92 results about "Cancer recurrence" patented technology

The invention discloses a gastric cancer recurrence risk prediction method based on metabonomics characteristic analysis. The method comprises the following steps: S1, constructing a metabonomics data set; s2, the collected metabonomics data set is preprocessed; s3, extracting metabolite characteristics related to gastric cancer recurrence; s4, based on the extracted metabolite features, using a metabolic pathway integration method to quantify disturbance of each metabolic pathway, and calculating the abnormal degree of metabolite concentration change in the metabolic pathways; s5, constructing a multi-dimensional feature matrix containing a metabonomics data set, metabolic pathway integrals and patient individual information; s6, inputting the multi-dimensional feature matrix into a trained machine learning model, and outputting a gastric cancer recurrence risk score of the patient; and S7, generating a prediction report according to the recurrence risk score. According to the method, by combining metabonomics characteristic analysis, the space-time coupling quantum optimization network and the nonlinear disturbance model, the problems of insufficient real-time performance and insufficient data integration in gastric cancer recurrence risk prediction in the prior art are solved.

The invention discloses a bladder cancer postoperative recurrence risk prediction system, and relates to the technical field of cancer recurrence risk prediction. The bladder cancer postoperative recurrence risk prediction system comprises a data acquisition module, a data processing module, a feature engineering module, a risk prediction module, a decision support module and a result display module. According to the method, a bladder cancer postoperative recurrence risk prediction model is optimized and improved, that is, an input layer, a full connection layer, a merging layer and a comprehensive processing layer are newly added on a traditional LSTM model, so that the prediction model can fully utilize time sequence data and static feature data; therefore, the influence of time sequence data such as methylation detection and miRNA expression of the patient and static data such as age and gender of the patient on the recurrence risk of the bladder cancer can be fully considered, data can be analyzed from different angles and levels, a more accurate prediction result is provided, the overfitting risk of the prediction model can be reduced, and the prediction accuracy of the bladder cancer is improved. And the generalization ability of the whole prediction model is improved.

The invention relates to the technical field of biomedicine, and discloses a rectal cancer postoperative recurrence risk prediction method based on a prediction model, and the method comprises the steps: obtaining a patient tumor in the in-vivo image data of a rectal cancer patient; extracting imaging features of the tumor of the patient, and identifying recurrence risk features of the rectal cancer patient from the imaging features; analyzing clinical pathological characteristics of the rectal cancer patient according to the preoperative evaluation data and the postoperative pathological report; key recurrence influence factors of the rectal cancer patients are identified, recurrence events and follow-up visit time of the rectal cancer patients are identified, risk scoring is carried out on the rectal cancer patients, and a risk scoring result is obtained; based on the risk scoring result, the recurrence risk stratification of the rectal cancer patient is defined, postoperative recurrence risk analysis is conducted on the rectal cancer patient in combination with the recurrence risk stratification, the recurrence risk characteristics and the risk scoring result, and a risk analysis result is obtained. According to the invention, the comprehensiveness and accuracy of the rectal cancer recurrence risk analysis result can be improved.

The invention discloses a cancer recurrence probability deep learning prediction system based on multi-modal time sequence characteristics, and relates to the technical field of medical data processing. The method comprises the following steps: constructing a multi-modal time sequence data set by collecting clinical static data, dynamic treatment data and time sequence monitoring data of a patient; missing value filling and abnormal value elimination based on sliding Z-score are carried out on the data to form an effective data set; screening key clinical static features by using a random forest model; constructing a radiotherapy cumulative toxicity model to quantify residual toxicity, and generating dynamic characteristics by combining the dose change rate three-state characteristics; converting the features into a four-dimensional time sequence tensor through a dynamic sliding window; optimizing LSTM hyper-parameters by adopting random search, and training a high-precision prediction model to output a recurrence probability; finally, differentiated clinical intervention is triggered based on risk grading, a'prediction-decision 'closed-loop system is formed, and the initiative and accuracy of cancer recurrence diagnosis and treatment are remarkably improved.

The invention belongs to the technical field of medical health management, and particularly relates to an AI personalized health education system for elderly patients with head and neck cancer, which comprises a content generation and management module, a personalized push engine, an interaction and artificial triage module, an elderly friendly interaction module and a data monitoring and safety module, by adopting an AI + manual hierarchical response mechanism and combining elderly friendly interactive design and operation training support, the participation obstacles that elderly patients are inconvenient to move and poor in informatization ability are broken through, and the intervention compliance and sustainability are improved; according to the intervention method, strict double-group random control test design is adopted, multi-dimensional and multi-time-point effect evaluation is combined with a scientific statistical analysis method, the improvement effect of AI-assisted health education on cancer recurrence, fear, psychological state and life quality of a patient can be accurately verified, and a solid evidence-based basis is provided for clinical popularization.

