loss-of-function mutations). In some embodiments, the lung cancer exhibits TKI resistance.

[0045] In some implementations, the SCLC is primary SCLC. In some implementations, the SCLC is transforming SCLC. In some implementations, the SCLC is transforming SCLC, and the LUAD is EGFRm LUAD.

[0046] In some implementations, for methods that presuppose that the subject has previously been diagnosed with EGFRm (EGFR mutant) LUAD, LUAD is EGFRm LUAD and SCLC is transformative SCLC (tSCLC).

[0047] In some embodiments, the method includes quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic loci in Tables 1 through 3. In some embodiments, the method includes quantifying H3K4me3 modifications at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the method includes quantifying H3K27ac modifications at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the method includes quantifying H3K27ac at at least 1, 2, 3, or 4 genomic loci in Table 4. In some embodiments, the method includes quantifying H3K4me3 or H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5. In some embodiments, the method includes quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3. In some implementations, the method includes quantifying DNA methylation at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5.

[0048] In some implementations, the area under the recipient operating characteristic curve (AUROC) used to determine whether a subject has SCLC or LUAD cancer is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95).

[0049] In some implementations, SCLC cancer is SCLC cancer based on histological testing (e.g., IHC test), and LUAD cancer is LUAD cancer based on histological testing (e.g., IHC test). In some implementations, the subject has been previously diagnosed with lung cancer. In some implementations, the sample contains a detectable amount of cfDNA (e.g., where the estimated tumor fraction is >3%, as determined by iChorCNA).

[0050] In some implementations, samples are obtained from subjects with lung cancer, where a biopsy of the lung cancer is not possible and / or not feasible.

[0051] In some embodiments, if a subject is determined to have SCLC, the method further includes subtyping the SCLC. In some embodiments, SCLC is subtyped by detecting the activity (e.g., expression level) of one or more transcription factors. In some embodiments, SCLC is subtyped by detecting increased activity (e.g., increased expression) of one or more transcription factors (e.g., an increase in average expression relative to the mean expression in subjects with SCLC and / or one or more subjects characterized by an alternative SCLC subtype). In some embodiments, SCLC is subtyped by detecting decreased activity (e.g., decreased expression) of one or more transcription factors (e.g., a decrease in mean expression relative to the mean expression in subjects with SCLC and / or one or more subjects characterized by an alternative SCLC subtype). In some embodiments, one or more transcription factors are ASCL1, NEUROD1, YAP1, and / or POU2F3. In some embodiments, one or more transcription factors are ASCL1, NEUROD1, YAP1, and POU2F3. In some embodiments, the SCLC subtype is characterized by increased YAP1 activity (e.g., increased relative to ASCL1, NEUROD1, and POU2F3). In some embodiments, the SCLC subtype is characterized by increased activity of ASCL1, NEUROD1, or POU2F3 (e.g., SCLC subtypes are classified based on which of ASCL1, NEUROD1, and POU2F3 is most highly expressed relative to each other). In some embodiments, the SCLC subtype is an inflammatory SCLC subtype (SCLC-1) and optionally characterized by low activity (e.g., low expression) of ASCL1, NEUROD1, and POU2F3 (e.g., lower activity relative to healthy subjects, average subjects with SCLC, and / or one or more alternative SCLC subtypes) and / or inflammatory gene signatures.

[0052] In some embodiments, the activity of one or more transcription factors is determined by measuring transcription factor binding. In some embodiments, the activity of one or more transcription factors is assessed using a method comprising: quantifying, optionally, at one or more genomic sites in cell-free DNA (cfDNA) from a biological sample obtained from or derived from a subject, the following: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) binding of one or more transcription factors, and / or (iv) DNA methylation. In some embodiments, a histone modification assay is used to quantify one or more histone modifications, said assay measuring one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, H3K4me3, and panacetylation. In some embodiments, the histone modification assay detects H3K4me3 modification. In some embodiments, the histone modification assay detects H3K27ac modification. In some embodiments, the one or more genomic sites are selected from those provided in Table 4.

[0053] In some embodiments, this disclosure provides a treatment method in which a subject has been previously identified as having mEGFRm LUAD before using the methods described herein to determine the SCLC / LUAD status, wherein the method comprises: administering SCLC therapy (e.g., as described herein) if the subject is identified as having SCLC using the methods described herein, and administering LUAD therapy (e.g., as described herein) if the subject is identified as having LUAD using the methods described herein.

[0054] In another aspect, this disclosure provides a method for treating a subject with lung cancer, the method comprising: administering a lung cancer therapy to the subject based on the SCLC / LUAD status of the lung cancer, wherein the SCLC / LUAD status of the lung cancer is determined using any of the methods described above for determining SCLC / LUAD status. In some embodiments, the method further comprises determining the SCLC / LUAD status of the lung cancer using any of the methods described above for determining SCLC / LUAD status. In some embodiments, the lung cancer is identified as SCLC cancer, and the cancer therapy is an SCLC cancer therapy. In some embodiments, the SCLC cancer has been subtyped, and the method comprises administering an SCLC therapy to the subject based on the SCLC subtype (e.g., administering an SCLC therapy that has been shown to provide improved benefit for the SCLC subtype compared to other treatments typically administered to subjects with SCLC).

[0055] In some implementations, SCLC therapy includes administration of (i) an agent targeting DLL3 (e.g., tarlatlamab), and / or (ii) a combination of a PD-L1 inhibitor and platinum-based etoposide chemotherapy or a PARP inhibitor.

[0056] In some implementations, if the lung cancer has been identified as EGFRm LUAD with a high risk of SCLC transformation (e.g., exhibiting loss of TP53 and / or RB1), the method includes administering a combination of platinum-based / etoposide chemotherapy and osimertinib.

[0057] In some implementations, SCLC cancers have been subtyped based on increased ASCL1 activity (e.g., expression), and SCLC therapy is associated with providing improved treatment benefits to subjects diagnosed with ASCL1 subtype SCLC (e.g., improvements over alternative treatments typically administered to subjects with SCLC). In some implementations, SCLC therapy is a BCL2 apoptosis modulator, a BCL2 inhibitor, a DLL3 inhibitor (e.g., rovalpituzumab tesirine), an LSD1 inhibitor, and / or a CEACAM5-targeting agent (e.g., labetuzumab govitecan).

[0058] In some implementations, SCLC cancers have been subtyped based on increased NEUROD1 activity (e.g., expression), and SCLC therapy is associated with providing improved treatment benefits to subjects diagnosed with NEUROD1 subtype SCLC (e.g., improvements over alternative treatments typically administered to subjects with SCLC). In some implementations, SCLC therapy is an Aurora kinase inhibitor, a somatostatin receptor 2 (SSTR2) inhibitor (e.g., lanreotide), an SSTR2-targeting therapy (e.g., PEN-221), or an immunotherapy (e.g., durvalumab) co-administered with platinum-based etoposide.

[0059] In some implementations, SCLC cancers have been subtyped based on increased POU2F3 activity (e.g., expression), and SCLC therapy is associated with improved treatment benefit in subjects diagnosed with SCLC of the POU2F3 subtype. In some implementations, SCLC therapy includes an insulin-like growth factor 1 receptor inhibitor (optionally without chemotherapy), cisplatin, a PARP inhibitor, antimetabolites (e.g., antifolate or nucleoside analogs), and / or durvalumab (optionally without platinum-based etoposide).

[0060] In some implementations, SCLC cancers have been subtyped based on increased YAP1 activity (e.g., expression), and SCLC therapy is associated with improved treatment benefit in subjects diagnosed with YAP1 subtype SCLC. In some implementations, SCLC therapy includes co-administration of durvalumab with platinum-based etoposide.

[0061] In some embodiments, the SCLC subtype is an inflammatory SCLC subtype (SCLC-I) and optionally characterized by (i) low activity (e.g., low expression) of ASCL1, NEUROD1, and POU2F3 (e.g., lower activity relative to healthy subjects, subjects with SCLC, and / or one or more alternative SCLC subtypes), and / or (ii) poor response to immune checkpoint blockade. In some embodiments, SCLC therapy includes anti-PD-L1 agents and chemotherapy agents co-administered with platinum-etoposide, immune checkpoint blockade, Bruton's tyrosine kinase (BTK) inhibitors, ibrutinib, EMT inhibitors (e.g., HDACi (e.g., mocetinostat)), MICA inhibitors (e.g., IPH43), and / or immunotherapy (e.g., durvalumab).

[0062] In some implementations, lung cancer is identified as LUAD cancer, and the cancer treatment is a LUAD cancer treatment. In some implementations, a LUAD cancer treatment includes the administration of a selective EGFR tyrosine kinase inhibitor (e.g., osimertinib).

[0063] In another aspect, this disclosure provides a method for monitoring the SCLC / LUAD status of a subject's lung cancer and optionally treating the lung cancer, the method comprising: determining the SCLC / LUAD status of the lung cancer at a first time point and a second time point using any of the methods described above for determining the SCLC / LUAD status. In some embodiments, the subject is being treated with a therapeutic agent that can cause transformation from LUAD cancer (or more commonly NSCLC cancer) to SCLC cancer, for example, wherein the subject has epidermal growth factor receptor (EGFR) mutant LUAD cancer and is being treated with a tyrosine kinase inhibitor (TKI), the subject has anaplastic lymphoma kinase (ALK) positive LUAD cancer and is being treated with an ALK inhibitor, or the subject has wild-type EGFR or ALK LUAD cancer and is being treated with immunotherapy. In some embodiments, the method further comprises administering lung cancer therapy, optionally SCLC cancer therapy or LUAD cancer therapy, to the subject based on the SCLC / LUAD status of the lung cancer at the second time point, optionally wherein the type, dose, and / or frequency of administration of the cancer therapy is adjusted based on the SCLC / LUAD status of the lung cancer at the second time point.

[0064] In another aspect, this disclosure provides a method for treating a subject with lung cancer, the method comprising: (i) administering an SCLC therapeutic agent to the subject, wherein the subject has been determined to possess a validated epigenetic characteristic indicative of SCLC cancer based on analysis of cell-free DNA (cfDNA) from a biological sample obtained from or derived therefrom, optionally from a liquid biopsy sample; or (ii) administering a LUAD therapeutic agent to the subject, wherein cell-free DNA from a biological sample obtained from or derived therefrom, optionally from a liquid biopsy sample, has been... Analysis of (cfDNA) has identified subjects with validated epigenetic features indicative of LUAD cancer, wherein the presence of validated epigenetic features has been determined using a validated classifier obtained by: (a) identifying genomic features of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in biological samples obtained from subjects in a first cohort previously diagnosed with SCLC cancer (e.g., primary SCLC or transformed SCLC); (b) identifying genomic features of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in biological samples obtained from healthy subjects in a second cohort or subjects previously diagnosed with LUAD cancer; and (c) comparing the genomic features identified in step (a) with those identified in step (b) to identify those with statistically distinct histone modifications, (d) Genomic loci (“differential loci”) with histone modifications, chromatin accessibility, transcription factor binding, and / or DNA methylation levels at differential loci; to distinguish (i) samples from one or more biological samples obtained from a first cohort and (ii) samples from one or more biological samples obtained from a second cohort, to identify samples with histone modifications, chromatin accessibility, transcription factor binding, and / or DNA methylation level characteristics (“epigenetic characteristics”) that indicate the sample may have been obtained from the first cohort; and (e) obtaining a validated classifier by validating the classifier in step (d) on a third cohort comprising independent, blinded subjects with SCLC and LUAD cancers, and selecting a threshold such that the validated classifier predicts SCLC cancer, wherein the area under the receiver operating characteristic curve (AUROC) is greater than 0.5. (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95), in which subjects falling into the predicted SCLC cancer group exhibited validated epigenetic characteristics, and subjects not falling into the SCLC cancer group lacked validated epigenetic characteristics.

[0065] In some implementations, the differential sites in step (c) are determined by comparing genomic features of one or more histone modifications and / or DNA methylation in (i) one or more biological samples from a first cohort and (ii) one or more biological samples from a second cohort.

[0066] In some implementations, the classifier in step (d) is trained on histone modification and / or DNA methylation levels in (i) one or more biological samples from a first cohort and (ii) one or more biological samples from a second cohort.

[0067] In some implementations, the classifier validated in step (e) is validated using liquid biopsy samples from a third queue.

[0068] In some embodiments, the classifier in step (d) is trained on two or more histone modification levels at differentially expressed sites. In some embodiments, the two or more histone modification levels include H3K4me3 and H3K27ac modification levels.

[0069] In some embodiments, the classifier in step (d) is trained on one or more histone modification levels and DNA methylation at differential sites. In some embodiments, one or more histone modification levels include H3K4me3 and / or H3K27ac modification levels. In some embodiments, the classifier in step (d) is trained using ridge regression, elastic network regression, or lasso regression. In some embodiments, one or more histone modification levels include H3K4me3 and / or H3K27ac modification levels. In some embodiments, one or more histone modification levels include both H3K4me3 and H3K27ac modification levels. In some embodiments, the biological sample is a liquid biopsy sample, such as a plasma sample, serum sample, or urine sample.

[0070] In another aspect, this disclosure provides a kit comprising reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1 to 3. In some embodiments, the kit comprises reagents for quantifying H3K4me3 at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the kit comprises reagents for quantifying H3K27ac at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the kit comprises reagents for quantifying H3K27ac at at least 1, 2, 3, or 4 genomic loci in Table 4. In some embodiments, the kit comprises reagents for quantifying H3K4me3 or H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5. In some embodiments, the kit includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3. In some embodiments, the kit includes reagents for quantifying DNA methylation at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5.

[0071] In some embodiments, the kit includes one or more antibodies for ChIP-seq, optionally said one or more antibodies specifically binding to H3K4me3 or H3K27ac modified histones. In some embodiments, the kit includes one or more methyl-binding domains for MBD-seq.

[0072] In some embodiments, the kit includes reagents for isolating cell-free DNA (cfDNA) from liquid biopsy samples. In some embodiments, the kit includes reagents for sequencing library preparation. In some embodiments, the kit includes reagents for sequencing. In some embodiments, the kit includes instructions for determining whether a subject has SCLC or LUAD cancer, optionally for determining whether a subject has an SCLC cancer subtype characterized by increased ASCL1, NEUROD1, YAP1, and / or POU2F3 activity (e.g., expression).

[0073] In another aspect, this disclosure provides a non-transient computer-readable storage medium encoded with a computer program, wherein the program contains instructions that, when executed by one or more processors, cause the one or more processors to perform operations to execute any of the methods described above for determining the SCLC / LUAD state.

[0074] In another aspect, this disclosure provides a computer system including a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to execute any of the methods described above for determining the SCLC / LUAD state.

[0075] In another aspect, this disclosure provides a system for determining the SCLC / LUAD status of a subject's lung cancer, the system comprising a sequencer configured to generate a sequencing dataset from a sample; and a non-transient computer-readable storage medium and / or computer system of this disclosure. In some embodiments, the sequencer is configured to generate a whole-genome sequencing (WGS) dataset from a sample. In some embodiments, the system further includes a sample preparation device. In some embodiments, the sample preparation device is configured to prepare a sample for sequencing from a biological sample (optionally, a liquid biopsy sample). In some embodiments, the sample preparation device includes reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic sites in cell-free DNA (cfDNA) from a biological sample (optionally, a liquid biopsy sample). In some embodiments, one or more genomic sites are selected from Tables 1 to 3. In some embodiments, the device includes reagents for quantifying H3K4me3 at, for example, at least 5, 10, 20, 30, 40, or 50 genomic sites in Table 1. In some embodiments, the device includes reagents for quantifying H3K27ac at, for example, at least 5, 10, 20, 30, 40, or 50 genomic loci as shown in Table 2. In some embodiments, the device includes reagents for quantifying DNA methylation at, for example, at least 5, 10, 20, 30, 40, or 50 genomic loci as shown in Table 3. In some embodiments, the reagents comprise one or more antibodies for ChIP-seq, optionally said antibodies specifically binding to H3K4me3 or H3K27ac-modified histones. In some embodiments, the reagents comprise one or more methyl-binding domains for MBD-seq. In some embodiments, the device includes reagents for isolating cell-free DNA (cfDNA) from biological samples (optionally, liquid biopsy samples). In some embodiments, the device includes reagents for sequencing library preparation. In some embodiments, the sequencer includes reagents for sequencing.

[0076] In some implementations, the method is used to determine the SCLC and / or LUAD status of a subject (e.g., a patient). The method may include receiving (e.g., via a processor of a computing device) one or more genomic features of the subject, including one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation. The method may further include determining whether the subject possesses epigenetic features indicative of SCLC or LUAD by classifying the genomic features using a classifier (e.g., by a processor).

[0077] In some embodiments, the classifier has been trained using one or more genomic features, including one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation, from one or more biological samples obtained from a cohort of subjects previously identified as having SCLC (e.g., primary SCLC or transformed SCLC) or LUAD. In some embodiments, the genomic features are relative to differentially expressed sites, which correspond to statistically different levels of histone modifications, chromatin accessibility, transcription factor binding, and / or DNA methylation between one or more biological samples obtained from a cohort of subjects previously identified as having SCLC (e.g., primary SCLC or transformed SCLC) or LUAD.

[0078] In some implementations, the classifier is trained based on the levels of two or more histone modifications at differentially expressed sites. In some implementations, the genomic features contain two or more histone modification levels. In some implementations, such two or more histone modification levels include H3K4me3 and H3K27ac modification levels.

[0079] In some embodiments, genomic features include one or more histone modification levels and DNA methylation. In some embodiments, the classifier is trained based on one or more histone modification levels and DNA methylation at differentially expressed sites. In some embodiments, such one or more histone modification levels include H3K4me3 and / or H3K27ac modification levels. In some embodiments, such one or more histone modification levels include both H3K4me3 and H3K27ac modification levels.

[0080] In some implementations, the classifier has been trained using data derived from plasma. In other implementations, such a classifier has been trained using data derived from liquid biopsy samples.

[0081] In some implementations, the classifier is a validated classifier. In some implementations, the classifier is validated by selecting a threshold such that the area under the recipient operating characteristic curve (AUROC) for the validated classifier predicting SCLC cancer is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95). In some implementations, the classifier has been validated on a cohort of independent subjects with SCLC (e.g., primary SCLC or transformed SCLC) and LUAD, where subjects falling into the predicted SCLC (e.g., primary SCLC or transformed SCLC) cancer group exhibit validated epigenetic characteristics, and subjects not falling into the predicted SCLC cancer group lacked validated epigenetic characteristics. In some implementations, the classifier has been validated using liquid biopsy sample data.

[0082] A non-transient computer-readable storage medium may encode a computer program, wherein the program may contain instructions that, when executed by one or more processors, cause the one or more processors to perform operations to perform a method for determining SCLC and / or LUAD of cancer in a subject (e.g., a patient). A computer system may include memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform a method for determining SCLC and / or LUAD of cancer in a subject (e.g., a patient).

[0083] In some embodiments, a method of treating a subject with cancer includes administering a SCLC therapeutic agent to the subject, wherein the subject has been determined to have validated epigenetic characteristics indicative of SCLC based on analysis of cell-free DNA (cfDNA) from a biological sample obtained from or derived from the subject, optionally from a liquid biopsy sample. In some embodiments, the presence of validated epigenetic characteristics has been determined using a classifier (e.g., a validated classifier) ​​according to methods used to determine SCLC and / or LUAD in a subject (e.g., a patient).

[0084] In some embodiments, a method of treating a subject with cancer includes administering a LUAD therapeutic agent to the subject, wherein the subject has been determined to have a validated epigenetic signature indicating LUAD based on analysis of a biological sample obtained from or derived from the subject, optionally from a liquid biopsy sample. In some embodiments, the presence of the validated epigenetic signature has been determined using a classifier (e.g., a validated classifier) ​​according to methods used to determine SCLC and / or LUAD in a subject (e.g., a patient). Attached Figure Description

[0085] Figure 1 Representative ROC curves of exemplary SCLC / LUAD state classifiers generated according to Example 2 are shown. As shown, different classifiers were generated using genomic sites from Tables 1 to 3 for different modifications, namely (i) H3K4me3 modification, (ii) H3K27ac modification, (iii) DNA methylation (MBD), or (iv) all of the above (combinations). For individual modifications, the AUC was calculated separately based on the SCLC / LUAD ratio for each modification. For combined modifications, the AUC was calculated based on the fitted values ​​from logistic regression. Each individual modification, as well as the combination of all three, correctly distinguished between SCLC and LUAD. The AUC value for H3K4me3 modification was 0.85, the AUC value for H3K27ac modification was 0.83, the AUC value for DNA methylation (MBD) was 0.9, and the AUC value for the combination of all three was 0.92.

[0086] Figure 2 Representative, non-limiting graphs are shown illustrating the accuracy of SCLC / LUAD status (based on AUCROC) determination using the classifier generated according to Example 2. As described in Example 3, the mean AUC and 95% confidence interval for 500 replicate region samples used to calculate the SCLC / LUAD ratio are shown. As indicated, different subsets of genomic loci from Tables 1 (H3K4me3), 2 (H3K27ac), 3 (MBD), and combinations of Tables 1 through 3 are used for different samples.

[0087] Figure 3 Representative, non-limiting graphs are shown illustrating the accuracy determined using the SCLC / LUAD state (based on AUCROC) of the classifier generated according to Example 2. As described in Example 4, the widths of the genomic loci in Tables 1 through 3 were increased / decreased, and the AUC was calculated based on the recalculated SCLC / LUAD ratio. As shown, increasing or decreasing the width of the classifier input genomic region by up to 50% had almost no impact on prediction performance.

[0088] Figure 4 Results of experiments conducted according to Example 5 are shown, in which different machine learning (ML) methods were used to generate different SCLC / LUAD state classifiers using genomic loci from Tables 1 through 3. The results show the mean (95% CI) AUC of 50 five-fold cross-validations. Instead of using the library-size-normalized background adjustment counts at each individual genomic locus to calculate the SCLC / LUAD ratio score, these counts were fed to the three different ML algorithms. As shown, the different ML methods (glmnet, random forest, and SVM) produced similar predictive performance.

[0089] Figure 5 The diagram shows the stratification by cancer type. DLL3 Normalized H3K4me3 cfChIP-seq signal at the promoter. As shown, the H3K4me3 cfChIP-seq signal was highest in Merkel cell carcinoma, neuroendocrine prostate cancer (NEPC), melanoma, and small cell lung cancer (SCLC). The lower and upper hinges represent the 25th and 75th percentiles, respectively; the whiskers extend to 1.5 times the interquartile range (IQR).

[0090] Figure 6 A heatmap showing the quantified and scaled enhancer and promoter activities of identified SCLC subtype driver genes (columns) in plasma samples (rows) from SCLC patients is presented. Unsupervised clustering of enhancer activities reveals distinct groupings of SCLC samples, demonstrating the ability to infer SCLC subtypes using an epigenome-based liquid biopsy platform. The observed SCLC subtypes are distributed across 70% SCLC-A, 11% SCLC-N, 17% SCLC-P, and 2% SCLC-Y. 3 Within the expected distribution of (p=0.2).

[0091] Figure 7 Patient-specific promoter signals of genes associated with differential transcriptional biology in SCLC and LUAD are shown. As illustrated, significant differences are visible between SCLC and LUAD. Samples were histologically grouped and ordered by the estimated ichorCNA ctDNA fraction within each group.

[0092] Figure 8 This paper demonstrates the ability of a classifier to distinguish between subjects with SCLC and LUAD using enhancer, promoter, and methylation signals quantified at sites (e.g., sites described herein) that are identified as differentially expressed between SCLC and NSCLC in cell lines. Five-fold cross-validation using regularized logistic regression was used to estimate the predictive performance for classifying SCLC and LUAD. Selected features included 65% promoter, 23% enhancer, and 13% methylation. Figure 8 As shown, even for samples with ctDNA levels below the ichorCNA detection limit, the predictive performance remains high, indicating that the assay is sensitive even at levels below 3% ctDNA.

[0093] Figure 9The results of a computer simulation experiment used to determine the detection limit of the assay described herein are shown. Computer-simulated plasma samples were created to simulate lower ctDNA levels by diluting each of 17 LUAD and 12 SCLC plasma samples from 24 healthy plasma samples with high ctDNA characteristics. The computer-simulated mixtures were classified using regularized logistic regression, employing a leave-one-out method, where all mixtures generated from a given cancer and healthy sample pair were excluded, and predictions were then made based on a model fitted to the remaining mixture samples. Figure 9 As shown, even with ctDNA at 0.5%, the AUC estimates for these simulations are still above 0.90; and even with ctDNA at 0.4%, the AUC estimates are still above 0.80.

[0094] Figure 10 This is a block diagram of an exemplary network environment for the methods and systems described herein, according to an illustrative embodiment of this disclosure.

[0095] Figure 11 This is a block diagram of an exemplary computing device and an exemplary mobile computing device used in illustrative embodiments of this disclosure.

[0096] Figure 12 This paper outlines an experimental method for comprehensive epigenomic analysis of lung cancer patient-derived xenografts (PDX), including multianalyte epigenomic analysis of cfDNA in 1 mL of patient plasma, and detection in a non-invasive manner. EGFR SCLC conversion in m LUAD patients. Those skilled in the art will understand that Figure 1 One or more (e.g., all) of the analytes shown may be used in the methods described in this disclosure. Those skilled in the art will also understand that the analytes may be evaluated in any order, to the extent permitted by the experimental protocol.

[0097] Figure 13 For LUAD, tSCLC and Primary Comprehensive epigenomic analysis of SCLC revealed extensive epigenomic reprogramming in small transformations. (A) Principal component analysis (PCA) plots of ATAC, H3K27ac ChIP, H3K4me3 ChIP, H3K27me3 ChIP, MeDIP, and RNA sequencing data revealed the relationship between tSCLC tumors and... Primary Clustering of SCLC tumors and their differentiation from LUAD tumors. (B) EGFRm tSCLC, EGFRm LUAD and PrimaryRepresentative epigenomic data from SCLC PDX showed enhanced signals of active gene transcription markers (ATAC-seq, H3K27ac ChIP-seq, H3K4me3 ChIP-seq, and genesomal DNA methylation) at the neural lineage-defining genes in tSCLC, while the signal of the repressive marker (H3K27me3 ChIP-seq) was attenuated. Each trajectory depicted the signal intensity of a specific epigenetic marker in a given sample.