The present invention relates to nitrogen-containing derivatives of narasin having the formula (I), as well as synthesis and uses thereof, in particular for the treatment and / or prevention of cancer. Also disclosed are medicaments including the nitrogen-containing derivatives of narasin, which include medicaments for preventing cancer metastasis and / or for preventing cancer recurrence and / or for decreasing resistance to a chemotherapy in a subject.

The present disclosure relate to a method. The method includes accessing segmented digitized pathology imaging data from a cancer patient. The segmented digitized pathology imaging data identifies segmented nuclei, segmented mitosis, and segmented tubule regions. A plurality of nuclear features are extracted using the segmented nuclei. A plurality of mitosis features are extracted using the segmented mitosis. A plurality of tubule features are extracted using the segmented tubule regions. A risk score is generated by operating a machine learning model on the plurality of nuclear features, the plurality of mitosis features, and the plurality of tubule features. The risk score correlates to a risk of recurrence of cancer for the cancer patient.

Disclosed are methods of treating a subject in need thereof comprising applying an alternating electric field, to a target site of the subject in need thereof; and administering a a Notch1 inhibitor or Hes5 inhibitor to the subject in need thereof. Disclosed are methods of preventing cancer recurrence in a subject having cancer comprising: applying an alternating electric field to a target site of the subject in need thereof; and administering a Notch1 inhibitor or Hes5 inhibitor to the subject in need thereof. Disclosed are methods of reducing cancer cell growth comprising: applying an alternating electric field to a population of cells comprising one or more cancer cells; and contacting a Notch1 inhibitor or Hes5 inhibitor to the population of cells. Disclosed are methods of sensitizing cancer cells to an alternating electric field comprising: applying an alternating electric field to a population of cells comprising one or more cancer cells; and contacting a Notch1 inhibitor or Hes5 inhibitor to the population of cells.

Presented herein are systems and methods for determining scores related to metastatic recurrence of cancers in subjects using multimodal machine learning (ML) architectures. A computing system may obtain, for a subject at risk of recurrence of cancer, a dataset comprising at least one of: (i) a biomedical image of a tissue sample from an organ associated with the cancer or (ii) a text report identifying a plurality of characteristics of a tumor associated with the cancer. The computing system may apply an ML architecture to at least one of the biomedical image or the text report of the dataset. The computing system may determine, based on applying the ML architecture, a score indicating a likelihood of recurrence associated with cancer in the subject. The computing system may generate a classification of the subject for administration of a therapy for the cancer, in accordance with the score.

The invention discloses a sugar chain marker combination for predicting the recurrence risk of a gastric cancer patient after treatment and application of the sugar chain marker combination. The invention discovers that the levels of six specific N-sugar chains (NGA2F, NG1A2F, NA3, NA3Fb, NA4 and NA4Fb) in blood are obviously related to relapse during definite diagnosis of gastric cancer for the first time. On the basis, a gastric cancer recurrence risk prediction model GC-GPSS is constructed through Cox regression. According to the model, individual risk scores are calculated by using a quantification formula containing a fixed regression coefficient (beta), and patients are divided into a high-risk group and a low-risk group according to a preset threshold. A verification result shows that the model can effectively distinguish patient groups with different recurrence risks. The marker combination, the prediction model and the system provided by the invention provide a brand new tool for realizing earlier and more objective recurrence risk assessment in the early stage of gastric cancer diagnosis and treatment, and have important clinical application value.

The present application relates to scaffolds for treating solid tumor cells and evasion variants. Implantable stents are described that treat solid tumors and evasion variants and provide effective vaccination against cancer recurrence. The scaffold includes a genetically reprogrammed lymphocyte and a lymphocyte activating portion.

The present invention relates to methods of diagnosing cancer in a patient. Furthermore, the present invention relates to a method of monitoring the course of cancer in a patient. Furthermore, the present invention relates to a method of determining whether a patient is responsive to a therapeutic treatment of cancer. The invention also relates to a method of determining the risk of cancer recurrence in a patient. In addition, the present invention relates to a method of detecting minimal residual lesions in a patient with cancer. In addition, the invention relates to kits for carrying out these methods.

Disclosed are broccoli plant extracts and nutraceuticals including the same that have increased levels of anti-inflammatory chemicals. Also provided are exosomal preparations containing the broccoli plant extracts and nutraceuticals as well as methods of using the broccoli plant extracts and nutraceuticals for treating inflammation and treating or reducing the risk of cancer recurrence in a subject.

This invention relates generally to biomarkers that are useful for determining whether a cancer is likely to recur in a subject, and / or determining whether a subject is likely to respond to cancer therapy. The invention therefore relates to methods, kits and compositions for determining whether a cancer is likely to recur in a subject, or whether a subject is likely to respond to cancer therapy, and to methods of treatment based on a determination that a subject with cancer is likely to respond to cancer therapy.