[0098] Figure 14 Comparative analysis identified a robust series of significantly different epigenomic features between LUAD and SCLC. (A) Heatmap: Normalized H3K27ac tag density at differentially expressed H3K27ac sites between LUAD and SCLC tumors (FDR-adjusted P < 0.001 and log2 fold change > 2), located at the peak center ± 2 kb. (B) Volcano plot showing the overlap of differentially expressed genes with log2 fold change between LUAD PDX and SCLC PDX with the corresponding differentially expressed H3K27ac peaks enriched in LUAD (blue) and SCLC (red). Multiple hypothesis testing was performed to correct for two-sided p-values ​​(FDR-adjusted P < 0.05). Abbreviations: LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; tSCLC, transformed SCLC; EGFR m, EGFR Mutant type.

[0099] Figure 15 Non-invasive detection of tSCLC was performed via tissue information epigenomic cfDNA analysis. Box plots illustrate the results based on H3K27ac cfChIP-seq analysis (A), H3K4me3 cfChIP-seq analysis (B), cfDNA methylation analysis (C), or cfDNA chromatin accessibility analysis (D). EGFR m LUAD and EGFR cfDNA-SCLC risk score for plasma samples from patients with m tSCLC. Box plots show the interquartile range and median for each dataset, with the whisker line representing the largest value at 1.5 times the interquartile range or the maximum value in the dataset. P-values ​​were calculated using the Mann-Whitney test. Corresponding ROC curves and AUROC are included. Abbreviations: cfDNA, cell-free DNA; LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; tSCLC, transformed SCLC; EGFR m, EGFR Mutant type; AUROC, area under the acceptor operating characteristic curve.

[0100] Figure 16Integrating multiple epigenomic cfDNA analytes improves the non-invasive detection of tSCLC. (A) A Venn diagram illustrates the overlap of H3K27ac, DNA methylation, and open chromatin sites between SCLC PDX and LUAD PDX. (B) A box plot illustrates an integrated epigenomic classifier based on H3K27ac incorporation, DNA methylation, and chromatin accessibility analysis. EGFR m LUAD and EGFR cfDNA SCLC risk score for plasma samples from patients with m tSCLC. Box plots show the interquartile range and median for each dataset, with the whisker line representing the larger value at 1.5 times the interquartile range or the maximum value in the dataset. P-values ​​were calculated using the Mann-Whitney test. ROC curves and AUROC are included. The optimal cutoff was calculated using the Youden index. (C) SCLC risk score and EGFR m tSCLC and EGFR Correlation of estimated cfDNA tumor score in m LUAD patients. Abbreviations: cfDNA, cell-free DNA; LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; tSCLC, transformed SCLC; EGFR m, EGFR Mutant type; ROC, recipient working characteristic; AUROC, area under the recipient working characteristic curve.

[0101] Figure 17 The patient illustrations highlight the non-invasive testing methods using cfDNA epigenomic analysis. EGFR The ability of mLUAD patients to undergo small cell transformation. This was observed in two patients with biopsy-confirmed SCLC. EGFR Longitudinal assessment of the integrated epigenomic cfDNA SCLC risk score in patients with mLUAD. (Abbreviation: ) EGFR m, EGFR Mutant type; cfDNA, cell-free DNA; LUAD, lung adenocarcinoma; SCLC, small cell lung cancer.

[0102] Figure 18 Gene expression of ASCL1, NEUROD1, POU2F3, and YAP1 in SCLC PDX. Abbreviations: SCLC, Small Cell Lung Cancer; PDX, Patient-Derived Xenograft; FPKM, Number of Fragments per Kilobase.

[0103] Figure 19 Epigenomic datasets derived from lung cancer PDX. Abbreviations: PDX, patient-derived xenograft; LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; tSCLC, transformed SCLC.

[0104] Figure 20For lung adenocarcinoma (LUAD), transformed small cell lung cancer (SCLC) and Primary Unsupervised hierarchical clustering was performed on ATAC-seq (A), H3K27ac ChIP-seq (B), H3K4me3 ChIP-seq (C), H3K27me3 ChIP-seq (D), and MeDIP-seq (E) data of SCLC patient-derived xenografts (PDX).

[0105] Figure 21 The Venn diagram illustrates lung adenocarcinoma (LUAD), transformed small cell lung cancer (SCLC), and... Primary Overlap of peaks in H3K27ac ChIP-seq (A), H3K4me3 ChIP-seq (B), ATAC-seq (C), and MeDIP-seq (D) from SCLC patient-derived xenografts (PDX).

[0106] Figure 22 Differences in enrichment of (A) H3K27ac, (B) H3K4me3, (C) DNA methylation, and (D) number of open chromatin sites in xenografts from patients with lung adenocarcinoma (LUAD) or small cell lung cancer (SCLC) before and after the removal of peaks also present in white blood cells (WBCs).

[0107] Figure 23 The volcano plot illustrates the overlap of differentially expressed genes with log2 fold change between LUAD PDX and SCLC PDX with corresponding differentially expressed peaks in (A) H3K4me3 ChIP-seq and (B) ATAC-seq in xenografts derived from patients with lung adenocarcinoma (LUA; blue) and small cell lung cancer (SCLC; red). Multiple hypothesis testing was performed to correct for two-sided p-values ​​(FDR-corrected P < 0.05).

[0108] Figure 24 Epigenomic dataset generated from cfDNA plasma samples of patients with metastatic lung cancer. Abbreviations: cfDNA, cell-free DNA; LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; tSCLC, transformed SCLC; EGFR m, EGFR Mutant type.

[0109] Figure 25 From EGFRm Representative epigenomic data of tSCLC and EGFRm LUAD show INSM1 Distribution of H3K27ac and H3K4me3 signal intensities near (a neural lineage-defining gene). Gray bars represent the signal intensity distribution near (a neural lineage-defining gene). INSM1The Elite GeneHancer and the Elite GeneHancer-gene-associated most recent enhancer.

[0110] Figure 26 In healthy, cancer-free controls, metastatic patients... EGFR Patients with m-type lung adenocarcinoma (LUAD) and metastatic lung adenocarcinoma EGFRm H3K27ac signal at selected genes in representative cfDNA samples from patients with transformed small cell lung cancer (tSCLC). Samples from cancer patients were selected based on a high estimated tumor content in cfDNA from low-depth whole-genome sequencing data. EGFR 55% of m LUAD patients, and EGFR The prevalence of m tSCLC patients was 46%. Each trajectory depicted the signal intensity of a specified epigenetic marker in a given sample. Each sample was determined based on the sample's... GAPDH The peak signal intensity is scaled.

[0111] Figure 27 LUAD and SCLC cell lines were classified based on H3K27ac ChIP-seq data. (A) Dot plot shows the SCLC risk scores for LUAD (n=20) and SCLC (n=13) cell lines generated using a PDX-derived classifier stratified by molecular subtype. The table to the right of the plot shows the Mann-Whitney test p-values ​​for noteworthy comparisons. Receiver operating characteristic (ROC) curves show the area under the ROC curve (AUROC) for (B) LUAD versus all SCLC cell lines, and (C) LUAD versus SCLC-P, SCLC-A, and SCLC-N cell lines (excluding SCLC-Y cell line). Abbreviations: LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; Y, YAP1 P, POU2F3 A, ASCL1 N, NEUROD1 .

[0112] Figure 28 After removing peaks also present in leukocytes, the differentially enriched H3K27ac, DNA methylation, and number of base pairs covered by open chromatin sites were observed in xenografts (PDX) from patients with lung adenocarcinoma (LUAD) or small cell lung cancer (SCLC). Detailed Implementation

[0113] This disclosure is based, at least in part, on the evidence that the SCLC / LUAD status of a subject's lung cancer can be determined by detecting and quantifying the presence of histone modifications and / or DNA methylation at one or more genomic sites in cell-free DNA (cfDNA) from liquid biopsy samples (e.g., plasma samples obtained from or derived from a subject). This disclosure also covers methods for detecting chromatin accessibility and / or binding of one or more transcription factors at one or more genomic sites, rather than (or in addition to) histone modifications and / or DNA methylation. This disclosure is also based, at least in part, on the evidence that genomic sites differentially modified based on different types of histone modifications (e.g., histone methylation markers such as H3K4me3 and histone acetylation markers such as H3K27ac) and / or DNA methylation can be combined into multimodal classifiers to determine SCLC / LUAD status. These novel unimodal and multimodal classifiers provide minimally invasive methods for determining SCLC / LUAD status that are more accurate, objective, and comprehensive than current tissue-based methods. To date, no liquid biopsy platform has been able to provide an actionable solution for therapy-related transcriptional regulatory phenotypes such as SCLC / LUAD status.

[0114] SCLC / LUAD status and lung cancer Approximately 80% to 85% of lung cancers are non-small cell lung cancer (NSCLC). The major subtypes of NSCLC are adenocarcinoma (LUAD), squamous cell carcinoma (SCC), and large cell carcinoma (LCC). These subtypes originate from different types of lung cells and are grouped together as NSCLC because their treatment and prognosis are often similar. Some types of lung cancer can be further subdivided based on the oncogenes driving the cancer. For example, one type of LUAD is mEGFR (mutated epidermal growth factor receptor) LUAD, where mutations in the EGFR receptor lead to constitutive activation of the receptor, rather than activation only in the presence of an endogenous homologous ligand. Exemplary mutations include E19del and L858R.

[0115] Approximately 10% to 15% of all lung cancers are small cell lung cancer (SCLC), a highly malignant neuroendocrine tumor with a poor prognosis. Besides primary SCLC, there is also transformed SCLC, which shares similar pathological morphology, molecular characteristics, clinical presentation, and drug sensitivity. However, the pathogenesis and tumor microenvironment of primary and transformed SCLC differ. SCLC transformation is one of the mechanisms by which resistance to chemotherapy, immunotherapy, and targeted therapy develops in NSCLC. It typically occurs in epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma (LUAD) after treatment with tyrosine kinase inhibitors (TKIs) (Sequist et al., Sci Transl Med (2011) 3:75ra26). SCLC transformation can also occur in anaplastic lymphoma kinase (ALK)-positive lung cancer after treatment with ALK inhibitors, and in wild-type EGFR or ALK NSCLC treated with immunotherapy (Ferrer et al., J Thorac Oncol (2019) 14:130-134). Chemotherapy was previously used to treat transformed SCLC, but its prognosis was not ideal.

[0116] SCLC cancer can be treated with any SCLC cancer therapy, such as those disclosed in this article. LUAD cancer can be treated with any LUAD cancer therapy, such as those disclosed in this article.

[0117] SCLC cancer therapy Currently approved treatments for SCLC include chemotherapy and immunotherapy.

[0118] Chemotherapy Chemotherapy is often part of the treatment for small cell lung cancer (SCLC). This is because SCLC is usually discovered after it has spread, so other treatments such as surgery or radiation therapy cannot reach all areas of the cancer.

[0119] For subjects with limited-stage SCLC, chemotherapy is usually administered in conjunction with radiation therapy. This is known as chemoradiotherapy. For subjects with extensive-stage SCLC, chemotherapy (with or without immunotherapy) is usually the primary treatment. Radiation therapy is sometimes also administered. SCLC is typically treated with combinations of chemotherapy agents. The most commonly used combinations are cisplatin and etoposide, carboplatin and etoposide, cisplatin and irinotecan, or carboplatin and irinotecan. Topotecan and rubitidine are chemotherapy agents that can be used alone in subjects with metastatic SCLC, especially if the subject has already tried cisplatin or carboplatin.

[0120] Chemotherapy agents for lung cancer are usually administered intravenously, either by injection over a few minutes or by infusion over a longer period of time.

[0121] Healthcare professionals administer chemotherapy in cycles, with a rest period after each treatment session to allow subjects time to recover from the effects of the chemotherapy. Cycles are typically 3 or 4 weeks long, and the initial treatment usually consists of 4 to 6 cycles. The protocol varies depending on the chemotherapy agent used. For example, some chemotherapeutic agents are administered only on the first day of a chemotherapy cycle. Others are administered for several consecutive days or once a week. Then, at the end of the cycle, the chemotherapy protocol is repeated to begin the next cycle.

[0122] For advanced cancer, four to six cycles of initial chemotherapy are typically required, sometimes in combination with immunotherapy. In addition, for subjects who respond well to initial chemotherapy or whose cancer has not progressed, medical practitioners may recommend extending the course of a single immunotherapy session.

[0123] If cancer progresses (worsens) during treatment or recurs after treatment, alternative chemotherapy agents may be tried. The choice of chemotherapy agent depends to some extent on how quickly the cancer starts to grow again. The longer it takes for cancer to recur, the more likely it is to respond to further treatment. If cancer recurs more than 6 months after treatment, it may respond again to the same chemotherapy agent given initially. If cancer recurs quickly or continues to grow during treatment, further treatment with the same chemotherapy agent is unlikely to be effective. If further chemotherapy is given, most healthcare practitioners tend to use a single, different chemotherapy agent to help limit side effects. Topotecan and rubitidine are the most commonly used, but other chemotherapy agents may also be tried.

[0124] Immunotherapy A crucial component of the immune system is its ability to prevent itself from attacking normal cells in the body. To achieve this, it uses "checkpoints," or proteins, on immune cells that need to be turned on (or off) to trigger an immune response. Cancer cells sometimes use these checkpoints to evade the immune system's attack. Therapeutic agents targeting these checkpoints can be used to treat some patients with small cell lung cancer (SCLC).

[0125] Atezolizumab and durvalumab are exemplary checkpoint inhibitors that target PD-L1, a PD-1-related protein present on some tumor cells and immune cells. Camrelizumab is an exemplary checkpoint inhibitor that targets PD-1. Blocking these proteins helps enhance the immune response against cancer cells. These agents can be used as part of first-line treatment for advanced SCLC in combination with etoposide and platinum-based chemotherapy (e.g., carboplatin or cisplatin). Either agent can then be continued alone as maintenance therapy. The combination of PD-L1 immunotherapy and chemotherapy also appears to help some patients with SCLC live longer. These agents are typically administered intravenously (IV) every 2, 3, or 4 weeks.

[0126] Other SCLC cancer therapies While the above sections focus on FDA-approved SCLC cancer therapies, many other SCLC cancer therapies are being developed and / or evaluated in clinical trials (e.g., see Giunta et al., Front Med (Lausanne) (2022) 9:924853, the entire contents of which are incorporated herein by reference).

[0127] For example, poly-ADP-ribose polymerase (PARP) inhibitors (PARPi), such as olaparib, fluzoparib, and talazoparib, are approved for ovarian, prostate, and / or breast cancer and are currently being investigated in SCLC because they have the potential to enhance cytotoxic responses to chemotherapy, radiation, and immunotherapy (Barayan et al., J Thorac Dis (2020) 12:6240-6252). Exemplary combination therapies currently under clinical evaluation for first-line treatment with platinum-based chemotherapy (e.g., carboplatin or cisplatin) include durvalumab and olaparib. Combinations of camrelizumab and fluzoparib, and atezolizumab and talazoparib are being evaluated as maintenance therapy for SCLC. Combinations of durvalumab with the ATR inhibitor ceralasertib, and durvalumab with the Aurora kinase B inhibitor AZD2811, are also being investigated for maintenance therapy in SCLC.

[0128] Other novel immunomodulators under investigation may also be evaluated for their ability to enhance the effects of immune checkpoint inhibitors such as atezolizumab and durvalumab, which target PD-L1 and act by influencing specific immune targets, such as: LAG3 expressed on activated T cells and NK cells (Goldberg and Drake, Curr Top Microbiol Immunol (2011) 344:269-278); TIGIT upregulated by activated T cells and regulatory cells (Chauvin and Zarour, J Immunother Cancer (2020) 8:57); ILT4 expressed in myeloid cells (Gao et al., Biochim Biophys Acta Rev Cancer (2018) 1869:278-285); and CD27 involved in T cell proliferation and differentiation into memory cells and effector cells (Starzer and Berghoff, ESMO Open (2020) 4(S3):e000629).

[0129] Delta-like ligand 3 (DLL3) has become an attractive tumor-specific target, uniquely overexpressed on the cell surface of SCLC and other high-grade neuroendocrine carcinomas (NECs) (Saunders et al., Sci Transl Med (2015) 7:302ra136 and Rudin et al., J Hematol Oncol (2023) 16(1):66). Rovalpizumab-tecillin is an antibody-drug conjugate (ADC) comprising a DLL3-specific humanized monoclonal antibody (SC16) conjugated to a membrane-permeable pyrrolobenzodiazepine (PBD) dimer via a lysosomal protease-sensitive dipeptide linker (Saunders et al., Sci Transl Med (2015) 7:302ra136). Rovalpizumab-tecillin binds to DLL3 on the cell surface, leading to the internalization of the ADC-target complex via endocytosis. The valine-alanine linker of rovalpizumab-tecillin is subsequently cleaved by lysosomal-associated cathepsin B, releasing PBD into the cytoplasm. PBD then enters the nucleus, cross-links DNA, and induces tumor cell death through apoptosis. In some embodiments, DLL3-targeting therapeutic agents such as ADCs (e.g., rovalpizumab-tecillin) can be used to treat subjects identified as having cancer according to the methods of this disclosure, for example, subjects identified as having SCLC. In some embodiments, such methods may involve further steps, namely, detecting or quantifying according to the methods of this disclosure. DLL3The presence of H3K4me3 modification at the promoter, for example in plasma samples, such as at the genomic site chr19:39,988,452-39,990,287 (hg19) or one or more subregions thereof, for example via cfChIP-seq. In some embodiments, such methods include the step of administering a DLL3-targeting therapeutic agent (e.g., an ADC such as rovalpizumab-tecillin) to a subject. In some embodiments, this disclosure covers methods for detecting or quantifying... DLL3 The presence of H3K4me3 modification at the promoter, for example in plasma samples, such as at the genomic site chr19:39,988,452-39,990,287 (hg19) or one or more subregions thereof, such as via cfChIP-seq, in subjects who have not previously been diagnosed with SCLC according to the methods of this disclosure, for example, where the subject has been independently diagnosed with SCLC, or where the subject has a non-SCLC cancer, such as Merkel cell carcinoma, neuroendocrine prostate cancer (NEPC), or melanoma. In some embodiments, detection or quantification DLL3 H3K4me3 modifications at the promoter (e.g., in plasma samples, for example, at the genomic site chr19:39,988,452-39,990,287 (hg19) or one or more subregions thereof, e.g., via cfChIP-seq) can be used to select a DLL3-targeting therapeutic agent (e.g., an ADC such as rovalpizumab-tecillin) to treat such a subject. In some embodiments, such methods include the step of administering a DLL3-targeting therapeutic agent (e.g., an ADC such as rovalpizumab-tecillin) to the subject.

[0130] It should be understood that these other SCLC cancer therapies can also be used in the treatments disclosed herein.

[0131] LUAD Cancer Therapy Currently approved LUAD cancer therapies include chemotherapy, immunotherapy, and targeted therapy.

[0132] Chemotherapy Not all patients with non-small cell lung cancer (NSCLC), such as LUAD, will require chemotherapy. However, depending on the stage of the cancer and other factors, chemotherapy may be recommended in the following situations: Preoperative (neoadjuvant) chemotherapy (sometimes with radiation therapy) may be used to try to shrink the tumor so it can be removed with a smaller surgery. Postoperatively, (adjuvant) chemotherapy (sometimes with radiation therapy) may be used to try to kill any cancer cells that may remain or have spread but are not visible even on imaging tests. For locally advanced NSCLC (e.g., LUAD), chemotherapy, along with radiation therapy, is sometimes given as primary treatment for advanced cancer that has grown to nearby structures where surgery is not possible, or for patients who are not healthy enough to undergo surgery. For metastatic (stage IV) NSCLC (e.g., LUAD), chemotherapy may be given to lung cancer that has spread to areas outside the lungs, such as the bone, liver, or adrenal glands.

[0133] The most commonly used chemotherapy agents for NSCLC (e.g., LUAD) include cisplatin, carboplatin, paclitaxel, albumin-bound paclitaxel (nab-paclitaxel), docetaxel, gemcitabine, vinorelbine, etoposide, and pemetrexed. A combination of two chemotherapy agents is often used to treat early-stage lung cancer. If a combination is used, it typically includes cisplatin or carboplatin plus another chemotherapy agent. Sometimes, other combinations that do not contain these chemotherapy agents are used, such as gemcitabine with vinorelbine or paclitaxel.

[0134] Chemotherapy agents for lung cancer are usually administered intravenously, either by injection over a few minutes or by infusion over a longer period of time.

[0135] Healthcare professionals administer chemotherapy in cycles, with a rest period after each treatment session to allow subjects time to recover from the effects of the chemotherapy. Cycles are typically 3 or 4 weeks long, and the initial treatment usually consists of 4 to 6 cycles. The protocol varies depending on the chemotherapy agent used. For example, some chemotherapeutic agents are administered only on the first day of a chemotherapy cycle. Others are administered for several consecutive days or once a week. Then, at the end of the cycle, the chemotherapy protocol is repeated to begin the next cycle.

[0136] Adjuvant and neoadjuvant chemotherapy are typically administered for 3 to 4 months, depending on the chemotherapy agents used. The duration of treatment for advanced lung cancer is based on the treatment's efficacy in the subjects discussed.

[0137] For advanced cancer, initial chemotherapy is typically administered for 4 to 6 cycles. Some medical practitioners now suggest that for subjects who respond well to initial chemotherapy or whose cancer has not progressed, a single chemotherapy session or targeted therapy can be added. Continuing this treatment (called maintenance therapy) appears to help control the cancer and has helped some subjects live longer.

[0138] If initial chemotherapy is no longer effective for advanced lung cancer, medical practitioners may recommend using a single chemotherapy agent (such as docetaxel or pemetrexed) or second-line treatment with immunotherapy or targeted therapy.

[0139] Immunotherapy A crucial component of the immune system is its ability to prevent itself from attacking normal cells in the body. To achieve this, it uses "checkpoints," or proteins, on immune cells that need to be turned on (or off) to trigger an immune response. Cancer cells sometimes use these checkpoints to evade the immune system's attack. Therapeutic agents targeting these checkpoints can be used to treat some patients with non-small cell lung cancer (NSCLC, e.g., LUAD).

[0140] PD-1 and PD-L1 inhibitors Nivolumab, pembrolizumab, and cemiplimab target PD-1, a protein on T cells that normally helps prevent these cells from attacking other cells in the body. These therapeutic agents enhance the immune response against cancer cells by blocking PD-1. This can shrink some tumors or slow their growth.

[0141] Atezolizumab and durvalumab target PD-L1, a protein associated with PD-1 that is present on some tumor cells and immune cells. Blocking this protein helps enhance the immune response against cancer cells. This can shrink some tumors or slow their growth.

[0142] These immunotherapies can be used to treat NSCLC, such as LUAD, in various situations. In some cases, laboratory testing of cancer cells may be required before one of these treatments can be used to demonstrate that they contain at least a certain amount of PD-L1 protein.

[0143] For some patients with early-stage NSCLC, such as LUAD, nivolumab can be used in combination with chemotherapy as first-line treatment before surgery (called neoadjuvant therapy).

[0144] Pembrolizumab, atezolizumab, or cimiprimab (sometimes in combination with chemotherapy) may be used as part of the first-line treatment for some patients with metastatic NSCLC (e.g., LUAD).

[0145] For some patients with metastatic NSCLC (e.g., LUAD), nivolumab may be administered as part of first-line treatment, in combination with the CTLA-4 inhibitor ipilimumab, as described below. Similarly, durvalumab may be given in combination with the CTLA-4 inhibitor tremelimumab. Chemotherapy is often also given in conjunction with these treatments.

[0146] Nivolumab, pembrolizumab, and atezolizumab can also be used in subjects with certain types of advanced NSCLC, such as LUAD, or in patients whose cancer begins to regrow after chemotherapy or other treatments.

[0147] For subjects with stage III NSCLC, such as LUAD patients who are ineligible for surgery or radiotherapy, pembrolizumab or cimiprimab can be given as first-line treatment.

[0148] Durvalumab can be used in patients with stage III NSCLC, such as LUAD patients whose cancer cannot be surgically removed and who have not progressed after radiochemotherapy (chemoradiotherapy). The goal of using this treatment (also known as consolidation therapy) is to prevent cancer progression for as long as possible.

[0149] For some patients with early-stage NSCLC, such as those with LUAD who have undergone surgery followed by chemotherapy, atezolizumab or pembrolizumab can be used. This is known as adjuvant therapy.

[0150] All of these therapeutic agents are administered via intravenous (IV) infusion. Depending on the agent, they may be administered every 2, 3, 4, or 6 weeks.

[0151] CTLA-4 inhibitors Ipilimumab and trimemumab are also immunotherapies that enhance the immune response, but they block CTLA-4, another protein on T cells that typically helps control T cells. These agents are used in conjunction with PD-1 inhibitors (ippilimumab with nivolumab, and trimemumab with durvalumab); they cannot be used alone. For certain types of advanced NSCLC (e.g., LUAD), they may be used as part of first-line therapy, often in conjunction with chemotherapy.

[0152] These treatments are administered via intravenous (IV) infusion, typically every 3 or 6 weeks.

[0153] Targeted therapy As researchers learn more about the changes in non-small cell lung cancer (NSCLC)—such as the LUAD cells that help it grow—they have developed therapeutics specifically targeting these changes. Targeted therapies work differently from standard chemotherapy. They can sometimes be effective when chemotherapy fails, and their side effects are often different. Currently, targeted therapies are most commonly used for advanced lung cancer, either in conjunction with chemotherapy or alone.

[0154] Therapeutic agents targeting tumor angiogenesis (angiogenesis) For a tumor to grow, it needs to form new blood vessels to obtain nutrients. This process is called angiogenesis. Some targeted therapies, known as angiogenesis inhibitors, prevent the growth of these new blood vessels. Bevacizumab (angiogenic) is used to treat advanced NSCLC, such as LUAD. It is an antibody that targets vascular endothelial growth factor (VEGF), a protein that helps form new blood vessels. This treatment is usually used in conjunction with chemotherapy for a period of time. Then, if the cancer responds, chemotherapy can be stopped, and bevacizumab can be given alone until the cancer starts growing again.

[0155] Ramucirumab can also be used to treat advanced NSCLC, such as LUAD. This therapeutic agent is an antibody that targets the VEGF receptor. It helps prevent the formation of new blood vessels. This therapeutic agent is often used in combination with chemotherapy, usually after another treatment has failed.

[0156] For cancer cells have certain EGFR For subjects with gene mutations, either of these two treatments can be used as first-line therapy in conjunction with the targeted therapy erlotinib (see below).

[0157] Therapeutic agents targeting cells with KRAS gene alterations Some NSCLCs, such as LUAD, have KRAS A genetic change leads to the production of an abnormal form of the KRAS protein. This abnormal protein contributes to the growth and spread of cancer cells.

[0158] Approximately one in eight (13%) patients with NSCLC, such as LUAD, have a condition called... KRAS Specific types of G12C mutations KRAS Genetic alteration. NSCLC with this mutation (e.g., LUAD) is often resistant to other targeted therapies, such as EGFR inhibitors (see below).

[0159] Sotorasib and adagrasib are therapeutic agents known as KRAS inhibitors. Their mechanism of action is to attach to the KRAS G12C protein, thereby inhibiting cancer cell growth. If a subject has advanced NSCLC (e.g., LUAD) and cancer cells are found to have… KRAS If there is a G12C mutation, one of these treatments may be effective.

[0160] These treatments are administered in tablet form, usually once or twice a day.

[0161] Therapeutic agents targeting cells with EGFR gene alterations Epidermal growth factor receptor (EGFR) is a protein on the surface of cells. It normally helps cells grow and divide. Sometimes, NSCLC (e.g., LUAD) cells have high levels of overactive EGFR, leading to accelerated growth. Therapeutic agents called EGFR inhibitors can block cell growth signals from EGFR. Some of these therapeutic agents are used to treat NSCLC, such as LUAD.

[0162] For the treatment of having EGFR For NSCLC with gene mutations, such as LUAD, EGFR inhibitors include erlotinib, afatinib, gefitinib, osimertinib, and dacomitinib.

[0163] For advanced NSCLC, such as LUAD, one of these treatments is often used as a treatment for EGFR Erlotinib is the first-line treatment for advanced NSCLC (e.g., LUAD) with certain mutations in the gene. While most of these treatments are used alone, erlotinib can also be used in conjunction with targeted therapies that affect angiogenesis (see above).

[0164] For early-stage NSCLC, such as LUAD, osimertinib can also be used as adjuvant (additional) therapy after surgery for some patients with certain... EGFR Early-stage lung cancer caused by gene mutations.

[0165] All of these treatments are administered in tablet form.

[0166] A subset of EGFR inhibitors can be used to target cells with the T790M mutation. EGFR inhibitors can typically shrink tumors for months or longer. However, these treatments eventually fail for most subjects, usually because the cancer cells have already shrunk. EGFR Another mutation has occurred in the gene. One such mutation is called T790M. Osimertinib is an EGFR inhibitor that is generally effective against cells with the T790M mutation.

[0167] A subset of EGFR inhibitors can be used to target cells with exon 20 mutations. While the EGFR inhibitors listed above can help many cancer cells with... EGFR Subjects with gene mutations, but they cannot help everyone. For example, those with... EGFR Cancer cells with genetic alterations (called exon 20 insertion mutations) are unlikely to be affected by these therapeutic agents. However, other therapeutic agents are currently available that target cancer cells with exon 20 mutations. Amivantamab is a bispecific antibody that targets two proteins that help cancer cells grow: EGFR and MET. This therapeutic agent is administered via intravenous infusion. Mobotinib is a therapeutic agent that targets the EGFR protein in a slightly different way. This therapeutic agent is administered in tablet form, usually once a day. These therapeutic agents can be used to treat advanced NSCLC (e.g., LUAD), when cancer cells have exon 20 mutations, often after chemotherapy has been attempted.

[0168] Therapeutic agents targeting cells with ALK gene alterations Approximately 5% of NSCLCs (e.g., LUAD) are classified as... ALK The genes contain rearrangements. This change is common in non-smokers (or light smokers) who are younger and have an adenocarcinoma subtype of NSCLC. Right now Subjects of LUAD). ALK Gene rearrangements produce abnormal ALK proteins, leading to cell growth and spread. Therapeutic agents targeting abnormal ALK proteins include crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib. These agents can often shrink tumors in patients with advanced lung cancer exhibiting ALK gene alterations. While they can be helpful after chemotherapy fails, they are not ideal for treating cancer with specific genetic abnormalities. ALK Subjects with gene rearrangements are often used as an alternative to chemotherapy. These treatments are administered in the form of pills.

[0169] Therapeutic agents targeting cells with ROS1 gene alterations Approximately 1% to 2% of NSCLCs (e.g., LUAD) are classified as... ROS1 The genes contain rearrangements. This change is most common in patients with the adenocarcinoma subtype of NSCLC (non-small cell lung cancer). Right now ,LUAD) and tumor ALK , KRAS and EGFR Subjects who were all negative for mutations. ROS1 Gene rearrangements are similar to ALK gene rearrangements, and some therapeutic agents can work on cells with ALK or ROS1 gene alterations. Therapeutic agents targeting the abnormal ROS1 protein include crizotinib, ceritinib, lorlatinib, lorbrena, and entrectinib. For patients with... ROS1 In patients with advanced lung cancer due to genetic alterations, these treatments can often shrink the tumor. Crizotinib or ceritinib can be used as first-line therapy in place of chemotherapy; and lorlatinib can be used when crizotinib or ceritinib fails. Entrectinib can be used for metastatic NSCLC, for example, with... ROS1 Subjects with genetically modified LUAD. These treatments are administered in tablet form.

[0170] Therapeutic agents targeting cells with BRAF gene alterations In some NSCLCs (e.g., LUAD), cells BRAF Genetic changes have occurred. Cells with these changes produce an altered BRAF protein, which aids in their growth. Dabrafenib is a therapeutic agent known as a BRAF inhibitor that directly attacks the BRAF protein. Trametinib is known as a MEK inhibitor because it attacks the associated MEK protein. If a certain type of... BRAF If there are genetic changes, these treatments can be used together to treat metastatic NSCLC, such as LUAD. These treatments are administered daily in tablet or capsule form.

[0171] Therapeutic agents targeting cells with RET gene alterations In a few NSCLCs (e.g., LUAD), the cells RET Certain genetic changes have caused them to produce an abnormal form of the RET protein. This abnormal protein contributes to cell growth. Sepatinib and pralatinib are therapeutic agents known as RET inhibitors. Their mechanism of action is to attack the RET protein. If cancer cells have certain types of... RET If there are genetic alterations, these treatments can be used to treat advanced NSCLC, such as LUAD. These treatments are administered orally in capsule form, usually once or twice a day.

[0172] Therapeutic agents targeting cells with MET gene alterations For some NSCLC, such as LUAD, the cells MET A genetic change leads to the production of an abnormal form of the MET protein. This abnormal protein contributes to cell growth and spread.

[0173] Carmatinib and tepoltinib are therapeutic agents known as MET inhibitors. Their mechanism of action is to attack the MET protein. If cancer cells possess certain types of... MET If there are genetic alterations, these therapeutic agents can be used to treat metastatic NSCLC, such as LUAD. Carmatinib is administered in tablet form, usually twice a day. Tepoltinib is also administered in tablet form, but usually once a day.

[0174] Therapeutic agents targeting cells with HER2 gene alterations In a small number of NSCLC cases (e.g., LUAD), cancer cells... HER2 Certain changes have occurred in the genes, which facilitate their growth. Trastuzumab deruxtecan is an antibody-drug conjugate (ADC). It consists of an antibody (trastuzumab) that targets the HER2 protein and is linked to a chemotherapy agent (drutecan). The antibody acts like a homing signal, delivering chemotherapy directly to the cancer cells by attaching to the HER2 protein. This therapeutic agent can be used to treat NSCLC that is unresectable or has spread, such as LUAD, provided that the cancer cells have certain types of... HER2 The patient has a genetic mutation and has already tried at least one other treatment. This treatment is administered intravenously (IV). It is usually given once every 3 weeks.

[0175] Therapeutic agents targeting cells with NTRK gene alterations A very small number of NSCLCs (e.g., LUAD) are in NTRK One of the genes has a change. Cells with these gene changes may lead to abnormal cell growth and cancer. Larotrectinib and entrectinib target and... NTRK The protein produced by the gene is ineffective. This is relevant for patients with advanced lung cancer that is still growing despite other treatments, and for tumors with... NTRK These therapeutic agents can be used by subjects with genetic alterations. These agents are administered in tablet form, once or twice a day.

[0176] Other LUAD cancer therapies While the preceding sections have focused on FDA-approved LUAD cancer therapies, many other LUAD cancer therapies are being developed and / or evaluated in clinical trials (e.g., see Guo et al., Front Oncol (2022) 12:945102, the entire contents of which are incorporated herein by reference). It should be understood that these other LUAD cancer therapies may also be used in conjunction with the treatments described in this disclosure.

[0177] Subjects and samples The samples used in the methods, kits, and systems analyses provided herein can be any biological sample, including any processed sample containing circulating tumor DNA (ctDNA) derived from a biological sample. In various embodiments, the samples used in the methods, kits, and systems analyses provided herein can be samples obtained from mammalian subjects. In various embodiments, the samples used in the methods, kits, and systems analyses provided herein can be samples obtained from human subjects.

[0178] In various cases, a human subject is someone who has been diagnosed with or is seeking a diagnosis of lung cancer (e.g., SCLC), someone who has been diagnosed with or is seeking a diagnosis of being at risk of developing lung cancer, and / or someone who has been diagnosed with or is seeking a diagnosis of being at direct risk of developing lung cancer, etc. In various cases, a human subject is someone identified as requiring SCLC / LUAD status screening. In some cases, a human subject is someone identified by a medical practitioner as requiring SCLC / LUAD status screening.

[0179] The subject may not have previously received cancer treatment, such as that described in this disclosure. In other embodiments, the subject has previously received cancer treatment, such as that described in this disclosure.

[0180] In various implementations, the subject possesses one or more cancer biomarkers and / or risk factors (e.g., lung cancer, SCLC, etc.). In some implementations, the requirement for SCLC / LUAD status screening is determined based on an initial cancer diagnosis (e.g., lung cancer diagnosis). In all cases, a human subject refers to a subject who has not been diagnosed with cancer (e.g., lung cancer), has no risk of developing cancer, has no direct risk of developing cancer, has not been diagnosed with cancer, and / or is not seeking a cancer diagnosis.

[0181] In various embodiments, samples from a subject (e.g., a person) can be obtained from a liquid biopsy. In some embodiments, the sample and / or reference is obtained from serum, plasma, or urine. In some embodiments, the sample is serum. In some embodiments, the sample contains circulating tumor DNA (ctDNA). In some embodiments, the sample is derived from about 1 mL of blood obtained from the subject. In some embodiments, the sample is derived from about 0.5–5 mL of blood obtained from the subject, for example, about 0.5 to about 2 mL, about 0.5 to 1.75 mL, about 0.5 to 1.5 mL, about 0.75 to 1.25 mL, about 0.9 to 1.1 mL, about 1 mL, about 2 mL, about 3 mL, about 4 mL, or about 5 mL of blood.

[0182] In various implementations, the sample is a cell-free DNA (cfDNA) sample. cfDNA typically exists in human biological fluids (e.g., plasma, serum, or urine) as short double-stranded fragments. cfDNA concentrations are usually low, but can increase significantly under certain conditions, including but not limited to pregnancy, autoimmune diseases, myocardial infarction, and cancer. Circulating tumor DNA (ctDNA) is a component of cell-free DNA specifically derived from cancer cells. ctDNA may or may not be present in human biological fluids and may bind to leukocytes and erythrocytes. Various tests for detecting tumor-derived ctDNA are based on detecting genetic or epigenetic modifications of cancer characteristics (e.g., features of the associated cancer). Genetic or epigenetic characteristics of cancer include, but are not limited to, oncogenetic or cancer-related mutations in tumor suppressor genes, activated oncogenes, chromosomal abnormalities, histone modifications (e.g., histone methylation and / or histone acetylation), chromatin accessibility, binding to one or more transcription factors, and / or DNA methylation.

[0183] In various implementations, ctDNA accounts for less than 30%, less than 20%, or less than 10% of cfDNA in the liquid biopsy sample obtained from the subject, for example, less than 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, or less than 1% of cfDNA in the sample. In some implementations, the percentage of ctDNA in the liquid biopsy sample is assessed using ichorCNA, which estimates the percentage of ctDNA in the sample in a probabilistic manner (see Adalsteinsson et al., Nat Commun (2017) 8(1):1324, the entire contents of which are incorporated herein by reference).

[0184] cfDNA and ctDNA can provide real-time or near-real-time indicators of the state of the source tissue. The half-life of cfDNA and ctDNA in blood is approximately 2 hours, therefore samples collected at a given time reflect the state of the source tissue relatively promptly.

[0185] In some embodiments, the method includes isolating DNA (e.g., cfDNA) from a liquid biopsy sample. Various methods for isolating nucleic acids from a sample are known in the art (e.g., isolating cfDNA from blood or plasma). Nucleic acids can be isolated using, but not limited to, standard DNA purification techniques via direct gene capture (e.g., by clarifying the sample to remove assay inhibitors, and, if the target nucleic acid is present, capturing the target nucleic acid from the clarified sample with a capture agent to generate a capture complex, and separating the capture complex to recover the target nucleic acid).

[0186] Reagents and protocols for obtaining and analyzing cfDNA and ctDNA (such as circulating cfDNA and ctDNA in blood or other tissues) are commercially available, as described in the examples, and are well known in the art (see, for example, Anker et al., Cancer and Metastasis Rev (1999) 18:65-73; Wua et al., Clin Chim Acta (2002) 321:77-87; Fiegel et al., Cancer Res (2005) 15:1141-1145; Pathak et al., Clin Chem (2006) 52:1833-1842; Schwarzenbach et al., Clin Cancer Res (2009) 15:1032-1038; Schwarzenbach et al., Nat Rev Cancer (2011) 11:426-437, the contents of each of which are incorporated herein by reference in their entirety).

[0187] In various implementations, samples can be repeatedly collected from individuals over a period of time (e.g., daily, weekly, monthly, annually, semi-annually, etc.). In various implementations, such samples can be used to validate early detection results and / or identify changes in biological patterns, such as due to disease progression, resistance to therapy, treatment, remission, etc. For example, according to this disclosure, subject samples can be collected and monitored monthly, every two months, or in combinations of one, two, or three-month intervals. In various implementations, samples can be collected from or at certain clinically determined stages (such as resistance to therapy, before radiological progression, after radiological progression, and / or tissue biopsy) for monitoring over a period of time. Furthermore, SCLC / LUAD status obtained at different time points can be conveniently compared with each other and with the status of normal controls during the monitoring period, thus providing the subject's own values ​​as internal or personal controls for long-term monitoring.

[0188] The samples include materials prepared by processes including, but not limited to, the following steps: concentration, dilution, pH adjustment, removal of high-abundance peptides (e.g., albumin, gamma globulin, and transferrin), addition of preservatives, addition of calibrators, addition of protease inhibitors, addition of denaturants, desalting, concentration, and / or extraction of sample nucleic acids, and / or amplification of sample nucleic acids (e.g., by PCR or other nucleic acid amplification techniques). The samples also include materials prepared by techniques for isolating, for example, nucleosomes or transcription factors and / or nucleic acids associated with nucleosomes or transcription factors.

[0189] Proteins unsuitable for the relevant purpose or background (e.g., high-abundance, non-informative, or undetectable proteins) can be removed from samples using high-affinity reagents, high-molecular-weight filters, ultracentrifugation, and / or electrodialysis. High-affinity reagents include antibodies or other reagents (e.g., aptamers) that selectively bind to high-abundance proteins. Sample preparation may also include ion-exchange chromatography, metal ion affinity chromatography, gel filtration, hydrophobic chromatography, chromatographic focusing, adsorption chromatography, isoelectric focusing, and related techniques. Molecular-weight filters include membranes that separate molecules based on size and molecular weight. Such filters can be further employed with reverse osmosis, nanofiltration, ultrafiltration, and microfiltration. Ultracentrifugation involves centrifuging the sample at approximately 15,000–60,000 rpm while monitoring particle settling (or non-settling) using an optical system. Electrodialysis is a procedure that uses electroporation or semipermeable membranes, involving the transfer of ions from one solution to another under the influence of a potential gradient. Because the membranes used in electrodialysis can selectively transport positively or negatively charged ions, repel ions with opposite charges, or allow substances to migrate through a semipermeable membrane based on size and charge, electrodialysis can be used for the concentration, removal, or separation of electrolytes.

[0190] The separation and purification methods disclosed herein may include any procedures known in the art, such as capillary electrophoresis (e.g., in a capillary or on a chip) or chromatography (e.g., in a capillary, column, or on a chip). Electrophoresis is a method that can be used to separate ionic molecules under the influence of an electric field. Electrophoresis can be performed in microchannels on a gel, capillary, or chip. Examples of gels used for electrophoresis include starch, acrylamide, polyethylene oxide, agarose, or combinations thereof. Gels can be modified by cross-linking, adding detergents or denaturing agents, immobilizing enzymes or antibodies (affinity electrophoresis) or substrates (zymography), and introducing pH gradients. Examples of capillaries used for electrophoresis include capillaries with electrospray interfaces.

[0191] Capillary electrophoresis (CE) is preferably used to separate complex hydrophilic molecules and highly charged solutes. CE technology can also be applied to microfluidic chips. Depending on the type of capillary and buffer used, CE can be further subdivided into separation techniques such as capillary zone electrophoresis (CZE), capillary isoelectric focusing (CIEF), capillary isovelocity electrophoresis (CITP), and capillary electrochromatography (CEC). One embodiment of coupling CE technology with electrospray ionization involves using a volatile solution, for example, an aqueous mixture containing volatile acids and / or bases and organic matter such as alcohols or acetonitrile.

[0192] Capillary isotachophoresis (CITP) is a technique in which analytes move through a capillary at a constant velocity but are still separated by their respective mobilities. Capillary zone electrophoresis (CZE), also known as free solution electrophoresis (FSCE), is based on the differences in electrophoretic mobilities of analytes, which depend on the analyte charge and the frictional resistance encountered during migration; this frictional resistance is typically proportional to the size of the analyte. Capillary isoelectric focusing (CIEF) allows weakly ionizable amphoteric molecules to be separated by electrophoresis over a pH gradient. CEC is a hybrid technique combining traditional high-performance liquid chromatography (HPLC) and capillary electrophoresis (CE).

[0193] The separation and purification techniques used in this disclosure may include any chromatographic procedure known in the art. Chromatography may be based on the differential adsorption and elution of certain analytes, or on the partition of the analyte between the mobile and stationary phases. Different examples of chromatography include, but are not limited to, liquid chromatography (LC), gas chromatography (GC), high-performance liquid chromatography (HPLC), etc.

[0194] In some implementations, whole blood is collected from the subject, and the plasma layer is separated by centrifugation. cfDNA can then be extracted from the plasma using methods known in the art.

[0195] Histone modification, chromatin accessibility and transcription factor binding Histone methylation is thought to increase or decrease the expression of related coding sequences, depending on which histone residues are methylated. Histone methylation is a necessary modification that leads to monomethylation (me1), dimethylation (me2), and trimethylation (me3) of several amino acids, directly affecting heterochromatin formation, gene imprinting, X chromosome inactivation, and gene transcription regulation. Histone methyltransferases promote monomethylation, dimethylation, or trimethylation of histones, while histone demethylases promote demethylation. Generally, lysine (Lys or K), arginine (Arg or R), and the rare histidine (His or H) are the most common histone methyl receptors. Histone methylation occurs only at specific lysine and arginine sites in histones H3 and H4. In histone H3, lysines 4, 9, 26, 27, 36, 56, and 79, and arginines 2, 8, and 17 can be methylated. In contrast, histone H4 has fewer methylation sites, with only lysines 5, 12, and 20, and arginine 3, capable of methylation. Histone methylation is generally associated with the activation or repression of transcription in downstream genes. Methylation of histones H3K4, R8, R17, K26, K36, K79, H4R3, and K12 can activate gene transcription. However, methylation of histones H3K9, K27, K56, H4K5, and K20 can repress gene transcription. For example, H3K4 methylation typically activates gene expression, while H3K27 methylation typically represses it.

[0196] Histone acetylation primarily occurs on lysine residues and is generally thought to increase the expression of related coding sequences. While not wanting to be bound by any theory, it is believed that acetylation of lysine residues neutralizes the positive charge of lysine, thus distancing histones from negatively charged DNA. The released structure facilitates the involvement of transcriptional mechanisms such as transcription factors and RNA polymerase II. Histone acetylation and deacetylation are typically catalyzed by histone acetyltransferases (HAT) and HDAC, respectively. Acetyl-CoA is both the source and a cofactor of acetylation. In regulatory regions, HAT can acetylate histones and recruit HAT-containing complexes to activate transcription. For example, H3K9ac and H3K27ac levels may be associated with promoter and enhancer activity. Furthermore, H3K27ac not only enhances the kinetics of transcriptional activation but also accelerates the transition of RNA polymerase II from the initiation to the elongation state.

[0197] Differential modifications at genomic sites (e.g., differences in histone methylation and / or histone acetylation) can refer to, be determined by, or detect as differences or changes in the modification status of one or more genomic sites between a first sample, disease, illness, or state and a second or reference sample, disease, illness, or state. Those skilled in the art will understand that a reference is typically generated by measuring using the same, similar, or comparable method as the non-reference measurement being compared.

[0198] Chromatin accessibility refers to the degree of physical contact between nuclear macromolecules and DNA, and depends in part on the occupancy and modification state of nucleosomes. Modified histones can regulate chromatin accessibility through various mechanisms, such as altering transcription factor (TF) binding through steric hindrance and modulating nucleosome affinity for active chromatin remodelers. The topological organization of nucleosomes in the genome is non-uniform: histones can be densely packed in both facultative and constitutive heterochromatin, and can be consumed at regulatory sites, including enhancers, insulators, and transcriptomes. Active regulatory elements of the genome are generally accessible.

[0199] Differences in accessibility to genomic loci can refer to, or be determined by, or detect by, a comparative difference or change in the modification status of one or more genomic loci between a first sample, disease, condition, or state and a second or reference sample, disease, condition, or state. Those skilled in the art will understand that a reference is typically generated by measuring using the same, similar, or comparable method as the non-reference measurement being compared.

[0200] Reference values ​​can be predetermined values ​​or a set of values, or values ​​or a set of values ​​derived from one or a set of samples. A reference can be one or a set of samples. Reference values ​​can be predetermined thresholds (values ​​that vary depending on circumstances (e.g., based on patient subgroups, age, weight, or other variables)) or ratios. Reference ratios can be ratios related to modifications and / or accessibility at multiple sites within, across, or between individual samples and / or references. In various embodiments, references can have or represent a normal, non-disease state. In some embodiments, such as for disease staging or for assessing treatment efficacy, references can have or represent a disease state, such as lung cancer, lung cancer stage, or lung cancer subtype, such as SCLC or LUAD cancer. In some embodiments, references can be based on IHC testing to represent SCLC cancer. In some embodiments, references can be based on IHC testing to represent LUAD cancer. In some embodiments, references can correspond to a subject with lung cancer and / or a lung cancer subtype, such as SCLC or LUAD cancer.

[0201] In some embodiments, the reference is a predetermined threshold. In some embodiments, the predetermined threshold has been previously demonstrated to distinguish between LUAD and SCLC subjects (e.g., by an AUROC greater than 0.5). In some embodiments, the reference is a measurement from a liquid biopsy sample. In some embodiments, the reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects. In some embodiments, the reference is a normalized sample. In some embodiments, the reference is a measurement obtained from a liquid biopsy sample obtained from a cohort of subjects previously diagnosed with lung cancer (including, for example, LUAD and / or SCLC).

[0202] In some cases, the reference is a non-contemporary sample from the same source, such as a previous sample from the same source, or a sample from the same subject. In some cases, the reference for the modification status of one or more genomic sites (e.g., one or more differentially modified genomic sites) can be the modification status of a sample (e.g., a sample from a subject) or multiple samples of one or more genomic sites (e.g., one or more differentially modified genomic sites) known to represent a specific state (e.g., SCLC cancer or LUAD cancer). In some cases, the reference for the accessibility status of one or more genomic sites (e.g., one or more differentially accessible genomic sites) can be the accessibility status of a sample (e.g., a sample from a subject) or multiple samples of one or more genomic sites (e.g., one or more differentially accessible genomic sites) known to represent a specific state (e.g., SCLC cancer or LUAD cancer).

[0203] In some exemplary but non-limiting embodiments of this disclosure, difference modification or difference accessibility may refer to a difference (e.g., the difference between a sample and a reference) in which the absolute log2 (fold change) is greater than or equal to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0 or higher, or in any range (including extreme values) between the two, such as that measured as provided herein.

[0204] Enhancers are genomic sites that can undergo differential modification or exhibit differential accessibility in different diseases, conditions, and other states. Enhancers are cis-acting DNA regulatory regions that are thought to bind to trans-acting proteins, thereby influencing the expression patterns of related genes. Chromium immunoprecipitation sequencing (ChIP-seq) of histone modifications (e.g., acetylation) has identified millions of enhancers in the mammalian genome. The number of active enhancers in any given cell type is estimated to be in the tens of thousands. Certain transcription factors (TFs), sometimes referred to as “master” transcription factors, are associated with active enhancers and have significant effects on gene expression and cellular function. Some of these transcription factors preferentially associate with enhancers that regulate genes required to establish cellular identity and function, including enhancer domains known as “superenhancers.” Furthermore, master TFs can participate in interconnected self-regulating circuits or “cliques” that are self-enhancing, exhibit significant cell selectivity, and play a role in maintaining cell state and / or cell survival.