The present disclosure provides a method for using peptides of oncogenic proteins to reverse immune suppression, induce stronger immune responses, reduce cancer recurrence rates, and prolong disease-free survival. The suppressed immune state may be due to prior treatments, including but not limited to surgery, chemotherapy, antibodies targeting the oncogenic protein, high levels of expression of the oncogenic protein, or combinations thereof. For example, in a control group of clinical studies, it was shown that when GM-CSF was administered to patients without peptides derived from the oncogenic protein, the immune response to GM-CSF alone was lower when compared with patients who were not treated with antibodies against the oncogenic protein and did not have high levels of expression of the oncogenic protein, and the immune state of these patients was suppressed, with higher recurrence rates and lower disease-free survival rates, all of which were reversed by the addition of the peptides.

The present invention relates to the field of medicine, in particular cancer treatment. More specifically, the present invention relates to new compounds that are generally used as drugs. In particular, the present invention relates to the use of these new compounds for improving the presentation, generally the production and presentation, of antigens derived from prior translation products (PTPs) by cells, in particular cancer cells, or for changing the immunopeptidase group in a subject and inducing or stimulating an immune response in the subject. The present disclosure also relates to the use of such compounds, in particular for the preparation of pharmaceutical compositions and / or for allowing or improving the efficiency of therapy in subjects in need. The present invention also discloses methods for treating diseases, in particular cancer, preventing or treating cancer metastasis and / or cancer recurrence in a subject. In addition, the present invention also provides a kit suitable for preparing a composition according to the present invention and / or for performing the methods described herein.

Positive surgical margins after surgery for breast cancer are defined as malignant cells identified at the edge of the resection specimen and have been associated with at least two-fold increase in ipsilateral breast cancer recurrence, higher distant recurrence rates, and shorter survival. While there have been several clinical factors associated with the risk of positive margins, there is a paucity of data considering both clinical variables and genomic profiles associated with positive margins. In this disclosure was explored the association of clinicopathologic and molecular factors with the occurrence of positive margins after first surgery in breast cancer. As a result, it was found that the occurrence of positive margins after surgery was associated with various clinical factors. Further, as the first effort to pursue molecular understanding of the margin status, a gene panel of 29 genes including 17 protein-coding genes was also identified for potential prediction of the margin status.

The disclosure, in one aspect, relates to methods for treating cancer in a subject, the methods including at least the steps of administering at least one drug from each of at least two classes selected from an inhibitor of poly-ADP ribose polymerase (PARP inhibitor), an inhibitor of DNA-dependent protein kinase catalytic subunit (DNA-PKcs inhibitor), an inhibitor of wild-type isocitrate dehydrogenase (IDH inhibitor), an inhibitor of histone acetyltransferase (HAT inhibitor), an inhibitor of histone deacetylase (HDAC inhibitor), an inhibitor of DNA polymerase Θ (POLΘ inhibitor), an inhibitor of platelet-derived growth factor receptor (PDGFR inhibitor), and a DNA alkylating agent to the subject. In any of these aspects, the disclosed method allows for administering lower doses of the drugs in combination compared to administration as single drugs while preventing the recurrence of the cancer, preventing drug resistance of the cancer, and reducing side effects associated with cancer treatment.

The invention provides a biomarker for judging cancer metastasis or cancer recurrence and application thereof, and relates to the technical field of molecular biology. The biomarker based on STEAP4 protein and / or IGFBP6 protein provided by the invention has the advantages of convenience, rapidness and the like in detection, can provide dynamic monitoring of diseases for patients, and achieves the technical effect of timely discovering cancer metastasis signs or cancer recurrence signs.

The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to extended treatment and cancer-free survival in a patient. In particular, the disclosure includes the identities of genes that are expressed in correlation with benefit in a switch in endocrine therapy used to treat a patient. The levels of gene expression are disclosed as a molecular index for predicting clinical outcome, and so prognosis, for the patient. The disclosure further includes methods for predicting cancer recurrence, and / or predicting occurrence of metastatic cancer, after initial treatment with an anti-estrogen agent. The disclosure further includes methods for determining or selecting the treatment of a subject based upon the likelihood of life expectancy, cancer recurrence, and / or cancer metastasis.

Methods for screening therapeutic agents for activity against dormant cancer cells, therapeutic agents identified by the methods, and treatment methods related to the same, and methods for screening therapeutic agents for activity against microscopic metastatic tumor cancer cells, therapeutic agents identified by the methods, and treatment methods related to the same.

Implantable scaffolds that treat solid tumors and escape variants and that provide effective vaccinations against cancer recurrence are described. The scaffolds include genetically-reprogrammed lymphocytes and a lymphocyte-activating moiety.