[0205] Techniques for detecting and quantifying histone modifications and transcription factor binding Various molecular biology techniques are well known in the art and / or disclosed in this application for the detection and quantification of histone modifications and / or transcription factor binding. In some embodiments, the methods, kits, and systems disclosed herein relate to the detection and quantification of histone modifications and / or transcription factor binding in samples (e.g., in liquid biopsy samples containing cfDNA, such as plasma samples containing cfDNA). Chromatin immunoprecipitation (ChIP) is a technique in molecular biology that can be used to detect and quantify histone modifications and transcription factor binding in samples. CUT&RUN or CUT&Tag are other, more recent techniques that can also be used to detect and quantify histone modifications and transcription factor binding sites.

[0206] ChIP can involve multiple steps, including one or more of fixation, sonication, immunoprecipitation, and analysis of the immunoprecipitated DNA. ChIP has become a widely used tissue-based technique for determining the in vivo locations of various transcription factors and histone binding sites. Because proteins are captured at their DNA-binding sites, ChIP facilitates the detection of DNA-protein interactions occurring in living cells. More importantly, ChIP can be coupled with many commonly used molecular biology techniques such as PCR and real-time PCR, single-strand conformation polymorphism PCR, Southern blot analysis, Western blot analysis, cloning, and microarrays. This resulting versatility enhances the potential of this technique.

[0207] ChIP of tissue samples typically involves cross-linking chromatin-binding proteins with formaldehyde, followed by sonication or nuclease treatment to obtain small DNA fragments. Immunoprecipitation can then be performed using specific antibodies against the DNA-binding proteins of interest. The DNA can then be released from the proteins and analyzed using various methods. ChIP is also used to study RNA-protein interactions. X-ChIP uses sonication to break down fixed chromatin, while N-ChIP uses native chromatin, which may not be fixed, and performs nuclease digestion.

[0208] The first step in this technology can be cross-linking DNA and proteins. Formaldehyde is one of the most commonly used cross-linking agents. One advantage of using formaldehyde is the ease of reversibility of the cross-linking and its ability to form bonds spanning approximately 2 angstroms. This means that formaldehyde can bind molecules tightly together. Typically, formaldehyde can be added to the culture medium in cell culture flasks or cell culture plates. It enters the cells through the cell membrane and cross-links proteins with chromatin. Formaldehyde is also used for fixing tumor tissue. Other cross-linking agents that have been used include chemicals such as methylene blue and acridine orange, cisplatin, dimethylarsenic acid, potassium chromate, and ultraviolet (UV) light and lasers.

[0209] The harvested chromatin can be subjected to one or more sonication cycles. This typically breaks down DNA into 100-500 bp fragments to precisely pinpoint the location of the DNA sequence of interest. An alternative to sonication is nuclease digestion of the chromatin, such as in the N-ChIP method. Chromatin purification can be achieved using cesium chloride (CsCl) gradient centrifugation.

[0210] Chromatin can be enriched by targeting histone modifications using agents that bind to specific histone modifications (e.g., immunoprecipitation using one or more antibodies that bind to target epitopes).

[0211] For example, antibodies used in ChIP can selectively bind to specific transcription factors or one or more specific histone modifications, such as one or more specific histone acetylation or histone methylation modifications. In some embodiments, the antibody used to bind to the target epitope can be a "pan-" antibody (e.g., a pan-acetylation antibody, a pan-methylation antibody, an antibody that binds to a set of histone modifications associated with increased transcriptional activation, and / or an antibody that binds to a set of histone modifications associated with increased transcriptional repression). An antibody targeting the protein of interest is bound to a protein-DNA complex, and the complex is then precipitated. Commonly used immunoprecipitants for separating antigen-antibody complexes from lysates include salmon sperm DNA-protein A-Sepharose®, protein G, magnetic beads, and other engineered immunoprecipitation systems known to those skilled in the art.

[0212] Immunoprecipitated DNA can be eluted. Once the DNA of interest is isolated, various detection and quantification methods can be used to study the isolated gene fragments. Commonly used methods include PCR, real-time PCR, groove blot hybridization, microarray technology, and deep sequencing or next-generation sequencing. ChIP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify binding sites of DNA-related proteins. ChIP-seq can be used to map DNA-binding proteins across the entire genome, such as transcription factor binding sites and histone modification maps.

[0213] Cell-free chromatin immunoprecipitation sequencing (cfChIP-seq) involves applying ChIP-seq to samples containing cell-free DNA, such as liquid biopsy samples containing cfDNA, like plasma samples containing cfDNA (see, for example, Sadeh et al., Nat Biotechnol (2021) 39: 586–598 and Jang et al., Life Sci Alliance (2023) 6(12):e202302003, the entire contents of each of which are incorporated herein by reference). In some embodiments, cfChIP-seq uses antibodies or antibody fragments that bind to specific histone modifications (e.g., H3K4me3 and / or H3K27ac) and / or transcription factors, which are covalently or non-covalently coupled to beads (e.g., magnetic beads such as Dynabeads® beads) and incubated with a volume, such as about 1 mL, of thawed plasma obtained from the subject. For example, exemplary antibodies binding to H3K4me3 include PA5-27029 (available from Thermo Fisher Scientific, Waltham, MA) and C15410003 (available from Diagenode, Denville, NJ), and exemplary antibodies binding to H3K27ac include ab21623 or ab4729 (both available from Abcam, Cambridge, UK) and C15210016 (available from Diagenode, Denville, NJ).

[0214] In some embodiments, antibodies or antibody fragments may be covalently coupled to beads, such as epoxy resin beads. In some embodiments, antibodies or antibody fragments may be non-covalently coupled to magnetic beads, such as protein A or protein G beads, such as Dynabeads® protein A or Dynabeads® protein G beads. After washing, a cfDNA library is typically prepared from the captured cfDNA. Library construction can be performed on beads or after releasing the captured cfDNA by digestion of bound histones (e.g., using proteinase K). The cfDNA library is then sequenced to produce reads of the captured cfDNA sequence, for example, by next-generation sequencing (NGS) as known in the art. The reads are then analyzed, for example, by alignment and / or counting using standard bioinformatics techniques as known in the art. The cfChIP-seq bioinformatics workflow may include, for example, aligning the sequence reads to a reference genome using BWA or Bowtie2. The aligned sequences can be used for comparison with the reference sequence to identify and quantify peaks. In some implementations, sequencing data can be used to quantify histone modifications at a given genomic site. For example, in some implementations, histone modifications can be quantified by counting the number of sequence reads falling within the genomic site (e.g., those with at least one nucleotide overlapping the genomic site). In some implementations, non-unique and / or redundant sequence reads are discarded before quantifying histone modifications. In some implementations, sequence reads falling within high-noise regions of the genome are ignored during histone modification quantification.

[0215] In some implementations, sequence reads are adjusted according to sequencing depth before counting. Adjustment based on sequencing depth may include, for example, normalizing the sequence read quantiles to a common reference distribution. In some implementations, sequence reads are adjusted according to ChIP quality before counting. In some implementations, sequence reads are normalized relative to aggregated counts of a set of regions (e.g., 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, or more regions) that have previously been identified as having DNase hypersensitivity in most cell types. In some implementations, an estimate of the local background signal is subtracted from the sequence read count at each genomic locus.

[0216] CUT&Tag involves antibody-based target protein binding, such as transcription factors of interest or histone modifications, where chromatin cleavage and library preparation occur directly after antibody incubation (see Kaya-Okur et al., Nat Comm (2019) 10:1930). CUT&Tag assays utilize a Tn5 transposase fused to protein A, guiding the enzyme to an antibody bound to a target on chromatin. The Tn5 transposase is pre-loaded with a sequencing adaptor (generating an assembled pA-Tn5 adaptor transposon) for antibody-targeted fragmentation labeling. In a typical CUT&Tag assay, the sample is incubated with antibodies immobilized on magnetic beads coated with concanavalin A for easy subsequent washing. Cells can be incubated first with a primary antibody specific to the target protein of interest, followed by a secondary antibody. The sample can then be incubated with an assembled transposon consisting of protein A fused to a Tn5 transposase conjugated to an NGS adaptor. After incubation, unbound transposons can be washed away under strict conditions. Tn5 is a Mg 2+ Dependent enzyme, therefore Mg can be added. 2+ This activates the reaction, causing chromatin to be cleaved near the protein binding site, and simultaneously adding the NGS adaptor DNA sequence. Chromatin cleavage and library preparation can be completed in one step.

[0217] CUT&RUN is an epigenomic analysis strategy in which a micrococcal nuclease targets and cleaves an antibody to release a specific protein-DNA complex into a supernatant for paired-end DNA sequencing (see Skene and Henikoff, Elife (2017) 6:1-35, Skene et al., Nat Protoc (2018) 13:1006-1019). Because only the target fragment enters the solution and the vast majority of the DNA remains in solution, the background level of CUT&RUN is very low. In an exemplary CUT&RUN assay, the sample is incubated with an antibody or antibody fragment that binds to the target protein (e.g., a transcription factor of interest or a histone modification). The sample is then incubated with protein A-MNase, after which CaCl2 may be added to initiate the calcium-dependent nuclease activity of MNase, thereby cleaving the DNA surrounding the target protein. The protein A-MNase reaction can be quenched by adding chelating agents (EDTA and EGTA). The cleaved DNA fragment is then released, extracted, and used to construct sequencing libraries.

[0218] Those skilled in the art will understand that the DNA sequencing techniques applicable to the methods described herein include a sequencing step. Applicable DNA sequencing techniques include, for example, next-generation sequencing (NGS) methods. Additional steps required for preparing DNA for sequencing via a suitable sequencing method may be incorporated into the methods described herein. For example, in some embodiments, the methods described herein include attaching (e.g., ligating) a DNA adaptor to cfDNA. In some embodiments, the DNA adaptor may be attached before, during, or after histone modification enrichment. In some embodiments, the method includes amplifying cfDNA after attaching the DNA adaptor.

[0219] Techniques for detecting and quantifying chromatin accessibility Various molecular biology techniques are well known in the art and / or disclosed in this application for detecting and quantifying chromatin accessibility. In some embodiments, the methods, kits, and systems of this disclosure relate to detecting and quantifying chromatin accessibility in samples, for example, in liquid biopsy samples containing cfDNA (such as plasma samples containing cfDNA). ATAC-seq (transposon accessibility chromatin sequencing assay), NOMe-seq (nucleosome occupancy and methylome sequencing), FAIRE-seq (formaldehyde-assisted separation of regulatory elements sequencing), MNase-seq (micrococcal nuclease digestion sequencing), and DNase hypersensitivity assay are exemplary techniques in molecular biology that can be used to detect and quantify chromatin accessibility in samples. Sono-Seq is another alternative method that can be used (see Auerbach et al., Proc Natl Acad USA (2009) 106(35):14926-14931).

[0220] DNase hypersensitivity assays utilize the nonspecific DNA endonuclease deoxyribonuclease I (DNase I), which selectively digests accessible DNA regions. DNase I hypersensitive sites (DHS) identified by DNase-seq include open chromatin regulatory regions. A typical DNase hypersensitivity assay involves a first step in which the cell nucleus is isolated from the cell using a lysis buffer, and the nucleus is digested using DNase I. DNA fragment size is measured using gel electrophoresis to determine optimal digestion. After polishing to form blunt ends, biotinylated linkers can be ligated to the ends of the digested DNA, which can then be isolated. DNA with biotinylated linkers can be digested with the restriction endonuclease MmeI and captured by streptavidin-coated Dynabeads®, resulting in short tags to which second sequencing linkers can be ligated. The second linkers can be ligated and amplified to produce a library for sequencing. DNase-seq bioinformatics workflows may include, for example, aligning sequence reads to a reference genome using BWA or Bowtie2. The aligned sequence can be used to compare with a reference sequence to identify and quantify peaks.

[0221] MNase-seq uses micrococcal nuclease (MNase) to determine chromatin accessibility. This enzyme preferentially digests DNA that does not contain nucleosomes and is not bound to proteins. A typical MNase-seq assay may include a first step in which the cell nucleus is isolated from native or cross-linked chromatin, digested with MNase, and titrated. The in vivo formaldehyde cross-linking step is designed to capture the interaction between proteins and DNA. This cross-linking allows the bound protein to protect its associated DNA from MNase digestion. After cross-linking, the sample is digested with MNase, which can be specifically activated by adding Ca2+ to the buffer. Digestion can be prevented by a chelation reaction, in which case the sample is treated with RNase, the cross-linking is reversed, and the protein is digested from the chromatin. DNA can then be isolated via phenol-chloroform extraction. Uncut DNA is purified, and mononucleosome bands are separated and excised by gel electrophoresis. The isolated DNA can be amplified by adding adaptors to generate a library for sequencing. MNase-seq primarily sequences DNA regions bound to histones or other proteins. Therefore, it indirectly determines which DNA regions are accessible by directly identifying which regions bind to nucleosomes or proteins.

[0222] FAIRE-seq is a method for isolating nucleosome-deleted regions (NDRs) of DNA from chromatin. A typical FAIRE-seq assay may include a first step in which cells are fixed with formaldehyde, causing histones to crosslink with interacting DNA. The crosslinked chromatin is then sheared by sonication, yielding protein-free DNA and protein-crosslinked DNA fragments. Protein-free DNA can be separated using phenol-chloroform extraction: protein-crosslinked DNA remains in the organic phase, while protein-free DNA remains in the aqueous phase. Highly crosslinked DNA remains in the organic phase, while uncrosslinked DNA is pulled into the aqueous phase. The uncrosslinked DNA in the aqueous phase can then be amplified and sequenced. Reads enriched in the sequencing pool tend to have less nucleosome and transcription factor binding, thus inferring that they originate from accessible regions.

[0223] NOMe-seq is a method that uses M. CviPI methyltransferase to recognize nucleosome deletion regions (NDRs) in DNA. This methyltransferase methylates cytosine in GpC dinucleotides that are not protected by nucleosomes or other proteins. (The last sentence appears to be incomplete and possibly refers to a different topic.) m pG is different from GpC in the human genome. m GpCs are not naturally present in most cell types. m Levels can be compared to background signals and used for detection and quantification of NDR. A typical NOMe-seq protocol may include a step in which the sample is treated with M. cviPI and S-adenosylhomocysteine ​​(SAM) to methylate accessible GpC sites. The M. cviPI-treated DNA can be sonicated for sequencing of the DNA fragments. The DNA is then treated with bisulfite, using sodium bisulfite to convert unmethylated cytosine to uracil, while methylated cytosine remains unaffected. An adaptor is used to generate a library, which is then sequenced. Accessible chromatin is expected to have high levels of GpC. m and low levels of C m Therefore, NOMe-seq uses two independent methylation analyses to identify NDRs, which, as independent (but opposite) measurements, provide matching chromatin markers for each regulatory element.

[0224] ATAC-seq utilizes a highly active Tn5 transposase that preferentially cleaves accessible chromatin regions while simultaneously inserting adaptors into the fragmented regions (Buenrostro et al., Nat Methods (2013) 10(12):1213-1218, the full text of which is incorporated herein by reference). A typical ATAC-seq assay may include a first step in which the sample is incubated with a Tn5 transposase. The DNA can then be isolated and purified. The DNA fragmented and labeled by the Tn5 transposase can be purified, then amplified to generate a library and sequenced for analysis.

[0225] Techniques for detecting and quantifying DNA methylation Various molecular biology techniques are well known in the art and / or disclosed in this application for the detection and quantification of DNA methylation. In some embodiments, the methods, kits, and systems of this disclosure relate to the detection and quantification of chromatin accessibility in a sample, for example, in a liquid biopsy sample containing cfDNA (such as a plasma sample containing cfDNA). Bisulfite sequencing (BS-Seq), whole-genome bisulfite sequencing (WGBS), methylated DNA immunoprecipitation sequencing (MeDIP-seq), or methyl-CpG-binding domain sequencing (MBD-seq) are exemplary techniques in molecular biology that can be used to detect and quantify chromatin accessibility in a sample. Degenerate representative bisulfite sequencing (RRBS) is another alternative method that can be used (see Meissner et al., Nucleic Acids Res (2005) 33(18):5868-5877). Illumina Infinium arrays can also be used to detect and quantify DNA methylation.

[0226] DNA methylation generally refers to the methylation of the 5' position of cytosine (mC) by DNA methyltransferases (DNMTs). This is an important epigenetic modification in humans and many other species. In mammals, most DNA methylation occurs against a CpG dinucleotide background. DNA methylation is considered a repressive chromatin modification. Abnormal methylation can lead to a variety of diseases, including cancer (Robertson, Nat Rev Genet (2005) 6:597–610 and Bergman and Cedar, Nat Struct Mol Biol (2013) 20:274–281).

[0227] Bisulfite sequencing (BS-Seq) or whole-genome bisulfite sequencing (WGBS) is a well-established protocol for detecting methylated cytosine in genomic DNA. In this method, genomic DNA is treated with sodium bisulfite and then sequenced, providing single-base resolution of methylated cytosine in the genome. After bisulfite treatment, unmethylated cytosine is deamination to uracil, which is then converted to thymidine after sequencing. Simultaneously, methylated cytosine resists deamination and is read as cytosine. The location of methylated cytosine can then be determined by comparing the treated and untreated sequences.

[0228] In some embodiments, methylated DNA can be sequenced using methods that include enriching cfDNA containing methylated DNA. For example, enrichment can be achieved using agents that selectively bind to methylated DNA (e.g., antibodies in MeDIP-seq or methyl-CpG binding domains (MBD) in MBD-seq). In some embodiments, an agent that binds to methylated DNA (e.g., via covalent or non-covalent bonding) is attached to a physical support (e.g., beads, magnetic beads, agarose beads, or magnetic epoxy beads), wherein attachment can be performed before, during, or after incubation with the sample.

[0229] MeDIP-seq was first reported by Weber et al., Nat Genet (2005) 37:853–862. In a typical MeDIP-seq protocol, methylated DNA fragments are enriched using antibodies or antibody fragments that bind to 5-methylcytidine (5mC), and these fragments are then sequenced and analyzed. If 5mC-specific antibodies or antibody fragments are used, methylated DNA is isolated from genomic DNA via immunoprecipitation. Anti-5mC antibodies are incubated with fragmented genomic DNA and precipitated, followed by DNA purification and sequencing.

[0230] Methyl-CpG-binding domain sequencing (MBD-seq) is similar to MeDIP-seq, except that it uses methyl-binding domain (MBD) proteins instead of antibodies or antibody fragments to bind methylated DNA. In a typical MBD-seq protocol, genomic DNA is first sonicated and then incubated with a labeled MBD protein that binds to methylated cytosine. The protein-DNA complex is then precipitated using beads conjugated with antibodies specific to the MBD protein tag, followed by DNA purification and sequencing.

[0231] In some implementations, DNA methylation at a given genomic site can be quantified by sequencing the methylated DNA. For example, in some implementations, DNA methylation at a genomic site can be quantified by counting the number of sequence reads that overlap with the genomic site (e.g., containing at least one nucleotide that overlaps with the genomic site).

[0232] Those skilled in the art will understand that the DNA sequencing techniques applicable to the methods described herein include a sequencing step. Applicable DNA sequencing techniques include, for example, next-generation sequencing (NGS) methods. Additional steps required for preparing DNA for sequencing via a suitable sequencing method may be incorporated into the methods described herein. For example, in some embodiments, the methods described herein include attaching (e.g., ligating) a DNA adaptor to cfDNA. In some embodiments, the DNA adaptor may be attached before, during, or after histone modification enrichment.

[0233] Classifier In some embodiments, this disclosure provides methods for obtaining a classifier, for example, a valid classifier that can be used to determine SCLC / LUAD status. In some embodiments, based on analysis of cell-free DNA (cfDNA) from a biological sample obtained from or derived from a subject, optionally from a liquid biopsy sample, the presence of a valid epigenetic characteristic indicating SCLC or LUAD cancer is determined in the subject, wherein the presence of the valid epigenetic characteristic has been determined using a valid classifier.

[0234] For illustrative purposes and not limited thereto, in one exemplary embodiment of this disclosure, a validated classifier can be obtained in the following manner: (a) Identify genomic features of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in biological samples obtained from a first group of subjects who have been previously diagnosed with SCLC (e.g., primary SCLC or transformed SCLC). (b) Identify genomic features of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in biological samples obtained from a second group of healthy subjects or subjects previously identified with LUAD cancer; (c) Compare the genomic features identified in step (a) with those identified in step (b) to identify genomic sites (“difference sites”) that show statistical differences in histone modification, chromatin accessibility, transcription factor binding and / or DNA methylation levels. (d) Using histone modification, chromatin accessibility, transcription factor binding, and / or DNA methylation level training at differential sites, a classifier is used to distinguish (i) samples from one or more biological samples obtained from a first cohort, and (ii) samples from one or more biological samples obtained from a second cohort, to identify samples having histone modification, chromatin accessibility, transcription factor binding, and / or DNA methylation level characteristics (“epigenetic features”) indicating that the sample may have been obtained from the first cohort; and (e) A validated classifier is obtained by validating the classifier in step (d) on a third cohort comprising independent, blinded subjects with SCLC cancer and LUAD cancer, and a threshold is selected such that the validated classifier predicts SCLC cancer and the area under the receiver operating characteristic curve (AUROC) is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95), wherein subjects falling into the predicted SCLC cancer group exhibit validated epigenetic characteristics and subjects not falling into the SCLC cancer group lack validated epigenetic characteristics.

[0235] Those skilled in the art will understand that other methods can be used to obtain classifiers, such as classifiers that can be used to determine the verification of SCLC / LUAD status, and this disclosure is not limited to classifiers obtained according to such methods.

[0236] Exemplary genomic sites This disclosure includes the identification of exemplary genomic loci with differential modifications and / or differential accessibility in SCLC and LUAD cancers. See Tables 1 through 3, which show the chromosomal coordinates of each genomic locus and whether they are associated with SCLC or LUAD cancer (genomic loci in columns with the title “Genomic Loci (SCLC)” are associated with SCLC, while those in columns with the title “Genomic Loci (LUAD)” are associated with LUAD cancer). Genomic loci are ordered based on their chromosomal coordinates, which are based on human genome version hg19.

[0237] This invention is not limited to methods using the exact same chromosome coordinates listed in Tables 1 through 13. This disclosure covers methods using any genomic locus and its subregions as listed in Tables 1 through 13. Right nowThe methods mentioned in this document for detecting and / or quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic loci listed in Tables 1 to 13 cover methods for detecting these markers at any location (including any subregion) within these genomic loci. For example, Table 2 lists chr1:110800810-110801156 as genomic loci for detecting and / or quantifying H3K27ac modifications. This covers methods for detecting and / or quantifying H3K27ac modifications at any location or subregion within chr1:110800810-110801156, such as methods for detecting and / or quantifying H3K27ac modifications within chr1:110800910-110801056, and so on. In some embodiments, the subregion may span at least 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, or at least 3000 consecutive base pairs located between the lower and upper coordinates of the genomic sites listed in Tables 1 to 13. In some embodiments, the subregion may span fewer than 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, or at least 3000 consecutive base pairs located between the lower and upper coordinates of the genomic sites listed in Tables 1 to 13. In some embodiments, the subregion may have the same center coordinates as the genomic sites listed in Tables 1 to 13. In some embodiments, the subregion may have different center coordinates than the genomic sites listed in Tables 1 to 13. It should also be understood that the lower / upper bound coordinates of the genomic loci in Tables 1 to 13 are approximate values, and this disclosure covers methods for expanding any one or more genomic loci by increasing the size of the genomic loci by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, or up to 50% in one or both directions.

[0238] In some embodiments, the classifier is generated using a set of differentially modified and / or differentially accessible genomic loci associated with SCLC and a set of differentially modified and / or differentially accessible loci associated with LUAD cancer. Sequence reads falling into each selected genomic locus are analyzed and counted, for example, as described herein, including examples. In some embodiments, the counts of genomic loci associated with SCLC are aggregated, and the counts of genomic loci associated with LUAD cancer are aggregated. In some embodiments, the ratio of aggregated SCLC and LUAD cancer counts is used to determine the SCLC / LUAD status. Other methods described herein and known in the art for generating and applying classifiers to determine SCLC / LUAD status using genomic loci and associated sequencing data, such as, but not limited to, methods using learned statistical classifier systems or combinations of learned statistical classifier systems, are also available.

[0239] In some embodiments, exemplary genomic loci from one or more of Tables 1 to 13 are used in a monomodal classifier, for example, a classifier that uses a single histone modification (e.g., H3K4me3 or H3K27ac) or DNA methylation at one or more genomic loci to determine the SCLC / LUAD state. In some embodiments, exemplary genomic loci from any of Tables 1 to 13, or any combination thereof, are combined for a multimodal classifier, for example, a classifier that uses more than one histone modification (e.g., H3K4me3 and H3K27ac) or one or more histone modifications (e.g., H3K4me3 and / or H3K27ac) and DNA methylation at one or more genomic loci to determine the SCLC / LUAD state.

[0240] In some embodiments, the methods described herein include quantifying one or more of histone modifications, DNA methylation, chromatin accessibility, and / or transcription factor binding at one or more sites provided in one or more of Tables 1 to 13. In some implementations, the method described herein includes quantifying one or more of the following sites listed in Tables 1 through 13: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 75, 100, 200, 300, 400, 500, 600, 800, 1,000, 1,500, 2,000, 3,000, 4,000, or more (e.g., 1-200, 5-200, 10-200, 15-200, 20-200, 30-200, 40-200, 50-200, 60-200, 70-200, 80-200, ...). One or more of the following: histone modifications, DNA methylation, chromatin accessibility, and / or transcription factor binding at 90-200, 100-200, 1-150, 5-150, 10-150, 15-150, 20-150, 30-150, 40-150, 50-150, 60-150, 70-150, 80-150, 90-150, 100-150, 1-100, 5-100, 10-100, 15-100, 20-100, 30-100, 40-100, 50-100, 60-100, 70-100, 80-100, 90-100. In some embodiments, the method described herein includes quantifying one or more of the following at each site provided in one or more of Tables 1 to 13: histone modifications, DNA methylation, chromatin accessibility, and / or transcription factor binding. In some embodiments, the method described herein includes quantifying at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the histone modifications, DNA methylation, chromatin accessibility, and / or transcription factor binding at each site identified in one or more of Tables 1 to 13. In some embodiments, the method described herein includes quantifying one or more of the following at least a certain percentage of sites identified in Table 13: histone modifications, DNA methylation, chromatin accessibility, and / or binding to transcription factors, with the lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and the upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%.

[0241] Difference H3K4me3 modification Table 1 provides genomic loci exhibiting differential H3K4 methylation (particularly H3K4 trimethylation, H3K4me3) in SCLC and LUAD cancers, showing the chromosomal coordinates of each locus and whether they are associated with SCLC or LUAD cancer (genomic loci in columns with "Genomic Loci (SCLC)" in the title are associated with SCLC, while those in columns with "Genomic Loci (LUAD)" in the title are associated with LUAD cancer). Genomic loci are ordered based on their chromosomal coordinates, which are based on human genome version hg19.

[0242] Those skilled in the art will understand that the methods disclosed herein do not require evaluating the H3K4me3 modification of every genomic locus listed in Table 1. Instead, the H3K4me3 modification of a subset of loci can be evaluated. A subset of genomic loci in Table 1 can be selected based on various performance criteria (e.g., for determining SCLC / LUAD status), such as selecting genomic loci exhibiting differential modifications at a specific statistical significance level and / or a specific difference threshold (e.g., measured log2 (fold change)) between relevant states. A subset of genomic loci can also be selected based on algorithms, such as during the process of obtaining a classifier. Those skilled in the art will understand that such subsets of loci in Table 1, and the loci included in such subsets, whether present individually or in randomly selected subsets, have at least equivalent information content (e.g., statistical significance and / or reliability) for the purposes disclosed herein (e.g., for determining SCLC / LUAD status). See also the embodiments of this disclosure illustrating experiments demonstrating that information-rich classifiers can be produced using many different combinations of loci. Among other things, this disclosure specifically includes subsets of genomic loci listed in Table 1, which have absolute log2 (fold change) values ​​of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher. This disclosure also includes subsets of genomic loci listed in Table 1, wherein the absolute log2 (fold change) of these subsets is 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.

[0243] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In some implementations, if at least a certain number are identified in Table 1 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250 or 300) and upper limit selected from 10, 15, 20, 25, 50, 75, 100, 150, 2... If a site (00, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000) is differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD status (e.g., SCLC status). In certain specific implementations, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 sites identified in Table 1 (e.g., about 1 to about 1000, about 5 to about 3000, about 10 to about 1000, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, ... If approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150 sites are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status).In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 1 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0244] In various implementations, if at least one of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites identified in Table 1 (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) is differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). (For example, the "top" 10 sites refer to the 10 sites with the highest absolute log2 (fold change) in Table 1). In some embodiments, if at least one of the top 10 sites identified in Table 1 is differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least one of the top 25 sites identified in Table 1 is differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least one of the first 50 loci identified in Table 1 is differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom or from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least five of the first 10 loci identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom or from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least five of the first 25 loci identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom or from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status).In some implementations, if at least five of the top 50 sites identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD status (e.g., SCLC status).

[0245] In various implementations, if at least one of the top 10 sites identified in Table 1 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In various implementations, if at least one of the first 25 sites identified in Table 1 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In various implementations, if at least one of the first 50 sites identified in Table 1 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) and the total number of sites identified in Table 1 is at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, ... If 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status).In various implementations, if at least five of the first 25 sites identified in Table 1, and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In various implementations, if at least five of the first 50 sites identified in Table 1, and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 1 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state).

[0246] In various implementations, differential H3K4me3 modification refers to a methylation state characterized by an increase or decrease of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 40-fold, 45-fold, 45-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, compared to a reference. 50 times or more, or any range such as 1% to 50%, 50% to 2 times, 25% to 50 times, 25% to 30 times, 25% to 20 times, 25% to 16 times, 30% to 16 times, 50% to 16 times, 70% to 16 times, 2 times to 16 times, 2.2 times to 16 times, 2.6 times to 16 times, 3 times to 16 times, 3.4 times to 16 times, 4 times to 16 times, 4.5 times to 16 times, 5.2 times to 16 times, 6 times to 16 times, 7 times to 16 times or 8 times to 16 times (inclusive), optionally wherein the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6 or 1e-6. In various implementations, the increase or decrease in the measured methylation value can be or is expressed as log2 (fold change), for example, log2 (fold change) is at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, 10 times, 15 times, 20 times or higher, or such as an increase or decrease of 0.1 times to 10 times, 0.2 times to 5 times, 0.2 times to 4.0 times, 0.4 times to 4.0 times, 0.4 times to Any range between 4.0x, 0.6x to 4.0x, 0.8x to 4.0x, 1.0x to 4.0x, 1.2x to 4.0x, 1.4x to 4.0x, 1.6x to 4.0x, 1.8x to 4.0x, 2.0x to 4.0x, 2.2x to 4.0x, 2.4x to 4.0x, 2.6x to 4.0x, 2.8x to 4.0x, or 3.0x to 4.0x (inclusive), optionally wherein the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6, or 1e-6.

[0247] In various embodiments, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 sites (or any subset thereof) identified in Table 5, such as those listed as H3K4me3 sites, are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least a certain number of sites identified in Table 5 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 15 and upper limit selected from 10, 15, and 20) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the subject from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In certain specific implementations, if at least 1, 2, 3, 4, 5, 10, 15, or 20 sites identified in Table 5 (e.g., about 1 to about 20, about 2 to about 20, about 5 to about 20, about 5, about 10, about 15, about 20 sites) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 5 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 5 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0248] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, or 130 sites (or any subset thereof) identified in Table 12 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain number of sites identified in Table 12 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 and upper limit selected from 10, 15, 20, 25, 50, 75, 100 or 135) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the subject from whom or from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 12 (e.g., about 1 to about 135, about 5 to about 135, about 10 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 100, about 2 to about 135, about 5 to about 135, about 10 to about 135, about 20 to about 135, about 25 to about 135, about 50 to about 135, about 20 to about 135, about 50 to about 135, about 50 to about 100, about 5, about 10) If approximately 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, or 135 sites are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from has a specific SCLC / LUAD status (e.g., SCLC status).In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 12 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 12 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0249] In various embodiments, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 15 sites (or any subset thereof) identified in Table 13 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In certain specific embodiments, if 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 sites identified in Table 13 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 13 are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In some implementations, if at least a certain percentage of the sites identified in Table 13 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially modified with H3K4me3 compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD state (e.g., LUAD state).

[0250] Difference H3K27ac modification Table 2 provides genomic loci exhibiting differential H3K27ac modification in SCLC and LUAD cancers, showing the chromosomal coordinates of each locus and whether they are associated with SCLC or LUAD cancer (genomic loci in columns with "Genomic Loci (SCLC)" in the title are associated with SCLC, while those in columns with "Genomic Loci (LUAD)" in the title are associated with LUAD cancer). Genomic loci are ordered based on their chromosomal coordinates, which are based on human genome version hg19.

[0251] Those skilled in the art will understand that the methods disclosed herein do not require evaluation of H3K27ac modifications for every genomic locus listed in Table 2. Instead, H3K27ac modifications for a subset of loci can be evaluated. A subset of genomic loci in Table 2 can be selected based on various performance criteria (e.g., for determining SCLC / LUAD status), such as selecting genomic loci exhibiting differential modifications at a specific statistical significance level and / or a specific difference threshold (e.g., measured log2 (fold change)) between relevant states. A subset of genomic loci can also be selected based on algorithms, such as during the process of obtaining a classifier. Those skilled in the art will understand that such subsets of loci in Table 2, and the loci included in such subsets, whether present individually or in randomly selected subsets, have at least equivalent information content (e.g., statistical significance and / or reliability) for the purposes disclosed herein (e.g., for determining SCLC / LUAD status). See also the embodiments of this disclosure illustrating experiments demonstrating that information-rich classifiers can be produced using many different combinations of loci. Among other things, this disclosure specifically includes subsets of genomic loci listed in Table 2, which have absolute log2 (fold change) values ​​of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher. This disclosure also includes subsets of genomic loci listed in Table 2, wherein the absolute log2 (fold change) of these subsets is 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.

[0252] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In some implementations, if at least a certain quantity is identified in Table 2 (the lower limit is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250 or 300) and the upper limit is selected from 10, 15, 20, 25, 50, 75 If a site (100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000) is modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD status (e.g., SCLC status).In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 2 (e.g., about 1 to about 1,000, about 5 to about 3,000, about 10 to about 1,000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 10) are identified in Table 2. If 0, approximately 5, approximately 10, approximately 15, approximately 20, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150 sites are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived has a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 2 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) of the sites are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0253] In various implementations, if at least one of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites identified in Table 2 (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) is modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). (For example, the "top" 10 sites refer to the 10 sites with the highest absolute log2 (fold change) in Table 2). In some embodiments, if at least one of the top 10 sites identified in Table 2 is modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least one of the top 25 sites identified in Table 2 is modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least one of the top 50 sites identified in Table 2 is modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least five of the first 10 loci identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least five of the first 25 loci identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).In some implementations, if at least five of the top 50 sites identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD status (e.g., SCLC status).

[0254] In various implementations, if at least one of the top 10 sites identified in Table 2 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In various implementations, if at least one of the first 25 sites identified in Table 2 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In various implementations, if at least one of the first 50 sites identified in Table 2 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) and the total number of sites identified in Table 2 is at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, or 9) If 0, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state).In various implementations, if at least five of the first 25 sites identified in Table 2, and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state). In various implementations, if at least five of the first 50 sites identified in Table 2, and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 2 are modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD state (e.g., SCLC state).

[0255] In various implementations, differential H3K27ac modification refers to an acetylation state characterized by an increase or decrease of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 45-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 45-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, or 45-fold compared to a reference. 50 times or more, or any range such as 1% to 50%, 50% to 2 times, 25% to 50 times, 25% to 30 times, 25% to 20 times, 25% to 16 times, 30% to 16 times, 50% to 16 times, 70% to 16 times, 2 times to 16 times, 2.2 times to 16 times, 2.6 times to 16 times, 3 times to 16 times, 3.4 times to 16 times, 4 times to 16 times, 4.5 times to 16 times, 5.2 times to 16 times, 6 times to 16 times, 7 times to 16 times or 8 times to 16 times (inclusive), optionally wherein the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6 or 1e-6. In various implementations, the increase or decrease in the measured value of acetylation can be or is expressed as log2 (fold change), for example, log2 (fold change) is at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, 10 times, 15 times, 20 times or higher, or such as an increase or decrease of 0.1 times to 10 times, 0.2 times to 5 times, 0.2 times to 4.0 times, 0.4 times to 4.0 times, 0.4 times to Any range between 4.0x, 0.6x to 4.0x, 0.8x to 4.0x, 1.0x to 4.0x, 1.2x to 4.0x, 1.4x to 4.0x, 1.6x to 4.0x, 1.8x to 4.0x, 2.0x to 4.0x, 2.2x to 4.0x, 2.4x to 4.0x, 2.6x to 4.0x, 2.8x to 4.0x, or 3.0x to 4.0x (inclusive), optionally wherein the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6, or 1e-6.

[0256] Table 4 provides genomic loci exhibiting differential H3K27ac modifications in different SCLC subtypes, showing the chromosomal coordinates of each locus and which subtype they are associated with. In some embodiments, the method described herein includes evaluating H3K27ac modifications at 1, 2, 3, or 4 of the genomic loci listed in Table 4.

[0257] In various embodiments, if at least 1, 2, 3, 4, 5, 6, or 7 of the sites identified in Table 5, such as those listed as H3K27ac sites (or any subset thereof), are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if 1, 2, 3, 4, 5, 6, or 7 of the sites in Table 5 are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0258] In various implementation schemes, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000 are identified in Table 6 If 1,500, 2,000, 2,500, 3,000, 3,500, 4,000, 4,500, 5,000, or 5,500 sites (or any subset thereof) are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain number are identified in Table 6 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300) and upper limit selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 3... If a site (50, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, or 5500) is differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD status (e.g., SCLC status).In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 6 (e.g., about 1 to about 5500, about 5 to about 5500, about 10 to about 5500, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 50 to about 150, about 1 ... If 00, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100, about 105, about 110, about 115, about 120, about 125, about 130, about 135, about 140, about 145, or about 150 sites are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived has a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 6 are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 6 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0259] In various implementation schemes, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1 are identified in Table 7 If 000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 sites (or any subset thereof) are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from has a specific SCLC / LUAD state (e.g., LUAD state). In some implementations, if at least a certain quantity is identified in Table 7 (the lower limit is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250 or 300) and the upper limit is selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 30), then the quantity is considered to be at least a certain quantity (the lower limit is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 250 or 300) and the upper limit is selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 30). If a site (0, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000) is differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD state (e.g., LUAD state).In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 7 (e.g., about 1 to about 5000, about 5 to about 5000, about 10 to about 5000, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 5 ...10 to about 150, about 10 to about 150, about 10 to about 150, about 10 to about 150, about 1 If 100, approximately 5, approximately 10, approximately 15, approximately 20, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150 loci are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from has a specific SCLC / LUAD state (e.g., LUAD state). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 7 are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In some implementations, if at least a certain percentage of the sites identified in Table 7 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially modified with H3K27ac compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD state (e.g., LUAD state).

[0260] Differential DNA methylation Table 3 provides genomic sites exhibiting differential DNA methylation in SCLC and LUAD cancers, showing the chromosomal coordinates of each site and whether they are associated with either SCLC or LUAD cancer (genomic sites in columns with "Genomic Sites (SCLC)" in the title are associated with SCLC, while those in columns with "Genomic Sites (LUAD)" in the title are associated with LUAD cancer). Genomic sites are ordered based on their chromosomal coordinates, which are based on human genome version hg19.

[0261] Those skilled in the art will understand that the methods disclosed herein do not require evaluating DNA methylation at every genomic site listed in Table 3. Instead, DNA methylation at a subset of sites can be evaluated. A subset of genomic sites in Table 3 can be selected based on various performance criteria (e.g., for determining SCLC / LUAD status), such as selecting genomic sites exhibiting differential modifications at a specific statistical significance level and / or a specific difference threshold (e.g., measured log2 (fold change)) between relevant states. A subset of genomic sites can also be selected based on algorithms, such as during the process of obtaining a classifier. Those skilled in the art will understand that such subsets of sites in Table 3, and the sites included in such subsets, whether present individually or in randomly selected subsets, have at least equivalent information content (e.g., statistical significance and / or reliability) for the purposes disclosed herein (e.g., for determining SCLC / LUAD status). See also the embodiments of this disclosure illustrating experiments demonstrating that information-rich classifiers can be generated using many different combinations of sites. Among other things, this disclosure specifically includes subsets of genomic loci listed in Table 3, which have absolute log2 (fold change) values ​​of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher. This disclosure also includes subsets of genomic loci in Table 3 with absolute log2 (fold change) values ​​of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.

[0262] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 sites (or any subset thereof) identified in Table 3 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain quantity is identified in Table 3 (the lower limit is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250 or 300) and the upper limit is selected from 10, 15, 20, 25, 50, 75, 100, 150, 2 If the sites (00, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000) are differentially methylated with DNA compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then it is determined that the subject from whom or from which the sample was obtained has a specific SCLC / LUAD status (e.g., SCLC status).In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 3 (e.g., about 1 to about 1,000, about 5 to about 3,000, about 10 to about 1,000, about 25 to about 200, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 5 ... If approximately 100, approximately 5, approximately 10, approximately 15, approximately 20, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150 sites are differentially methylated with DNA compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived has a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 3 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 3 (lower limits selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limits selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0263] In various implementations, if at least one of the first 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites identified in Table 3 (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) is differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). (For example, the "top" 10 sites refer to the 10 sites with the highest absolute log2 (fold change) in Table 3). In some embodiments, if at least one of the top 10 sites identified in Table 3 is differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least one of the top 25 sites identified in Table 3 is differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some embodiments, if at least one of the top 50 sites identified in Table 3 is differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least five of the first 10 sites identified in Table 3 are differentially DNA-methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least five of the first 25 sites identified in Table 3 are differentially DNA-methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).In some implementations, if at least five of the top 50 sites identified in Table 3 are differentially methylated with DNA compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), the subject from whom the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0264] In various implementations, if at least one of the top 10 sites identified in Table 3 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 3 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least one of the first 25 sites identified in Table 3 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 3 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least one of the first 50 sites identified in Table 3 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) and the total number of sites identified in Table 3 is at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, or 90) If 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) are differentially methylated with DNA compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status).In various implementations, if at least five of the first 25 sites identified in Table 3, and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 3 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least five of the first 50 sites identified in Table 3, and a total of at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 sites (or any subset thereof) identified in Table 3 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample is derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0265] In various implementations, differential DNA methylation refers to a methylation state characterized by an increase or decrease of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, ...2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 5-fold, 5-fold, 2-fold, 3-fold, 40-fold, 45-fold, 5-fold, 2-fold, 3-fold, 3-fold, 40-fold, 45-fold, 5-fold, 2-fold, 3-fold, 4-fold, 5-fold, 2-fold, 3-fold, 3-fold, 40-fold, 45-fold, 5-fold, 2-fold, 3-fold, 4-fold, 5-fold, 2-fold, 3-fold, 3-fold, 40-fold, 45-fold, 0 times or greater, or any range such as 1% to 50%, 50% to 2 times, 25% to 50 times, 25% to 30 times, 25% to 20 times, 25% to 16 times, 30% to 16 times, 50% to 16 times, 70% to 16 times, 2 times to 16 times, 2.2 times to 16 times, 2.6 times to 16 times, 3 times to 16 times, 3.4 times to 16 times, 4 times to 16 times, 4.5 times to 16 times, 5.2 times to 16 times, 6 times to 16 times, 7 times to 16 times, or 8 times to 16 times (inclusive), optionally wherein the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6, or 1e-6. In various implementations, the increase or decrease in the measured methylation value can be or is expressed as log2 (fold change), for example, log2 (fold change) is at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, 10 times, 15 times, 20 times or higher, or such as an increase of 0.1 times to 10 times, 0.2 times to 5 times, 0.2 times to 4.0 times, 0.4 times to 4.0 times, 0.4 times to 4.0 times. Any range between 0.0x, 0.6x to 4.0x, 0.8x to 4.0x, 1.0x to 4.0x, 1.2x to 4.0x, 1.4x to 4.0x, 1.6x to 4.0x, 1.8x to 4.0x, 2.0x to 4.0x, 2.2x to 4.0x, 2.4x to 4.0x, 2.6x to 4.0x, 2.8x to 4.0x, or 3.0x to 4.0x (inclusive), optionally wherein the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6, or 1e-6.

[0266] In various embodiments, if at least one, two, three, or four of the sites identified in Table 5, such as those listed as MBD genomic sites (or any subset thereof), are differentially DNA-methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In certain specific embodiments, if one, two, three, or four sites in Table 5 are differentially methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0267] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 600, or 650 sites (or any subset thereof) identified in Table 8 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain number of sites identified in Table 8 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and upper limit selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, or 650) are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the subject from whom or from which the sample was obtained is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 8 (e.g., about 1 to about 650, about 5 to about 650, about 10 to about 650, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 2) are identified in Table 8, then the following conditions apply: If 0, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150 sites are differentially methylated with DNA compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from which the sample was derived has a specific SCLC / LUAD status (e.g., SCLC status).In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 8 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the sites identified in Table 8 (lower limits selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limits selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0268] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, or 600 sites (or any subset thereof) identified in Table 9 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In some implementations, if at least a certain number of sites identified in Table 9 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and upper limit selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, or 600) are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the subject from whom or from which the sample was obtained is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 9 (e.g., about 1 to about 600, about 5 to about 600, about 10 to about 600, about 1 to about 550, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about...), If 20, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150 sites are differentially methylated with DNA compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from which the sample was derived has a specific SCLC / LUAD status (e.g., LUAD status).In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 9 are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD status (e.g., LUAD status). In some implementations, if at least a certain percentage of the sites identified in Table 9 (lower limits selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limits selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) are differentially DNA methylated compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., LUAD status).

[0269] Differential chromatin accessibility or transcription factor binding The genomic loci provided in Tables 1 to 13 can also demonstrate differential chromatin accessibility or transcription factor binding in SCLC and LUAD cancers.

[0270] In various embodiments, while not wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds to and / or is related to chromatin accessibility. In various embodiments, while not wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds to and / or is related to chromatin accessibility. In various embodiments, while not wishing to be bound by any particular scientific theory, DNA methylation corresponds to and / or is related to chromatin accessibility.

[0271] In some implementations, while not intended to be limited to any particular scientific theory, chromatin accessibility corresponds to and / or is related to H3K4me3 modification. Therefore, in some implementations, based on the section above discussing exemplary genomic sites with differential H3K4me3 modification, SCLC / LUAD status can be determined by detecting and quantifying chromatin accessibility at one or more genomic sites in Table 1.

[0272] In some implementations, while not intended to be limited to any particular scientific theory, chromatin accessibility corresponds to and / or is related to H3K27ac modifications. Therefore, in some implementations, based on the section above discussing exemplary genomic sites with differential H3K27ac modifications, SCLC / LUAD status can be determined by detecting and quantifying chromatin accessibility at one or more genomic sites in Table 2.

[0273] In some implementations, while not wishing to be limited to any particular scientific theory, chromatin accessibility corresponds to and / or is related to DNA methylation. Therefore, in some implementations, based on the section above discussing exemplary genomic sites with differential DNA methylation, SCLC / LUAD status can be determined by detecting and quantifying chromatin accessibility at one or more genomic sites in Table 3.

[0274] In various embodiments, while not wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds to and / or is associated with transcription factor binding. In various embodiments, while not wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds to and / or is associated with transcription factor binding. In various embodiments, while not wishing to be bound by any particular scientific theory, DNA methylation corresponds to and / or is associated with transcription factor binding.

[0275] In some implementations, while not intended to be limited to any particular scientific theory, the binding of RNA pol II corresponds to and / or is associated with H3K4me3 modification. Therefore, in some implementations, based on the section above discussing exemplary genomic sites with differential H3K4me3 modification, the SCLC / LUAD status can be determined by detecting and quantifying the binding of RNA pol II at one or more genomic sites in Table 1.

[0276] In some implementations, while not intended to be limited to any particular scientific theory, the binding of p300, the mediator complex, the cohesin complex, or RNA pol II corresponds to and / or is associated with H3K27ac modification. Therefore, in some implementations, based on the section above discussing exemplary genomic sites with differential H3K27ac modification, the SCLC / LUAD status can be determined by detecting and quantifying the binding of p300, the mediator complex, the cohesin complex, or RNA pol II at one or more genomic sites in Table 2.

[0277] In some embodiments, while not intended to be limited to any particular scientific theory, the binding of NKX2-1, ASCL1, POU2F3, NEUROD1, YAP1, MYC, SOX2, or HNF4a corresponds to and / or is associated with histone methylation (e.g., H3K4me3), histone acetylation (e.g., H3K27ac), or DNA methylation. Therefore, in some embodiments, based on the section above discussing exemplary genomic sites with differential histone methylation (e.g., H3K4me3), histone acetylation (e.g., H3K27ac), or DNA methylation, the SCLC / LUAD status can be determined by detecting and quantifying the binding of NKX2-1, ASCL1, POU2F3, NEUROD1, YAP1, MYC, SOX2, or HNF4a at one or more genomic sites in Tables 1 through 3.

[0278] In various implementation schemes, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 75 are identified in Table 10 If 0, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 loci (or any subset thereof) show differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD), then the sample or the subject from which the sample was obtained or from has a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain number are identified in Table 10 (lower limit selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250 or 300) and upper limit selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250) If a locus (300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000) shows differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD), then the subject from whom the sample was obtained or from which the sample was derived has a specific SCLC / LUAD status (e.g., SCLC status).In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 10 (e.g., about 1 to about 5000, about 5 to about 5000, about 10 to about 5000, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 5 ... If a locus (0 to approximately 100, approximately 5, approximately 10, approximately 15, approximately 20, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150) has differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD), then the sample or the subject from which the sample was obtained or from has a specific SCLC / LUAD status (e.g., SCLC status). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 10 have differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status). In some implementations, if at least a certain percentage of the loci identified in Table 10 (lower limit selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limit selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) have differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., SCLC status).

[0279] In various implementations, if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, or 4500 loci (or any subset thereof) identified in Table 11 have differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from which the sample was derived is determined to have a specific SCLC / LUAD state (e.g., LUAD state). In some implementations, if at least a certain quantity is identified in Table 11 (the lower limit is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250 or 300) and the upper limit is selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 2... If a locus (50, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, or 4500) shows differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the subject from whom the sample was obtained or from which the sample was derived has a specific SCLC / LUAD state (e.g., LUAD state).In certain specific embodiments, if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 of those identified in Table 11 (e.g., about 1 to about 4500, about 5 to about 4500, about 10 to about 4500, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, about 50 to about 200, about 20 to about 150, about 5 ... If a locus (0 to approximately 100, approximately 5, approximately 10, approximately 15, approximately 20, approximately 25, approximately 30, approximately 35, approximately 40, approximately 45, approximately 50, approximately 55, approximately 60, approximately 65, approximately 70, approximately 75, approximately 80, approximately 85, approximately 90, approximately 95, approximately 100, approximately 105, approximately 110, approximately 115, approximately 120, approximately 125, approximately 130, approximately 135, approximately 140, approximately 145, or approximately 150) has differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from has a specific SCLC / LUAD state (e.g., LUAD state). In various implementations, if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of the sites identified in Table 11 have differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., LUAD status). In some implementations, if at least a certain percentage of the loci identified in Table 11 (lower limits selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10% and upper limits selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%) have differential chromatin accessibility compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC), then the sample or the subject from which the sample was obtained or from is determined to have a specific SCLC / LUAD status (e.g., LUAD status).

[0280] application The methods, kits, and systems disclosed herein include analyzing differentially modified and / or differentially accessible genomic sites to determine the SCLC / LUAD status of lung cancer. The methods, kits, and systems disclosed herein can be used in any of a variety of applications. For example, the methods, kits, and systems disclosed herein can be used for the detection and / or treatment of cancer based on SCLC / LUAD status. The methods, kits, and systems disclosed herein can also be used to detect or determine resistance to therapy or transformation of lung cancer (e.g., LUAD cancer) (e.g., from LUAD to SCLC).

[0281] In various embodiments, the methods, kits, and systems of this disclosure can be applied to asymptomatic human subjects. As used herein, a subject may be described as “asymptomatic” if the subject does not report, and / or does not demonstrate, by non-invasive, observable indicators (e.g., no device-based detection, tissue sample analysis, body fluid analysis, surgery, or cancer screening, one, several, or all of which) sufficient cancer characteristics to support a medically reasonable suspicion that the subject may have cancer, such as lung cancer. The methods, kits, and systems of this disclosure enable early cancer detection, leading to medical benefits, including the possibility of early treatment and improved treatment outcomes.

[0282] In various implementations, the methods, kits, and systems of this disclosure can be applied to human subjects who are highly susceptible to lung cancer (including SCLC and / or LUAD). Exemplary factors that increase susceptibility to lung cancer include a history of smoking, exposure to secondhand smoke, exposure to certain toxins, and family history.

[0283] In various embodiments, the methods, kits, and systems of this disclosure can be applied to symptomatic human subjects. As used herein, a subject may be described as “symptomatic” if the subject reports, and / or demonstrates by non-invasive, observable indicators (e.g., without device-based detection, tissue sample analysis, body fluid analysis, surgery, or cancer screening, one, several, or all of these) that there are sufficient cancer characteristics to support a medically reasonable suspicion that the subject may have lung cancer. For example, in various embodiments, a sample from a subject (optionally, wherein the subject has lung cancer but their SCLC / LUAD status is unknown) can be measured according to one or more embodiments of this disclosure to determine whether the lung cancer is SCLC cancer or LUAD cancer. In various embodiments, a sample from a subject with lung cancer, known or suspected of having SCLC cancer (or LUAD cancer) can be measured according to one or more embodiments of this disclosure to determine whether the lung cancer is actually SCLC cancer (or LUAD cancer).

[0284] In some embodiments, the methods, kits, and systems of this disclosure can be used to determine that a subject has SCLC cancer, consistent with a prior determination based on IHC testing. In some embodiments, the methods, kits, and systems of this disclosure can be used to determine that a subject has LUAD cancer, consistent with a prior determination based on IHC testing.

[0285] In some embodiments, the methods, kits, and systems of this disclosure can be used to verify or confirm a prior determination that a subject has SCLC cancer (optionally, SCLC cancer associated with an IHC test). In some embodiments, the methods, kits, and systems of this disclosure can be used to verify or confirm a prior determination that a subject has LUAD cancer (optionally, LUAD cancer associated with an IHC test).

[0286] In some embodiments, the methods, kits, and systems of this disclosure are used to identify and detect novel SCLC or LUAD-related categories unrelated to IHC testing. For example, instead of training a classifier based on samples from a cohort defined by IHC testing, it is trained on samples from a cohort defined by whether or not a subject responds to a particular therapeutic agent. The resulting classifier is then used to identify subjects more likely to respond to the therapeutic agent without any IHC testing. Therefore, it should be understood that the term “SCLC / LUAD status” as used herein is not limited to SCLC and LUAD status based on IHC or other histological tests, but can also encompass any SCLC or LUAD-related category, including whether a subject responds to a particular therapeutic agent.

[0287] Those skilled in the art will understand that regular, preventative, and / or disease-preventive screening to determine SCLC / LUAD status improves cancer diagnosis, including and / or particularly early-stage cancer diagnosis. Therefore, this disclosure specifically provides methods, kits, and systems particularly useful for early cancer diagnosis and treatment. Generally, especially in embodiments where SCLC cancer testing is performed annually according to this disclosure, and / or where the subject is asymptomatic at the time of testing, the methods, kits, and systems of this disclosure are particularly likely to detect early-stage SCLC cancer, including transforming SCLC. In various embodiments, testing according to the methods, kits, and systems of this disclosure reduces cancer mortality, for example, through early cancer diagnosis. In some embodiments, detection according to the methods, kits, and systems of this disclosure is performed while a subject with LUAD cancer (or more generally NSCLC cancer) is treated with a therapeutic agent that can cause LUAD cancer (or more generally NSCLC cancer) to transform into SCLC cancer, for example, in epidermal growth factor receptor (EGFR) mutant LUAD cancer after treatment with a tyrosine kinase inhibitor (TKI), in anaplastic lymphoma kinase (ALK) positive LUAD cancer after treatment with an ALK inhibitor, and in wild-type EGFR or ALK LUAD cancer treated with immunotherapy.

[0288] In various implementations, the SCLC / LUAD status determination according to this disclosure may be performed once or multiple times on a given subject. In various implementations, the SCLC / LUAD status determination according to this disclosure is performed periodically, such as every six months, annually, every two years, every three years, every four years, every five years, or every ten years.

[0289] In various embodiments, the methods, kits, and systems disclosed herein provide for the determination of SCLC / LUAD status. In other cases, the methods, kits, and systems disclosed herein will indicate SCLC / LUAD status but cannot determine it. In all cases where the methods, kits, and systems of this disclosure are used to determine SCLC / LUAD status, further confirmatory assays may then be performed to confirm, support, refute, or reject the previously determined status, for example, the determination according to this disclosure. As used herein, confirmatory assays may be tests currently recognized by medical practitioners, such as tests based on IHC or other histological tests.

[0290] In various embodiments, cancer treatment is performed after determining the SCLC / LUAD status according to one or more methods, kits, and / or systems disclosed herein. In various embodiments, cancer treatment includes administering a treatment regimen comprising one or more cancer therapies provided herein, including but not limited to SCLC or LUAD therapy, surgery, radiation, endocrine therapy, chemotherapy, and / or immunotherapy. In various embodiments, cancer treatment includes administering a treatment regimen comprising one or more treatments provided herein, which are available, appropriate, and / or preferred for a particular SCLC / LUAD status.

[0291] In various implementations, methods, kits, and systems can be used to determine whether a particular subject and / or cancer is likely and / or characterized as responsive to SCLC or LUAD therapeutic agents. In some such implementations, the methods, kits, and systems can subsequently be used to treat the subject with SCLC or LUAD therapeutic agents.

[0292] In various implementations, methods, kits, and systems may be used to determine whether a particular subject and / or cancer is likely and / or characterized as resistant to, unresponsive to, or not recommended for treatment with SCLC or LUAD agents. In some such implementations, the methods, kits, and systems may be followed by treatment with one or more of surgery and / or radiation, HER2-targeted therapy (if HER2 positive), endocrine therapy (if hormone receptors such as estrogen receptors are positive), chemotherapy, and immunotherapy, instead of SCLC or LUAD agents.

[0293] Response can refer to the ability or likelihood of a therapy to shrink tumor size or inhibit tumor growth or metastasis. Response can refer to improved prognosis (e.g., prolonged time to cancer recurrence or extended life expectancy, such as extended overall survival, recurrence-free survival, metastasis-free survival, or disease-free survival). Response can refer to the realization of treatment benefits, including, for example, improvement in one or more symptoms of cancer, such as lung cancer. Response can be measured quantitatively (e.g., tumor size; measurements of histone modifications, chromatin accessibility, transcription factor binding, or DNA methylation at one or more genomic loci; or clinical benefit (CBR) calculations) or qualitatively (e.g., by metrics such as “pathological complete response” (pCR), “clinical complete response” (cCR), “clinical partial response” (cPR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD), or other qualitative criteria). Resistance can refer to the inability or improbability of a therapy to achieve the desired therapeutic effect in the subject and / or cancer (e.g., shrinking tumor size, improving prognosis, or other treatment benefits, such as, for example, improvement in one or more cancer symptoms). Resistance includes acquired resistance and natural resistance. In some implementations, resistance includes the extent to which one or more desired therapeutic benefits resulting from administration of the therapy to the subject and / or cancer are less than those anticipated and / or achieved in the reference (e.g., less than 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, or 10% of the benefits achieved in the reference).

[0294] In various implementations, methods, kits, and systems can be used to detect the clinical efficacy of cancer (e.g., lung cancer) treatments. For example, the methods and / or compositions of this disclosure can be used to determine whether a subject has lung cancer or SCLC / LUAD status during treatment. The methods and / or compositions disclosed herein may be used in conjunction with or confirmed by other methods for determining the presence of lung cancer or the SCLC / LUAD status of lung cancer, such as measuring the size or characteristics of the tumor by techniques such as CT, PET, mammography, ultrasound, palpation, histology, biopsy, or caliper measurement after surgical resection, or measuring the size or characteristics of the tumor by various qualitative, quantitative, or semi-quantitative scoring systems (including, but not limited to, those based on IHC testing, residual cancer burden (Symmans et al., J Clin Oncol (2007) 25:4414-4422, incorporated herein by reference in its entirety) or Miller-Payne score (Ogston et al., Breast (2003) 12:320-327, incorporated herein by reference in its entirety), in a qualitative manner (e.g., “pathological complete response” (pCR), “clinical complete response” (cCR), “clinical partial response” (cPR), “clinical stable disease” (cSD), or “clinical progressive disease” (cPD)).

[0295] In some embodiments, the methods, kits, and systems described herein can be used to monitor disease progression in subjects. In some embodiments, monitoring progression requires obtaining and characterizing samples from the subject at at least at a first time point and a second time point. In some embodiments, at the first time point, the subject has been diagnosed with lung cancer (e.g., SCLC or LUAD). In some embodiments, at the first time point, the subject has been diagnosed with lung cancer, and therapy was administered before or near the first time point (e.g., on the same day as the first time point) or between the first and second time points; in such embodiments, determining the SCLC / LUAD status at at least the first and second time points can be used to monitor treatment efficacy and / or determine when therapy should be changed. For example, in some embodiments, the subject has been diagnosed with LUAD at the first time point, is receiving or will receive LUAD therapy, and monitoring whether the disease status transitions to SCLC can be used, for example, to determine whether SCLC therapy should be changed. In some embodiments, treatment efficacy can be monitored, for example, by using the methods described herein to determine a decrease or increase in disease status signals, which may be useful in determining whether the administered therapy is effective and / or whether therapy should be changed. In some implementations, at the first time point, the subject's lung cancer has already been in remission (e.g., the subject has very little residual disease). In implementations where lung cancer has been in remission, the methods, kits, and systems described herein can be used, for example, to detect cancer recurrence, and may be faster, less costly, and / or less invasive compared to methods, for example, those relying on tissue biopsy and / or imaging techniques.

[0296] In some implementations, the methods, kits, and systems provided herein for determining SCLC / LUAD status can inform treatment and / or payment (e.g., medical expense reimbursement or reduction, such as testing or treatment) decisions and / or actions, for example, by individuals, healthcare institutions, healthcare practitioners, health insurance providers, government agencies, or other parties interested in healthcare costs.

[0297] In some implementations, the methods, kits, and systems provided herein for determining SCLC / LUAD status may inform health insurance providers in decisions regarding whether to reimburse healthcare payers or recipients, for example, for (1) the determination of SCLC / LUAD status itself (e.g., reimbursement for tests not otherwise available, reimbursement only for regular / routine tests, or reimbursement only for ad hoc and / or incidental tests); and / or for (2) treatment, including initiating, maintaining, and / or changing therapy, for example, based on the determined SCLC / LUAD status. For example, in some implementations, the methods, kits, and systems provided herein for determining SCLC / LUAD status are used as a basis, supplementary basis, or supporting basis for determining whether to provide reimbursement or cost reduction to healthcare payers or recipients. In some cases, a party seeking reimbursement or cost reduction may provide the results of an SCLC / LUAD status determination made according to this disclosure and make a request for such healthcare reimbursement or reduction. In some cases, the party deciding whether to provide reimbursement or relief for healthcare expenses will make its decision, in whole or in part, based on the results of receiving and / or reviewing the SCLC / LUAD status determination made pursuant to this disclosure.

[0298] In various embodiments, the determination of SCLC / LUAD status using the methods, kits, and systems disclosed herein can be used to classify subjects, samples, and / or tumors (e.g., lung cancer subjects, samples, and / or tumors). In various embodiments, the methods, kits, and systems disclosed herein can be used to generate a set of subjects, samples, and / or tumors identified according to the methods, kits, and systems of the present invention, each subject, sample, and / or tumor being classified to correspond to a specific SCLC / LUAD status, and optionally two or more such classifications of subjects, samples, and / or tumors are used to identify and distinguish these categories. Right now Biomarkers that differentiate subjects, samples, and / or tumors (e.g., based on their SCLC / LUAD status).

[0299] For illustrative purposes, but not limited to, in one exemplary assay of this disclosure, one or more samples (e.g., liquid biopsy samples containing cfDNA, e.g., plasma samples containing cfDNA) obtained from a subject are analyzed by a method comprising enriching cfDNA containing specific histone modifications, wherein enrichment is performed by incubating the sample with a reagent that specifically binds to the histone modifications to be enriched, and sequencing the enriched cfDNA. An example of such an assay is ChIP-seq for histone modifications (e.g., H3K4me3 and / or H3K27ac). Sequence reads (e.g., ChIP-seq sequence reads) can be aligned to human genome version hg19, for example using Burrows-WheelerAligner (BWA). Non-unique mappings and redundant reads are optionally discarded.

[0300] For example, MACS v2.1.1.20140616 can be used for sequence (e.g., ChIP-seq) peak recall with a q-value (FDR) threshold of 0.01. Sequence (e.g., ChIP-seq) data quality can optionally be assessed using one or more of a variety of metrics, including total number of peaks, FRiP (fraction of reads in a peak) score, number of high-confidence peaks (e.g., >10-fold enrichment over background), and percentage overlap of peaks with “blacklisted” DHS peaks from the ENCODE project (Amemiya et al., Sci Rep (2019) 9(1):9354). If sequence (e.g., ChIP-seq) data quality falls below a certain threshold, the data may be discarded and the assay repeated. Sequence (e.g., ChIP-seq) peaks overlapping with selected genomic sites that are differentially modified for relevant histone modifications (Tables 1-2) as provided in this paper can be used to determine SCLC / LUAD status. The number of reads overlapping with selected genomic sites with relevant histone modifications can be summed, for example, in some embodiments, selecting all differentially modified genomic sites with an absolute log2 (fold change) ≥ 4.0. In some embodiments, the average number of reads in the local background of each ChIP-seq peak is subtracted to improve the signal-to-noise ratio. In some embodiments, the read density of one or more histone modifications can be calculated by including: (1) summing the background adjustment sequence counts at one or more genomic sites and dividing the sum by the total number of kilobases at one or more genomic sites; or (2) for each genomic site, determining the ratio of the background adjustment fragment count to the number of kilobases at the genomic site and then summing the ratios for each site. In some embodiments, the method includes determining an SCLC / LUAD ratio score, for example, by including: (a) calculating the SCLC read density, calculating the LUAD read density, and dividing the SCLC read density by the LUAD read density. In some embodiments, SCLC sequence read density can be determined by methods including: calculating sequence read densities using one or more genomic loci, which have increased epigenetic modifications in samples obtained from one or more subjects with LUAD compared to samples obtained from one or more subjects with SCLC. In some embodiments, LUAD sequence read density can be determined by methods including: calculating sequence read densities using one or more genomic loci, which have increased epigenetic modifications in samples obtained from one or more subjects with LUAD compared to samples obtained from one or more subjects with SCLC. An SCLC / LUAD ratio score is used to determine one or more histone modifications.In some embodiments, the SCLC / LUAD ratio score for H3K4me3 modification is determined. In some embodiments, the SCLC / LUAD ratio score for H3K27ac modification is determined. In some embodiments, the SCLC / LUAD ratio score for methylated DNA is determined. In some embodiments, the SCLC / LUAD ratio scores for H3K4me3 modification and H3K27ac modification, H3K4me3 and methylated DNA, or H3K27ac and methylated DNA are determined. In some embodiments, the SCLC / LUAD ratio score for each of H3K4me3 modification, H3K27ac modification, and methylated DNA is determined. In some embodiments, the SCLC / LUAD ratio scores for two or more different epigenetic modifications can be combined. In some embodiments, fitted values ​​determined by logistic regression can be used to combine each ratio score.

[0301] The data can then be log2 transformed and quantile normalized to match the data distribution used to train the classifier. The normalized data can be used as input to a classifier trained using the same histone modifications and selected genomic sites. The classifier can then use the input data to determine the SCLC / LUAD status of the subject's cancer. It should be understood that this or similar methods can be applied to the assays of quantifying chromatin accessibility, transcription factor binding, and / or DNA methylation as described in this disclosure.

[0302] In some implementations, multiple epigenetic markers (e.g., one or more histone modifications, chromatin accessibility, binding to one or more transcription factors, and / or DNA methylation) can be quantified in a single sample. In such implementations, two or more epigenetic marker assays can be performed sequentially (meaning each modification can be detected sequentially in a single sample) or in parallel (meaning a single sample can be split into multiple fractions and each fraction can be analyzed to quantify the epigenetic modification). In some implementations, H3K4me3 and H3K27ac histone modifications; H3K4me3 modification and DNA methylation; H3K27ac modification and DNA methylation; or H3K4me3 modification, H3K27ac histone modification, and DNA methylation are quantified in a single sample.

[0303] To avoid any doubt, those skilled in the art will understand from this disclosure that the methods, kits, and systems for determining SCLC / LUAD status disclosed herein are for at least in vitro use. Therefore, all aspects and embodiments of this disclosure can be at least... exist Performed and / or used in vitro.

[0304] Those skilled in the art will also understand that, in some embodiments, the methods of this disclosure may be implemented on and / or in conjunction with computer programs and computer systems. In some embodiments, the methods of this disclosure may be implemented on and / or in conjunction with a non-transient computer-readable storage medium coded with a computer program, wherein the program contains instructions that, when executed by one or more processors, cause the one or more processors to perform operations to execute the methods. The computer system may also store and manipulate data generated by the methods of this disclosure, including multiple genomic site modification states and / or accessibility state changes / profiles, which the computer system may use to implement the methods disclosed herein. In some embodiments, the computer system (i) receives modification state and / or accessibility state data; (ii) stores the data; and (iii) compares the data in any of the various ways described herein (e.g., analysis relative to a suitable reference), for example, to determine SCLC / LUAD status. In some implementations, the computer system (i) compares the genomic site modification and / or accessibility status with a reference; and (ii) outputs an indication of whether the genomic site modification status and / or accessibility status differs significantly from the reference, and / or provides a determination of the SCLC / LUAD status.

[0305] Based on the knowledge possessed by those skilled in the art of bioinformatics and / or computer science, various types of computer systems can be used to implement the methods of this disclosure. During the operation of such a computer system, several software components can be loaded into memory. These software components may include standard software components in the art and components specific to this disclosure (e.g., the dCHIP software described in Lin et al., Bioinformatics (2004) 20:1233-1240, which is incorporated herein by reference in its entirety; radial basis function (RBM) algorithms known in the art). The methods of this disclosure can also be programmed or modeled in mathematical software packages that allow symbolic input equations and advanced processing specifications, including specific algorithms to be used, thereby eliminating the need for users to programmatically write individual equations and algorithms. Such software packages include, for example, Matlab from Mathworks (Natick, MA), Mathematica from Wolfram Research (Champaign, IL), S-Plus from MathSoft (Seattle, WA), R from the R Foundation for Statistical Computation (Vienna, Austria), Python from the Python Software Foundation (Wilmington, DE), or Perl from the Perl Foundation (Holland, MI). In some embodiments, the computer system includes a database for storing data on the status and / or accessibility of genomic site modifications. Such stored files can then be accessed and used for comparisons of interest. Other alternative program structures and computer systems, besides those exemplary described herein, will readily be apparent to those skilled in the art.

[0306] As illustrated in the embodiments, various algorithms can be applied to compare the modification status and / or accessibility status of genomic loci between a sample and a reference sample, where the genomic loci are differentially modified in SCLC or LUAD cancers. In various embodiments, the algorithm may be a single learned statistical classifier system. Other suitable statistical algorithms are well known to those skilled in the art. For example, a learned statistical classifier system includes a machine learning algorithm technique capable of adapting to complex datasets (e.g., a set of genomic loci of interest) and making decisions based on such datasets. In some embodiments, a single learned statistical classifier system, such as a classification tree (e.g., a random forest), is used. In other embodiments, combinations of 2, 3, 4, 5, 6, 7, 8, 9, 10, or more learned statistical classifier systems are preferably used in tandem. Examples of learning statistical classifier systems include, but are not limited to, those systems described in the embodiments, as well as systems using: inductive learning (e.g., decision / classification trees, such as random forests, classification and regression trees (C&RT), boosting trees, etc.), probabilistic approximate correct (PAC) learning, connectionist learning (e.g., neural networks (NN), artificial neural networks (ANN), neural fuzzy networks (NFN), network structures, perceptrons such as multilayer perceptrons, multilayer feedforward networks, applications of neural networks, Bayesian learning in belief networks, etc.), reinforcement learning (e.g., passive learning in known environments such as naive learning, adaptive dynamic learning and temporal difference learning, passive learning in unknown environments, active learning in unknown environments, learning action-value functions, applications of reinforcement learning, etc.), and genetic algorithms and evolutionary programming. Other learned statistical classifier systems include support vector machines (e.g., kernel methods), multivariate adaptive regression splines (MARS), Levenberg-Marquardt algorithms, Gauss-Newton algorithms, mixtures of Gaussians, gradient descent, and learned vector quantization (LVQ). In some implementations, the methods of this disclosure may include sending classification results to medical practitioners, such as oncologists.

[0307] In various implementation schemes, the area under the recipient operating characteristic curve (AUROC) used to determine whether a subject has a specific condition (e.g., SCLC cancer vs. LUAD cancer) is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95).

[0308] Preparation and administration of therapeutic agents This disclosure includes methods for administering therapeutic agents or regimens to subjects based on their SCLC / LUAD status in lung cancer. Generally, the therapeutic agents or regimens provided herein are available, suitable, and / or preferred for the identified SCLC / LUAD status. Those skilled in the art will understand the recommended and / or government-approved formulations and / or dosages of the various therapeutic agents provided herein.

[0309] This disclosure includes pharmaceutical compositions for delivering one or more therapeutic agents to a subject. As disclosed herein, the pharmaceutical composition may be any form known in the art, including formulations administered via any route known in the art. An appropriate method of administration may be selected based on the subject's age and medical condition.

[0310] The pharmaceutical compositions disclosed herein may be in the form of, for example, liquid, semi-solid, and solid dosage forms. The pharmaceutical compositions disclosed herein may be in the form of, for example, liquid solutions (e.g., injectable and infusionable solutions), dispersions or suspensions, tablets, pills, powders, and liposomes. The choice or use of any particular form may depend in part on the intended route of administration and therapeutic application. Therefore, the compositions may be formulated for administration via parenteral route (e.g., intravenous, subcutaneous, intraperitoneal, or intramuscular injection) or non-parenteral route. As used herein, parenteral administration refers to a route of administration other than enteral and local administration, typically by injection or infusion.

[0311] In some embodiments, the compositions provided herein are available in unit dosage forms suitable for self-administration. Such unit dosage forms may be provided in containers such as tablets, vials, cartridges, pre-filled syringes, or disposable injection pens.

[0312] The pharmaceutical compositions disclosed herein may be in injectable or infusion-ready forms. For example, this disclosure includes sterile formulations for injection or infusion that can be formulated according to conventional pharmaceutical practices. A sterile solution can be prepared by incorporating the desired amount of the composition described herein with one of the ingredients listed above or a combination thereof into a suitable solvent, followed by filtration sterilization as needed. For example, an isotonic solution containing glucose and other supplements (such as D-sorbitol, D-mannose, D-mannitol, or sodium chloride) can be used as an aqueous solution for injection, optionally combined with a suitable solubilizer (e.g., alcohols such as ethanol and / or polyols such as propylene glycol or polyethylene glycol and / or nonionic surfactants such as polysorbate 80™ or HCO-50, etc.). In the case of sterile powders used to prepare sterile injectable solutions, the preparation methods include vacuum drying and freeze-drying, which produce a powder of the composition described herein plus any additional desired ingredients (see below) from its previously sterile filtered solution. Appropriate solution fluidity can be achieved, for example, by using coatings such as lecithin, by maintaining the desired particle size in the case of dispersions, and by using surfactants. Extended absorption of injectable compositions can be achieved by including, for example, monostearate and gelatin as agents that extend absorption. In certain cases, pharmaceutical compositions can be formulated into buffer solutions, for example, at suitable concentrations and suitable for storage (e.g., at 2-8°C (e.g., 4°C)).

[0313] In various embodiments, the pharmaceutical compositions of this disclosure can be formulated as solutions, microemulsions, dispersions, liposomes, or other ordered structures suitable for stable storage at high concentrations. Typically, dispersions are prepared by incorporating the compositions described herein into a sterile medium containing an alkaline dispersion medium and the other desired components listed above.

[0314] In various cases, pharmaceutical compositions may be formulated to include pharmaceutically acceptable carriers or excipients. Pharmaceutically acceptable carriers include, but are not limited to, any and all physiologically compatible solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic agents, and absorption delay agents.

[0315] In some embodiments, compositions can be formulated with a carrier that prevents rapid release of the therapeutic agent, such as controlled-release formulations comprising an implant and a microencapsulated delivery system. Biodegradable, biocompatible polymers such as ethylene vinyl acetate, polyanhydride, polyglycolic acid, collagen, polyorthoester, and polylactic acid can be used. Many methods for preparing such formulations are known in the art. See, for example, JR Robinson (1978) “Sustained and Controlled Release Drug Delivery Systems,” Marcel Dekker, Inc., New York.

[0316] The route of administration can be parenteral, such as by injection. Injection administration can be via intravenous injection, intramuscular injection, intraperitoneal injection, or subcutaneous injection. Administration can be systemic or local. In some embodiments, the compositions described herein can be therapeutically delivered to a subject via local administration. As used herein, “local administration” or “local delivery” means delivery that does not rely on the delivery of the composition or therapeutic agent to its intended target tissue or site via the vascular system. For example, the composition can be delivered by injection or implantation of the composition or therapeutic agent or by injection or implantation of a device containing said composition or therapeutic agent. In some embodiments, after local administration near a target tissue or site, the composition or therapeutic agent or one or more components thereof may diffuse to the intended target tissue or site, which is not the site of administration.

[0317] Pharmaceutical compositions can be administered parenterally in the form of injectable formulations comprising a sterile solution or suspension in water or another pharmaceutically acceptable liquid. For example, a pharmaceutical composition can be formulated by suitably combining a therapeutic molecule with a pharmaceutically acceptable medium or medium (such as sterile water and saline, vegetable oil, emulsifier, suspending agent, surfactant, stabilizer, flavoring excipient, diluent, carrier, preservative, binder) and then mixing them in a unit dose form required by generally accepted pharmaceutical practice. Examples of oily liquids include sesame oil and soybean oil, and it can be combined with benzyl benzoate or benzyl alcohol as a solubilizer. Other items that may be included are buffers (such as phosphate buffers or sodium acetate buffers), analgesics (such as procaine hydrochloride), stabilizers (such as benzyl alcohol or phenol), and antioxidants. The formulated injectable can be packaged in suitable ampoules.

[0318] In various implementations, subcutaneous administration can be achieved by devices such as syringes, pre-filled syringes, autoinjectors (e.g., disposable or reusable), injection pens, patch syringes, wearable syringes, portable syringe infusion pumps with subcutaneous infusion devices, or other devices that combine with therapeutic agents for subcutaneous injection.

[0319] The injection system disclosed herein may employ a delivery pen as described in U.S. Patent No. 5,308,341. Insulin pens are most commonly used for self-delivering insulin to diabetic patients and are well known in the art. Such devices may include at least one injection needle, typically pre-filled with one or more therapeutic unit doses of solution containing a therapeutic agent, and may be used to rapidly deliver the solution to the subject with minimal pain. A drug delivery pen includes a vial holder into which a vial containing a therapeutic agent or other medication may be housed. The injection pen may be a fully mechanical device or may be combined with electronic circuitry to precisely set and / or indicate the dosage of medication injected into the user. See, for example, U.S. Patent No. 6,192,891. In some embodiments, the needle of the pen device is disposable, and the kit includes one or more disposable replacement needles. Pen devices suitable for delivering any of the currently characteristic compositions are also described, for example, in U.S. Patent Nos. 6,277,099; 6,200,296; and 6,146,361, the disclosure of each of which is incorporated herein by reference in its entirety. For example, U.S. Patent No. 7,556,615 describes a microneedle-based pen device, the disclosure of which is incorporated herein by reference in its entirety. See also the MOLLY precision pen injector (PPI) device manufactured by Scandinavian Health Ltd. TM .

[0320] In some embodiments, administration of the therapeutic agent as described herein is achieved by administering to a subject a nucleic acid encoding the therapeutic agent described herein. The nucleic acid encoding the therapeutic agent described herein may be incorporated into a gene construct as part of a gene therapy regimen to deliver the nucleic acid, which may be used for intracellular expression and production of the therapeutic agent. Expression constructs of such components may be administered in any therapeutically effective carrier, such as any formulation or composition capable of effectively delivering the component gene in vivo to cells. Methods include inserting the subject gene into a viral vector, including recombinant retroviruses, adenoviruses, adeno-associated viruses, lentiviruses, and herpes simplex virus-1 (HSV-1), or recombinant bacterial or eukaryotic plasmids. The viral vector may be directly transfected into cells; plasmid DNA may be delivered using, for example, cationic liposomes (liposomal transfection agents) or derived polylysine conjugates, Gramin S, artificial viral envelopes, or other such intracellular carriers, or directly injected with the gene construct or CaPO4 precipitation. Examples of suitable retroviruses include adenovirus-derived vectors, adeno-associated viruses (AAV), pLJ, pZIP, pWE, and pEM, which are known to those skilled in the art.

[0321] In some embodiments, the composition may be formulated for storage at temperatures below 0°C (e.g., -20°C or -80°C). In some embodiments, the composition may be formulated for storage at 2-8°C (e.g., 4°C) for up to 2 years (e.g., one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, ten months, eleven months, one year, or two years). Therefore, in some embodiments, the composition described herein is stable when stored at 2-8°C (e.g., 4°C) for at least one year.

[0322] Pharmaceutical compositions may contain a therapeutically effective amount of the therapeutic agent described herein. Such effective amounts can be readily determined by those skilled in the art. A therapeutically effective amount is the amount by which any toxic or harmful effects of the composition outweigh the beneficial therapeutic effects. In some embodiments, the dosage may also be selected to reduce or avoid the production of antibodies or other host immune responses against the therapeutic agent. Those skilled in the art will understand that data obtained from cell culture assays and animal studies can be used to formulate dosage ranges for human use. In various embodiments, the amount of active ingredient contained in the pharmaceutical composition allows for the administration of an appropriate dose within a specified range to a subject. The dosage and method of administration may depend on the patient's weight, age, condition, and other characteristics, and may be appropriately selected as needed by those skilled in the art.

[0323] Pharmaceutical compositions, including certain therapeutic agents such as therapeutic antibodies, may be administered at a fixed dose or at a dose of milligrams per kilogram (mg / kg). While not intended to be limiting, exemplary single doses of certain pharmaceutical compositions described herein may include certain therapeutic agents as described herein, in amounts equivalent to, for example, 0.001 mg / kg to 1000 mg / kg, 1-1000 mg / kg, 1-100 mg / kg, 0.5-50 mg / kg, 0.1-100 mg / kg, 0.5-25 mg / kg, 1-20 mg / kg, and 1-10 mg / kg body weight. Exemplary doses of the compositions described herein include, but are not limited to, 0.1 mg / kg, 0.5 mg / kg, 1 mg / kg, 2 mg / kg, 4 mg / kg, 8 mg / kg, or 20 mg / kg. This disclosure is not limited to such ranges or doses.

[0324] This disclosure further includes methods for preparing the pharmaceutical compositions of this disclosure and kits comprising the pharmaceutical compositions of this disclosure.

[0325] In various embodiments, the therapeutic agents of this disclosure may be administered to a subject, and the treatment process may further include the administration of one or more other therapeutic agents or non-therapeutic agents (e.g., surgery or radiation). Combination therapies of this disclosure may include therapeutic agents that simultaneously expose a subject to two or more treatment options.

[0326] In some embodiments, the therapeutic agent as described herein may be administered together with other agents or therapies (e.g., simultaneously and / or with the same composition). In some embodiments, the therapeutic agent of this disclosure may be administered separately from additional therapeutic agents or therapies (e.g., at a different time or with a different composition than the additional therapeutic agent or therapy). The dosing regimen of the therapeutic agent and one or more additional therapeutic agents administered therewith may be determined in a coordinated manner or independently. In various embodiments, as described herein, additional therapeutic agents or therapies administered in combination with the therapeutic agent may be administered simultaneously with the therapeutic agent, on the same day as the therapeutic agent, or in the same week as the therapeutic agent. In various embodiments, additional therapeutic agents or therapies may be administered in combination with the therapeutic agent as described herein, such that the interval between administration of the therapeutic agent and the additional therapeutic agent or therapy is one or more hours before and after administration of the therapeutic agent, one or more days before and after administration of the therapeutic agent, one or more weeks before and after administration of the therapeutic agent, or one or more months before and after administration of the therapeutic agent. In various embodiments, the frequency and / or dosage of administration of one or more additional therapeutic agents may be the same as, similar to, or different from the frequency of administration of the therapeutic agent. In some embodiments, two or more regimens may be administered simultaneously; in some embodiments, such regimens may be administered sequentially (e.g., all “doses” of the first regimen are administered before any dose of the second regimen is administered); in some embodiments, such therapeutic agents are administered in an overlapping dosing regimen.

[0327] In some implementations, the subject to which the therapeutic agent is administered may be a subject who has previously received, is scheduled to receive, or is currently receiving a treatment regimen including additional cancer therapies. In some cases, combining the administration of one therapeutic agent may improve the delivery or efficacy of another therapeutic agent or therapy.

[0328] It is believed that combination therapy can exhibit a synergistic and / or greater additive effect when a therapeutic agent is administered in combination with one or more additional therapeutic agents. The therapeutic agent can be administered at any independently determined effective amount, or at any effective amount determined by the combined effect of the administered therapeutic agent with one or more additional therapeutic agents or therapies. In some embodiments, administration of the therapeutic agent may reduce the therapeutically effective dose, required dose, or administered dose of the additional therapeutic agent or therapy relative to a reference administration regimen of the additional therapeutic agent or therapy or a therapy without the therapeutic agent. In some embodiments, the compositions described herein may replace or enhance other previously or currently administered therapies. For example, after treatment with the therapeutic agent, administration of one or more additional therapeutic agents or therapies may be stopped or reduced, for example, administered at a lower level.

[0329] Reagent test kit This disclosure includes kits for detecting modifications and / or accessibility at one or more genomic sites. In some embodiments, this disclosure provides kits for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic sites. Kits of this disclosure may include, for example, reagents for detecting and quantifying histone modifications, such as buffers and / or antibodies. In some embodiments, kits of this disclosure may include at least one antibody that selectively binds to histone modifications selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, or H3K4me3, or panacetylation. In some embodiments, kits of this disclosure may include at least one antibody that selectively binds to H3K4me3 modifications. In some embodiments, kits of this disclosure may include at least one antibody that selectively binds to H3K27ac modifications. Kits of this disclosure may include explanatory material that discloses or describes the use of the kit in determining the SCLC / LUAD status and / or treatment disclosed herein. In various embodiments, the kits disclosed herein may include one or more therapeutic agents that can be used to treat cancer, for example, optionally combined with illustrative materials for the treatment of lung cancer based on SCLC / LUAD status as disclosed herein.

[0330] In some embodiments, the kits disclosed herein include reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic sites, wherein one or more genomic sites are selected from Tables 1 to 13, for example, Tables 1 to 3.

[0331] In some embodiments, the kit includes reagents for quantifying H3K4me3 at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the kit includes reagents for quantifying H3K27ac at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the kit includes reagents for quantifying H3K27ac at at least 1, 2, 3, or 4 genomic loci in Table 4. In some embodiments, the kit includes reagents for quantifying H3K4me3 or H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5. In some embodiments, the kit includes reagents for quantifying H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 6. In some embodiments, the kit includes reagents for quantifying H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 7. In some embodiments, the kit includes reagents for quantifying H3K4me3 at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 12. In some embodiments, the kit includes reagents for quantifying H3K4me3 at at least 5, 10, or 18 genomic loci in Table 13. In some embodiments, the kit includes one or more antibodies for ChIP-seq, optionally said antibodies specifically binding to H3K4me3 or H3K27ac-modified histones.

[0332] In some embodiments, the kit includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3. In some embodiments, the kit includes reagents for quantifying DNA methylation at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5. In some embodiments, the kit includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 8. In some embodiments, the kit includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 9. In some embodiments, the kit includes one or more methyl-binding domains (e.g., for MBD-seq). In some embodiments, the kit includes one or more antibodies capable of binding methylated DNA (e.g., for MeDIP).

[0333] In some embodiments, the kit includes reagents for measuring chromatin accessibility at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 10. In some embodiments, the kit includes reagents for measuring chromatin accessibility at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 11. In some embodiments, the kit includes reagents for measuring chromatin accessibility via ATAC-seq assay.

[0334] In some embodiments, the kit includes reagents for isolating cell-free DNA (cfDNA) from liquid biopsy samples. In some embodiments, the kit includes reagents for sequencing library preparation. In some embodiments, the kit includes reagents for sequencing. In some embodiments, the kit includes instructions for determining whether a subject has SCLC or LUAD cancer.

[0335] system This disclosure includes systems for detecting modifications and / or accessibility at one or more genomic loci. In some embodiments, this disclosure provides systems for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic loci. Systems of this disclosure may include: a sequencer configured to generate sequencing datasets from a sample; and a non-transient computer-readable storage medium and / or a computer system.

[0336] In some embodiments, a non-transient computer-readable storage medium is encoded with a computer program containing instructions that, when executed by one or more processors, cause the one or more processors to perform operations to execute the methods of this disclosure.

[0337] In some implementations, the computer system includes a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform the methods of this disclosure.

[0338] In some embodiments, the sequencer is configured to generate whole-genome sequencing (WGS) datasets from a sample. In some embodiments, the system also includes a sample preparation device configured to prepare a sample for sequencing from a biological sample (optionally, a liquid biopsy sample). The sample preparation device may include reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic sites in cell-free DNA (cfDNA) from the biological sample (optionally, a liquid biopsy sample).

[0339] The systems disclosed herein may include, for example, reagents such as buffers and / or antibodies, for detecting and quantifying histone modifications. In some embodiments, the systems disclosed herein may include at least one antibody that selectively binds to histone modifications selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, or H3K4me3, or panacetylation. In some embodiments, the systems disclosed herein may include at least one antibody that selectively binds to H3K4me3 modifications. In some embodiments, the systems disclosed herein may include at least one antibody that selectively binds to H3K27ac modifications. The systems disclosed herein may include explanatory materials that disclose or describe the use of the system in determining the SCLC / LUAD status and / or treatment disclosed herein.

[0340] In some embodiments, the system disclosed herein includes reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic sites, wherein one or more genomic sites are selected from Tables 1 to 13, for example, Tables 1 to 3.

[0341] In some embodiments, the system includes reagents for quantifying H3K4me3 at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the system includes reagents for quantifying H3K27ac at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the system includes reagents for quantifying H3K27ac at at least 1, 2, 3, or 4 genomic loci in Table 4. In some embodiments, the system includes reagents for quantifying H3K4me3 or H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5. In some embodiments, the system includes reagents for quantifying H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 6. In some embodiments, the system includes reagents for quantifying H3K27ac at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 7. In some embodiments, the system includes reagents for quantifying H3K4me3 at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 12. In some embodiments, the system includes reagents for quantifying H3K4me3 at at least 5, 10, or 18 genomic loci in Table 13. In some embodiments, the system includes one or more antibodies for ChIP-seq, optionally said antibodies specifically binding to H3K4me3 or H3K27ac-modified histones.

[0342] In some embodiments, the system includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3. In some embodiments, the system includes reagents for quantifying DNA methylation at at least 5, 10, 15, 20, 25, or 30 genomic loci in Table 5. In some embodiments, the system includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 8. In some embodiments, the system includes reagents for quantifying DNA methylation at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 9. In some embodiments, the system includes one or more methyl-binding domains (e.g., for MBD-seq). In some embodiments, the system includes one or more antibodies capable of binding methylated DNA (e.g., for MeDIP).

[0343] In some embodiments, the system includes reagents for isolating cell-free DNA (cfDNA) from liquid biopsy samples. In some embodiments, the sequencer includes reagents for preparing sequencing libraries. In some embodiments, the sequencer includes reagents for sequencing. In some embodiments, the system includes instructions for determining whether a subject has SCLC or LUAD cancer.

[0344] In some embodiments, the system includes reagents for measuring chromatin accessibility at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 10. In some embodiments, the system includes reagents for measuring chromatin accessibility at at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 11. In some embodiments, the system includes reagents for measuring chromatin accessibility via ATAC-seq.

[0345] The foregoing description of illustrative embodiments of the systems and methods disclosed herein refers to computations performed locally by a computing device. However, computations performed over a network are also contemplated. Figure 10 An illustrative network environment 1000 for use in the methods and systems described herein is shown. In a brief overview, reference is now made to... Figure 10A block diagram illustrating an illustrative cloud computing environment 1000 is shown and described. The cloud computing environment 1000 may include one or more resource providers 1002a, 1002b, 1002c (collectively referred to as 1002). Each resource provider 1002 may include computing resources. In some implementations, computing resources may include any hardware and / or software for processing data. For example, computing resources may include hardware and / or software capable of executing algorithms, computer programs, and / or computer applications. In some embodiments, the illustrative computing resources may include application servers and / or databases with storage and retrieval capabilities. Each resource provider 1002 may be connected to any other resource provider 1002 in the cloud computing environment 1000. In some implementations, resource providers 1002 may be connected via a computer network 1008. Each resource provider 1002 may be connected via the computer network 1008 to one or more computing devices 1004a, 1004b, 1004c (collectively referred to as 1004).

[0346] The cloud computing environment 1000 may include a resource manager 1006. The resource manager 1006 can be connected to resource providers 1002 and computing devices 1004 via a computer network 1008. In some implementations, the resource manager 1006 may facilitate one or more resource providers 1002 to provide computing resources to one or more computing devices 1004. The resource manager 1006 may receive requests for computing resources from a specific computing device 1004. The resource manager 1006 may identify one or more resource providers 1002 capable of providing the computing resources requested by the computing device 1004. The resource manager 1006 may select a resource provider 1002 to provide computing resources. The resource manager 1006 may facilitate a connection between the resource provider 1002 and the specific computing device 1004. In some implementations, the resource manager 1006 may establish a connection between a specific resource provider 1002 and a specific computing device 1004. In some implementations, the resource manager 1006 may redirect a particular computing device 1004 to a particular resource provider 1002 that has requested computing resources.

[0347] Figure 11 Examples of computing devices 1100 and 1150 that can be used in the methods and systems described in this disclosure are shown. Computing device 1100 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. Mobile computing device 1150 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are intended only as examples and not as limitations.

[0348] The computing device 1100 includes a processor 1102, a memory 1104, a storage device 1106, a high-speed interface 1108 connected to the memory 1104 and a plurality of high-speed expansion ports 1110, and a low-speed interface 1112 connected to a low-speed expansion port 1114 and the storage device 1106. Each of the processor 1102, memory 1104, storage device 1106, high-speed interface 1108, high-speed expansion port 1110, and low-speed interface 1112 is interconnected using various buses and may be mounted on a common motherboard or otherwise mounted as appropriate. The processor 1102 can process instructions (including instructions stored in the memory 1104 or storage device 1106) for execution within the computing device 1100 to display graphical information of a GUI on an external input / output device, such as a display 1116 coupled to the high-speed interface 1108. In other embodiments, multiple processors and / or multiple buses may be used together with multiple memories and various types of memory as appropriate. Additionally, multiple computing devices can be connected, each providing a portion of the necessary operation (e.g., as a server group, a set of blade servers, or a multiprocessor system). Therefore, as used herein, when multiple functions are described as being performed by a “processor,” this covers implementations where the multiple functions are performed by any number of processors (e.g., one or more processors) of any number of computing devices (e.g., one or more computing devices). Furthermore, when a function is described as being performed by a “processor,” this covers implementations where said function is performed by any number of processors (e.g., one or more processors) of any number of computing devices (e.g., one or more computing devices) (e.g., in a distributed computing system).

[0349] Memory 1104 stores information within computing device 1100. In some implementations, memory 1104 is one or more volatile memory cells. In some embodiments, memory 1104 is one or more non-volatile memory cells. Memory 1104 may also be another form of computer-readable medium, such as a magnetic disk or optical disk.

[0350] Storage device 1106 provides large-capacity storage for computing device 1100. In some implementations, storage device 1106 may be or contain computer-readable media, such as hard disk drives, optical disk drives, flash memory or other similar solid-state storage devices, or device arrays, including those in a storage area network or other configuration. Instructions may be stored in an information carrier. When executed by one or more processing devices (e.g., processor 1102), the instructions are performed in one or more ways, such as those described above. Instructions may also be stored by one or more storage devices, such as computer or machine-readable media (e.g., memory 1104, storage device 1106, or memory on processor 1102).

[0351] High-speed interface 1108 manages bandwidth-intensive operations of computing device 1100, while low-speed interface 1112 manages lower bandwidth-intensive operations. This allocation of functions is merely an example. In some embodiments, high-speed interface 1108 is coupled to memory 1104, display 1116 (e.g., via a graphics processor or accelerator), and to high-speed expansion port 1110, which accepts various expansion cards (not shown). In embodiments, low-speed interface 1112 is coupled to storage device 1106 and low-speed expansion port 1114. Low-speed expansion port 1114, which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, Wireless Ethernet), may be coupled to one or more input / output devices, such as keyboards, pointing devices, scanners, or networking devices (such as switches or routers), for example, via a network adapter.

[0352] The computing device 1100 can be implemented in a variety of different forms, as shown in the figure. F...

Claims

1. A method for determining the SCLC / LUAD status in a subject with lung cancer, the method comprising: Quantifying one or more epigenetic biomarkers at one or more genomic loci in a liquid biopsy sample obtained from or derived from the subject, wherein the one or more epigenetic biomarkers include: (a) One or more histone modifications, (b) Chromatin accessibility, (c) The binding of one or more transcription factors, and (d) DNA methylation; and The SCLC / LUAD status of the lung cancer in the subject is determined by comparing the levels of one or more epigenetic biomarkers at one or more genomic loci with reference values. The one or more genomic loci mentioned therein include (i) one or more genomic loci in subjects with SCLC whose levels of one or more of the aforementioned epigenetic biomarkers are elevated compared to subjects with LUAD; and / or (ii) one or more genomic loci in subjects with LUAD whose levels of one or more of the aforementioned epigenetic biomarkers are elevated compared to subjects with SCLC.

2. The method of claim 1, wherein: (a) The liquid biopsy sample is a plasma sample, serum sample, or urine sample; (b) The method includes isolating cfDNA from approximately 1 mL of the liquid biopsy sample (e.g., a plasma sample), and / or (c) The sample contains a detectable amount of ctDNA (e.g., where the estimated tumor fraction of the cfDNA is >3%, e.g., as determined by iChorCNA).

3. The method of claim 1 or 2, wherein the one or more histone modifications are quantified using a histone modification assay, the assay measuring one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, H3K4me3 and panacetylation (e.g., H3K4me3 and H3K27ac).

4. The method according to any one of claims 1 to 3, wherein: (a) The one or more histone modifications are quantified using assays selected from the following: ChIP-seq (chromatin immunoprecipitation sequencing), CUT&RUN (target cleavage and nuclease release) sequencing and CUT&Tag (target cleavage and fragmentation labeling) sequencing. (b) The chromatin accessibility was quantified using a selection of the following chromatin accessibility assays: ATAC-seq (transposon-accessible chromatin sequencing assay), NOMe-seq (nucleosome occupancy and methylome sequencing), FAIRE-seq (formaldehyde-assisted separation of regulatory elements sequencing), MNase-seq (micrococcal nuclease digestion sequencing), and DNase hypersensitivity assay. (c) The binding of one or more transcription factors is quantified using a transcription factor binding assay that detects the binding of one or more of p300, mediator complex, cohesin complex, RNA pol II, FOXA1, ESR1, PR, MYC, EN1, FOXM1, KLF4, AP-2, RARA, or RUNX1, optionally wherein the transcription factor binding assay is selected from ChIP-seq (chromatin immunoprecipitation sequencing), CUT&RUN (target cleavage and nuclease release) sequencing, and CUT&Tag (target cleavage and fragmentation labeling) sequencing; and / or (d) DNA methylation was quantified using bisulfite sequencing (BS-Seq), whole-genome bisulfite sequencing (WGBS), methylated DNA immunoprecipitation sequencing (MeDIP-seq), or methyl-CpG-binding domain sequencing (MBD-seq).

5. The method of any one of claims 1 to 4, wherein the method comprises: (a) Quantify H3K4me3 modifications at one or more genomic sites using a assay that includes enriching cfDNA containing one or more H3K4me3 modifications (e.g., using a method that includes incubation with an agent that binds to H3K4me3 modifications) and sequencing the cfDNA enriched for H3K4me3 modifications to determine the sequence counts of sequences having one or more H3K4me3 modifications. (b) Quantify H3K27ac modifications at one or more genomic sites using a assay that includes enriching cfDNA containing one or more H3K27ac modifications (e.g., using a method that includes incubation with an agent that binds to H3K27ac modifications) and sequencing the cfDNA enriched for H3K27ac modifications to determine the sequence counts of sequences having one or more H3K27ac modifications. and / or (c) Quantifying methylated DNA at one or more genomic sites using a assay comprising: enriching methylated cfDNA (e.g., using a method comprising incubating with an agent that binds to methylated DNA), and sequencing said enriched cfDNA to determine a sequence count having one or more methylated nucleotides; and Optional location: (d) If the method includes using an agent that binds to H3K4me3 modification, an agent that binds to H3K27ac modification, and / or an agent that binds to methylated DNA, the agent is attached (e.g., via covalent or non-covalent bonds) to a physical support (e.g., beads, magnetic beads, agarose beads, or magnetic epoxy beads) and then incubated with the sample; and / or (e) If the method involves incubation with two or more of the following: an agent that binds to H3K4 modification, an agent that binds to H3K27ac modification, and an agent that binds to methylated DNA, then the sample is incubated with the two or more agents in the following manner: (i) sequentially, or (ii) in parallel (e.g., wherein the sample is divided into several portions and each portion is incubated with a different agent).

6. The method of any one of claims 1 to 5, the method comprising mapping sequence reads to a reference genome, optionally wherein non-unique mappings and redundant sequence reads are discarded and / or peaks in high-noise regions are removed.

7. The method of claim 6, wherein the one or more genomic sites correspond to sequence read peaks, wherein the sequence read peaks correspond to regions in the genome where the number of sequence reads is higher than the local background.

8. The method of any one of claims 5 to 7, wherein quantifying H3K4me3 modification, H3K27ac modification, and / or DNA methylation comprises summing the number of sequence reads that overlap with at least one nucleotide at said one or more genomic sites. Choose one of them: Before summing, the sequence reads are adjusted according to sequencing depth (e.g., normalizing the sequence read quantiles to a common reference distribution) and / or ChIP quality; Sequence counts were normalized to aggregate counts of a set of regions (e.g., 10,000 regions) in a given sample, regions previously identified as having DNAse hypersensitivity in most cell types; and / or Before summing, the estimated value of the local background signal is subtracted from the sequence read at each genomic locus.

9. The method of any one of claims 1 to 8, wherein the reference value is a predetermined threshold, a measurement of a liquid biopsy sample, a measurement from a liquid biopsy sample obtained from a group of subjects, and / or a normalized value, wherein: It has been previously demonstrated that the predetermined threshold and the normalized value distinguish between LUAD and SCLC subjects (e.g., by using AUROC greater than 0.5); The reference values ​​are measurements taken from liquid biopsy samples obtained from a cohort of subjects previously diagnosed with LUAD or SCLC; or The aforementioned group of subjects had previously been diagnosed with lung cancer (e.g., LUAD or SCLC).

10. The method of any one of claims 5 to 9, wherein the method comprises calculating the sequence read density at the one or more genomic loci, optionally wherein the sequence read density is calculated in the following manner: (a) Summing the background-adjusted sequence counts at each of the one or more genomic loci and dividing by the sum of the kilobases at the one or more genomic loci; or (b) For each genomic locus, divide the background adjustment fragment count by the number of kilobases of the genomic locus, and then sum over each locus.

11. The method of claim 10, wherein the method comprises calculating the SCLC / LUAD ratio score by means of a method comprising: (a) SCLC sequence read density is calculated by summing background-adjusted sequence counts at each of the one or more genomic loci where the level of the one or more epigenetic biomarkers is increased in a sample obtained from a subject with LUAD, compared to a sample obtained from a subject with SCLC; (b) Calculate the LUAD sequence read density by summing the background-adjusted sequence counts at each of the one or more genomic loci where the levels of the one or more epigenetic biomarkers are increased, compared to samples obtained from subjects with SCLC; and (c) Divide the SCLC sequence read density by the LUAD sequence read density.

12. The method of claim 11, wherein the method comprises: (a) Determine the SCLC / LUAD ratio score for H3K4me3 modification; (b) Determine the SCLC / LUAD ratio score for H3K27ac modification; and / or (c) Determine the SCLC / LUAD ratio score for methylated DNA; and If each of (a) through (c) is performed, then each of the said ratio scores may optionally be combined (e.g., with a fitted value determined using logistic regression).

13. The method of any one of claims 1 to 12, wherein the one or more epigenetic biomarkers are quantified at one or more genomic loci listed in Tables 1 to 13. Optionally, the method described herein includes quantization: (a) H3K4me3 modification at at least 5, 10, 20, 30, 40, 50, 100, 150 or 200 genomic loci listed in Table 1; (b) H3K27ac modifications at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500 or 2000 genomic loci listed in Table 2; (c) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci listed in Table 3; (d) H3K4me3, H3K27ac and / or DNA methylation at at least 5, 10, 20 or 30 genomic loci listed in Table 5; (e) H3K27ac modifications at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, 5000 or 5500 genomic loci listed in Table 6; (f) H3K27ac modifications at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci listed in Table 7; (g) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500 or 600 genomic loci listed in Table 8; (h) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500 or 600 genomic loci listed in Table 9; (i) Chromatin accessibility of at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci listed in Table 10 (e.g., using ATAC-seq). (j) Chromatin accessibility of at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000 or 4000 genomic loci listed in Table 11 (e.g., using ATAC-seq). (k) H3K4me3 modifications at at least 5, 10, 20, 30, 40, 50 or 100 genomic loci listed in Table 12; (l) H3K4me3 modifications at at least 5, 10, or 15 genomic loci listed in Table 13, or (m) or any combination of (a) to (l).

14. The method of any one of claims 1 to 13, wherein the area under the recipient operating characteristic curve (AUROC) provided by the method for determining whether a subject has SCLC or LUAD is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95).

15. The method of any one of claims 1 to 14, wherein the subject has been previously diagnosed with lung cancer (e.g., EGFRm (EGFR mutant) LUAD), the subject has increased susceptibility to lung cancer (e.g., SCLC, including primary SCLC and transformed SCLC), and / or wherein the method further comprises determining whether the subject has lung cancer.

16. The method of any one of claims 1 to 15, wherein the SCLC is a transformative SCLC and the LUAD is an EGFRm LUAD.

17. The method of any one of claims 1 to 16, wherein if the subject is determined to have SCLC, the method further comprises classifying the SCLC into subtypes by detecting an increase or decrease in the activity (e.g., expression level) of one or more transcription factors; Optionally, the increase or decrease is relative to the average expression of subjects with SCLC and / or one or more subjects characterized by an alternative SCLC subtype.

18. The method of claim 17, wherein: (a) The SCLC subtype is characterized by increased YAP1 activity (e.g., increased expression relative to ASCL1, NEUROD1 and POU2F3 compared to the general population of subjects with SCLC); (b) The SCLC subtype is characterized by increased activity of ASCL1, NEUROD1, or POU2F3 (e.g., the SCLC is subtyped based on which of ASCL1, NEUROD1, and POU2F3 is expressed most highly relative to each other). (c) The SCLC subtype is an inflammatory SCLC subtype (SCLC-1) and optionally is characterized by low activity (e.g., low expression) of ASCL1, NEUROD1 and POU2F3 (e.g., lower activity relative to healthy subjects, average subjects with SCLC and / or one or more alternative SCLC subtypes) and / or inflammatory gene signatures.

19. The method of claim 17 or 18, wherein the activity of the one or more transcription factors is assessed by quantifying the following methods at one or more genomic sites in cell-free DNA (cfDNA) from a liquid biopsy sample: (i) One or more histone modifications, (ii) Chromatin accessibility, (iii) Binding of one or more transcription factors (e.g., measuring the binding of ASCL1, NEROD1, YAP1, and / or POU2F3 at one or more genomic loci), and / or (iv) DNA methylation, The one or more genomic sites mentioned therein include one or more genomic sites with increased histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in samples obtained from subjects with a first SCLC subtype compared to samples obtained from one or more subjects with different SCLC subtypes. Optionally, a histone modification assay is used to quantify one or more histone modifications, the assay measuring one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, H3K4me3 and pantothenic acid (e.g., H3K4me3 modification and / or H3K27ac modification).

20. The method of any one of claims 17 to 19, wherein the method comprises: (a) Quantify H3K4me3 modifications at one or more genomic sites using an assay that includes enriching cfDNA containing one or more H3K4me3 modifications (e.g., including an assay that incubates the liquid biopsy sample with an agent that binds to H3K4me3 modifications) and sequencing the cfDNA enriched for H3K4me3 modifications to determine the sequence count containing one or more H3K4me3 modifications. (b) Quantify H3K27ac modifications at one or more genomic sites using an assay that includes enriching cfDNA containing one or more H3K27ac modifications (e.g., an assay that involves incubating the liquid biopsy sample with an agent that binds to H3K27ac modifications) and sequencing the cfDNA enriched for H3K27ac modifications to determine the sequence count containing one or more H3K27ac modifications. and / or (c) Quantifying methylated DNA using an assay that includes: enriching methylated cfDNA (e.g., an assay that involves incubating the liquid biopsy sample with an agent that binds methylated DNA (e.g., an antibody or a methyl-binding domain)) and sequencing the enriched cfDNA to determine a sequence count containing one or more methylated nucleotides. Choose one of them: The agent binding H3K4me3 modification, the agent binding H3K27ac modification, and / or the agent binding methylated DNA are attached (e.g., via covalent or non-covalent bonds) to a physical support (e.g., beads, magnetic beads, agarose beads, or magnetic epoxy beads) and then incubated with the sample; and / or If the method includes incubation with two or more of the following: the agent that binds H3K4 modification, the agent that binds H3K27ac modification, and the agent that binds methylated DNA, then the sample is incubated with the two or more agents in the following manner: (a) sequentially, or (b) in parallel (e.g., wherein the sample is divided into several portions and each portion is incubated with a different agent).

21. The method of any one of claims 17 to 20, the method comprising mapping sequence reads to a reference genome, optionally wherein non-unique mappings and redundant sequence reads are discarded and / or high-noise regions are removed.

22. The method of claim 21, wherein the one or more genomic loci correspond to a sequence read peak, wherein the sequence read peak corresponds to a region in the genome where the number of sequence reads is higher than the local background.

23. The method of any one of claims 18 to 22, wherein quantifying H3K4me3 modification, H3K27ac modification and / or DNA methylation comprises summing the number of sequence reads that overlap with at least one nucleotide at the one or more genomic sites; Choose one of them: Before summing, the sequence reads are adjusted according to sequencing depth (e.g., normalizing the sequence read quantiles to a common reference distribution) and / or ChIP quality; Sequence counts were normalized to aggregate counts of a set of regions (e.g., 10,000 regions) in a given sample, regions previously identified as having DNAse hypersensitivity in most cell types; and / or Before summing, the estimated value of the local background signal is subtracted from the sequence read at each genomic locus.

24. The method of any one of claims 18 to 23, the method comprising calculating the sequence read density at the one or more genomic loci, optionally wherein the sequence read density is calculated in the following manner: (a) Summing the background-adjusted sequence counts at each of the one or more genomic loci and dividing by the sum of the kilobases at the one or more genomic loci; or (b) For each genomic locus, divide the background adjustment fragment count by the number of kilobases of the genomic locus, and then sum over each locus.

25. The method of any one of claims 19 to 24, wherein the one or more genomic sites are selected from those provided in Table 4.

26. The method according to any one of claims 1 to 25, wherein: (a) Biopsy of the lung cancer is impossible and / or infeasible; (b) The lung cancer described is metastatic lung cancer; (c) The lung cancer exhibits TP53 and / or RB1 loss (e.g., containing one or more loss-of-function mutations); and / or (d) The subjects described therein exhibited TKI resistance.

27. A method for treating a subject with lung cancer, the method comprising: The subject is given lung cancer therapy based on the SCLC / LUAD status of the lung cancer, wherein the SCLC / LUAD status of the lung cancer has been determined using the method of any one of claims 1 to 26, wherein: (a) If the lung cancer is identified as SCLC, then the cancer treatment includes administering SCLC therapy; and (b) If the lung cancer is identified as LUAD, the cancer treatment includes administration of LUAD therapy.

28. The method of claim 27, wherein the subject has been previously identified as having EGFR m LUAD before determining the SCLC / LUAD status using the method of any one of claims 1 to 27.

29. The method of claim 28, wherein the cancer has been subtyped using the method of any one of claims 17 to 17, and wherein the method includes administering SCLC therapy to the subject based on the SCLC subtype (e.g., administering SCLC therapy that has been shown to provide improved benefit for the identified SCLC subtype compared to other treatments typically administered to subjects with SCLC).

30. The method of claim 29, wherein: (a) The cancer has been subtyped based on increased ASCL1 activity (e.g., expression), and the SCLC therapy is associated with providing improved treatment benefits to subjects diagnosed with ASCL1 subtype SCLC (e.g., improvement relative to alternative therapies typically administered to subjects with SCLC), optionally wherein the SCLC therapy is a BCL2 apoptosis modulator, a BCL2 inhibitor, a DLL3 inhibitor (e.g., rovalpizumab-tecillin), an LSD1 inhibitor, and / or a CEACAM5-targeting therapy (e.g., labezizumab-glavotecan); (b) The cancer has been subtyped based on increased NEUROD1 activity (e.g., expression), and the SCLC therapy is associated with providing improved treatment benefits to subjects diagnosed with NEUROD1 subtype SCLC (e.g., improvements relative to alternative therapies typically administered to subjects with SCLC), optionally wherein the SCLC therapy is an Aurora kinase inhibitor co-administered with platinum-etoposide, a somatostatin receptor 2 (SSTR2) inhibitor (e.g., lanreotide), an SSTR2-targeting therapy (e.g., PEN-221), or an immunotherapy (e.g., durvalumab). (c) The cancer has been subtyped based on increased POU2F3 activity (e.g., expression), and the SCLC therapy is associated with improved treatment benefit in subjects diagnosed with POU2F3 subtype SCLC, optionally wherein the SCLC therapy comprises an insulin-like growth factor 1 receptor inhibitor (optionally, without chemotherapy), cisplatin, a PARP inhibitor, antimetabolites (e.g., antifolate or nucleoside analogs) and / or durvalumab (optionally, without platinum-etoposide administration); (d) The subject has been subtyped based on increased YAP1 activity (e.g., expression), and the SCLC therapy is associated with improved treatment benefit in subjects diagnosed with YAP1 subtype SCLC, optionally wherein the SCLC therapy comprises durvalumab co-administered with platinum-etoposide. (e) The SCLC subtype is an inflammatory SCLC subtype (SCLC-I) and optionally features: (i) low activity (e.g., low expression) of ASCL1, NEUROD1, and POU2F3 (e.g., lower than average subjects with SCLC and / or one or more alternative SCLC subtypes relative to healthy subjects), and / or (ii) poor response to immune checkpoint blockade; optionally, the SCLC therapy comprises anti-PD-L1 agents and chemotherapeutic agents co-administered with platinum-etoposide, immune checkpoint blockade, Bruton's tyrosine kinase (BTK) inhibitors, ibrutinib, EMT inhibitors (e.g., HDACi (e.g., mosetinofet)), MICA inhibitors (e.g., IPH43), and / or immunotherapy (e.g., durvalumab).

31. The method of claim 27, wherein: The LUAD therapy includes administration of a selective EGFR tyrosine kinase inhibitor (e.g., osimertinib); and The SCLC therapy includes the administration of (i) an agent targeting DLL3 (e.g., talatumab), and / or (ii) a combination of a PD-L1 inhibitor and platinum-based etoposide chemotherapy or a PARP inhibitor; Optionally, if the lung cancer has been determined to be EGFRm LUAD with a high risk of SCLC transformation (e.g., exhibiting loss of TP53 and / or RB1), the method comprises administering a combination of platinum-based / etoposide chemotherapy and osimertinib.

32. A method for monitoring the SCLC / LUAD status of a subject's lung cancer and optionally treating the lung cancer, the method comprising: The SCLC / LUAD status of the lung cancer was determined at a first time point and a second time point using the method of any one of claims 1 to 26.

33. The method of claim 32, wherein, prior to the first time point or between the first time point and the second time point, the subject has been administered a therapeutic agent that can cause LUAD (or more generally, NSCLC) to transform into SCLC, for example, wherein the subject has epidermal growth factor receptor (EGFR) mutant LUAD and is being treated with a tyrosine kinase inhibitor (TKI), the subject has anaplastic lymphoma kinase (ALK) positive LUAD and is being treated with an ALK inhibitor, or the subject has wild-type EGFR or ALK LUAD and is being treated with immunotherapy.

34. The method of claim 32 or 33, further comprising administering lung cancer therapy, optionally SCLC therapy or LUAD therapy, to the subject based on the SCLC / LUAD status of the lung cancer at the second time point, optionally wherein the type, dose, and / or frequency of the cancer therapy is adjusted based on the SCLC / LUAD status of the lung cancer at the second time point.

35. A method for treating a subject with lung cancer, the method comprising: (i) If, based on analysis of cell-free DNA (cfDNA) from a biological sample obtained from or derived from the subject, optionally from a liquid biopsy sample (e.g., plasma, serum, or urine sample), the subject has been determined to have a validated epigenetic signature of SCLC, then the subject is administered an SCLC treatment agent; or (ii) If, based on analysis of cell-free DNA (cfDNA) obtained from or derived from the subject, optionally from a liquid biopsy sample, the subject has been determined to possess a validated epigenetic signature of LUAD, then the subject is administered a LUAD treatment agent. The presence of the verified epigenetic features was determined using a validated classifier. The classifier used for verification is obtained in the following way: (a) Identify genomic features of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in biological samples obtained from a first group of subjects who have been previously diagnosed with SCLC (e.g., primary SCLC or transformed SCLC). (b) Identify genomic features of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation in biological samples obtained from a second group of healthy subjects or subjects previously identified as having LUAD; (c) Compare the genomic features identified in step (a) with those identified in step (b) to identify genomic sites ("difference sites") that show statistical differences in histone modification, chromatin accessibility, transcription factor binding and / or DNA methylation levels. (d) Using histone modification, chromatin accessibility, transcription factor binding, and / or DNA methylation level training at the differential sites to distinguish (i) samples from one or more biological samples obtained from the first cohort, and (ii) samples from one or more biological samples obtained from the second cohort, to identify samples having histone modification, chromatin accessibility, transcription factor binding, and / or DNA methylation level characteristics ("epigenetic features") indicating that the sample may have been obtained from the first cohort; and (e) The validated classifier is obtained by validating the classifier in step (d) on a third cohort comprising independent, blinded subjects with SCLC cancer and LUAD cancer, and a threshold is selected such that the validated classifier predicts SCLC cancer and the area under the receiver operating characteristic curve (AUROC) is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95), wherein subjects falling into the predicted SCLC cancer group exhibit the validated epigenetic feature and subjects not falling into the SCLC cancer group lack the validated epigenetic feature.

36. The method of claim 35, wherein: (a) The differential sites in step (c) are determined by comparing the genomic features of one or more histone modifications and / or DNA methylation in (i) one or more biological samples from the first cohort and (ii) one or more biological samples from the second cohort; (b) The classifier in step (d) is trained on the levels of histone modifications and / or DNA methylation in (i) one or more biological samples from the first cohort and (ii) one or more biological samples from the second cohort; (c) Validate the classifier used in step (e) using liquid biopsy samples from the third queue; and / or (d) The classifier in step (d) is trained on one or more (e.g., two or more) levels of histone modification and / or DNA methylation at the differential sites, optionally wherein the one or more histone modification levels include H3K4me3 and H3K27ac modification levels; and / or (e) The classifier in step (d) is trained using ridge regression, elastic network regression, or lasso regression.

37. A kit comprising reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors and / or DNA methylation at one or more genomic sites, wherein the one or more genomic sites are selected from Tables 1 to 13, for example, Tables 1 to 3; Optionally, the kit described herein includes reagents for quantification: (a) H3K4me3 modification at at least 5, 10, 20, 30, 40, 50, 100, 150 or 200 genomic loci listed in Table 1; (b) H3K27ac modifications at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500 or 2000 genomic loci in Table 2; (c) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci in Table 3; (d) H3K4me3, H3K27ac and / or DNA methylation at at least 5, 10, 20 or 30 genomic loci in Table 5; (e) H3K27ac modification at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, 5000 or 5500 genomic loci in Table 6; (f) H3K27ac modification at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci in Table 7; (g) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500 or 600 genomic loci in Table 8; (h) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500 or 600 genomic loci in Table 9; (i) Chromatin accessibility of at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci in Table 10 (e.g., using ATAC-seq); (j) Chromatin accessibility of at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000 or 4000 genomic loci in Table 11 (e.g., using ATAC-seq); (k) H3K4me3 modification at at least 5, 10, 20, 30, 40, 50 or 100 genomic loci in Table 12; (l) H3K4me3 modification at at least 5, 10, or 15 genomic loci listed in Table 13, or (m) or any combination of (a) to (l).

38. The kit of claim 37, wherein the kit comprises: (a) One or more antibodies for ChIP-seq, wherein said one or more antibodies specifically bind to histones modified with H3K4me3 or H3K27ac; (b) One or more methyl-binding domains for MBD-seq, or the kit comprising one or more antibodies for binding methylated DNA for MeDIP; (c) Reagents for isolating cell-free DNA (cfDNA) from liquid biopsy samples; (d) Reagents for library preparation used in sequencing; (e) Reagents used for sequencing; (f) Instructions for determining whether a subject has SCLC or LUAD, optionally instructions for determining whether a subject has an SCLC subtype characterized by increased ASCL1, NEUROD1, YAP1 and / or POU2F3 activity (e.g., expression); and / or (g) Any combination of (a) to (f).

39. A non-transient computer-readable storage medium encoded with a computer program, wherein the program includes instructions that, when executed by one or more processors, cause the one or more processors to perform operations to perform the method of any one of claims 1 to 26.

40. A computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of claims 1 to 26.

41. A system for determining the SCLC / LUAD status of lung cancer in a subject, the system comprising a sequencer configured to generate a sequencing dataset from a sample; and the non-transient computer-readable storage medium of claim 39 and / or the computer system of claim 40. Optionally, the sequencer is configured to generate a whole-genome sequencing (WGS) dataset from the sample.

42. The system of claim 41, further comprising a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample. The sample preparation apparatus includes reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation at one or more genomic sites in cell-free DNA (cfDNA) from the biological sample.

43. The system of claim 42, wherein the one or more genomic loci are selected from Tables 1 to 13, for example, Tables 1 to 3. Optionally, the device includes a reagent for quantification: (a) H3K4me3 modification at at least 5, 10, 20, 30, 40, 50, 100, 150 or 200 genomic loci listed in Table 1; (b) H3K27ac modifications at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500 or 2000 genomic loci in Table 2; (c) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci in Table 3; (d) H3K4me3, H3K27ac and / or DNA methylation at at least 5, 10, 20 or 30 genomic loci in Table 5; (e) H3K27ac modification at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, 5000 or 5500 genomic loci in Table 6; (f) H3K27ac modification at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci in Table 7; (g) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500 or 600 genomic loci in Table 8; (h) DNA methylation at at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500 or 600 genomic loci in Table 9; (i) Chromatin accessibility of at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000 or 5000 genomic loci in Table 10 (e.g., using ATAC-seq); (j) Chromatin accessibility of at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000 or 4000 genomic loci in Table 11 (e.g., using ATAC-seq); (k) H3K4me3 modification at at least 5, 10, 20, 30, 40, 50 or 100 genomic loci in Table 12; (l) H3K4me3 modification at at least 5, 10, or 15 genomic loci listed in Table 13 (m) or any combination of (a) to (l).

44. The system of claim 42 or 43, wherein: (a) The reagent contains one or more antibodies for ChIP-seq, wherein the one or more antibodies specifically bind to histones modified by H3K4me3 or H3K27ac; (b) The reagent contains one or more methyl-binding domains for MBD-seq; (c) The apparatus includes reagents for isolating cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample; (d) The apparatus includes library preparation reagents for sequencing; and / or (e) The sequencer includes reagents for sequencing.

45. A method for determining the SCLC and / or LUAD status of a subject (e.g., a patient), the method comprising: Receive (e.g., via a processor of a computing device) one or more genomic features of a subject, including one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation; as well as Whether the subject has an epigenetic trait indicating SCLC or LUAD is determined by classifying the genomic features using an SCLC / LUAD classifier (e.g., by the processor).

46. ​​The method of claim 45, wherein the SCLC / LUAD classifier has been trained using one or more genomic features of histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation from one or more biological samples obtained from one or more cohorts of subjects previously diagnosed with SCLC (e.g., primary SCLC or transformed SCLC) or LUAD. Optionally, the one or more genomic features used to train the SCLC / LUAD classifier are for differentially expressed sites that show statistically significant differences in the levels of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and / or DNA methylation levels among one or more biological samples obtained from a cohort of subjects previously identified as having SCLC (e.g., primary SCLC or transformed SCLC) or LUAD.

47. The method of claim 46, wherein the SCLC / LUAD classifier has been trained using the following: (a) Genomic features of two or more histone modification levels at the differentially expressed sites; or (b) Genomic characteristics of the levels of one or more histone modifications and DNA methylation at the differential sites.

48. The method of any one of claims 45 to 47, wherein the method comprises receiving: (a) One or more genomic features of two or more histone modifications, wherein the two or more histone modifications optionally include H3K4me3 and H3K27ac modifications; (b) One or more genomic features of histone modifications and DNA methylation; optionally, said histone modifications include H3K4me3 and / or H3K27ac modifications.

49. The method of any one of claims 45 to 48, wherein the SCLC / LUAD classifier is validated by selecting a threshold such that the validated classifier predicts a recipient operating characteristic curve area under the curve (AUROC) for SCLC cancers greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95), and Choose one of them: (a) The SCLC / LAUD classifier has been validated on a cohort of subjects with SCLC (e.g., primary SCLC or transformed SCLC) or LUAD, wherein subjects falling into the predicted SCLC (e.g., primary SCLC or transformed SCLC) cancer group exhibited the validated epigenetic characteristics, and subjects not falling into the predicted SCLC cancer group lacked the validated epigenetic characteristics; and / or (b) The SCLC / LUAD classifier has been validated using liquid biopsy sample data.

50. A non-transient computer-readable storage medium encoded with a computer program, wherein the program includes instructions that, when executed by one or more processors, cause the one or more processors to perform operations to perform the method of any one of claims 45 to 49.

51. A computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of claims 45 to 50.

52. A method for treating a subject suffering from cancer, the method comprising: The subject was administered a therapeutic agent for SCLC, wherein, based on analysis of cell-free DNA (cfDNA) from a biological sample obtained from or derived from the subject, optionally from a liquid biopsy sample, the subject was determined to possess validated epigenetic characteristics indicative of SCLC. The presence of the verified epigenetic feature has been determined using a classifier (e.g., a verified classifier) ​​according to any one of claims 45 to 50.

53. A method for treating a subject suffering from cancer, the method comprising: The subject was administered a LUAD therapeutic agent, wherein, based on analysis of cell-free DNA (cfDNA) from a biological sample obtained from or derived from the subject, optionally from a liquid biopsy sample, the subject was determined to possess validated epigenetic characteristics indicative of LUAD. The presence of the verified epigenetic feature has been determined using a classifier (e.g., a verified classifier) ​​according to any one of claims 45 to 50.

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