Glioblastomas (GBMs) are primary brain lesions with poor overall survival rates. Nearly 95% of patients die within 5 years of primary diagnosis. One of the leading factors to this high mortality is the inevitable nature of cancer recurrence. Disclosed herein are methods and compositions related to the identification and treatment of glioblastoma. Specifically, disclosed herein are methods for identifying progressing glioblastoma, and distinguishing it from pseudo-progression.

The invention belongs to the technical field of traditional Chinese medicines, and particularly relates to a traditional Chinese medicine composition for preventing and treating tumor cancer and resisting relapse, which comprises the following raw materials in parts by weight: 1-50 parts of sanqi, 1-50 parts of Chinese mahonia, 10-100 parts of gynostemma pentaphylla, 1-50 parts of wild poria cocos, 1-50 parts of local scorpion and 1-60 parts of wild gastrodia elata. The whole formula is synergistic, and the cachexia metabolic disorder is improved by adjusting the intestinal flora-immune axis; the traditional Chinese medicine composition integrates three treatment methods of promoting blood circulation to remove blood stasis, clearing away heat and toxic materials and supporting healthy energy, eliminates evil without hurting healthy energy through multi-channel cross regulation and control, and provides a traditional Chinese medicine innovative scheme for tumor prevention and treatment.

Compositions comprising migratory type 1 conventional dendritic cells in combination with a positively charged antigen capturing nanoparticle comprising a hydrophobic surface and use of the nanoparticle and dendritic cells optionally in combination with an immune checkpoint inhibitor in methods of treating cancer or preventing or reducing the risk of reoccurrence of a cancer in a subject.

The present invention relates to the fields of medicine and in particular cancer treatment. The invention more specifically relates to new compounds which are typically for use as a medicament. In particular, the invention relates to the use of these new compounds for increasing the presentation, typically the production and presentation, of Pioneer Translation Products (PTPs)-derived antigens by cells, in particular cancer cells, or changing the immunopeptidome, in a subject, and inducing or stimulating an immune response in the subject. The present disclosure also relates to uses of such compounds, in particular to prepare a pharmaceutical composition and / or to allow or improve the efficiency of a therapy in a subject in need thereof. The invention also discloses methods for treating a disease, in particular cancer, for preventing or treating cancer metastasis and / or cancer recurrence, in a subject. The present invention in addition provides kits suitable for preparing a composition according to the present invention and / or for implementing the herein described methods.

The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to extended treatment and cancer-free survival in a patient. In particular, the disclosure includes the identities of genes that are expressed in correlation with benefit in a switch in endocrine therapy used to treat a patient. The levels of gene expression are disclosed as a molecular index for predicting clinical outcome, and so prognosis, for the patient. The disclosure further includes methods for predicting cancer recurrence, and / or predicting occurrence of metastatic cancer, after initial treatment with an anti-estrogen agent. The disclosure further includes methods for determining or selecting the treatment of a subject based upon the likelihood of life expectancy, cancer recurrence, and / or cancer metastasis.

The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to cancer. In particular, the disclosure includes the identities of genes that are expressed in correlation with tumor grade. The levels of gene expression are disclosed as a molecular index for determining tumor grade in a patient and predicting clinical outcome, and so prognosis, for the patient. The molecular grading of cancer may optionally be used in combination with a second molecular index for diagnosing cancer and its prognosis. The disclosure further includes methods for predicting cancer recurrence, and / or predicting occurrence of metastatic cancer. For diagnosis or prognosis, the disclosure further includes methods for determining or selecting the treatment of cancer based upon the likelihood of life expectancy, cancer recurrence, and / or cancer metastasis.

In alternative embodiments, provided are methods for detecting a cancer, the method comprising: obtaining a sample comprising biological fluids or cells from a subject or human; isolating extracellular vesicles (EVs) having a selected diameter range; determining the presence and concentration of one or at least two proteins, Haptoglobin (HP) and Catalase (CAT), in the selected diameter range from the sample; and correlating the presence of a combination of the one or at least two proteins with a source of the sample, wherein if HP and CAT are individually detected, or if HP and CAT are both detected, then cancer has been positively detected. Also provided are methods for treating, lessoning the symptoms of or decreasing the chance of recurrence of, a cancer comprising administering to an individual in need thereof an antibody (Ab) or an antigen (Ag) binding fragment that specifically binds haptoglobin (HP) and / or a haptoglobin-hemoglobin complex.

The present disclosure provides gene expression profiles that are associated with cancer, including certain gene expression profiles that differentiate between cancer that is at a high risk of recurrence. The gene expression profiles can be measured at the nucleic acid or protein level. The gene expression profiles can also be used to identify a subject for cancer treatment. Also provided are kits for use in predicting cancer recurrence and / or prognosing cancer and an array comprising probes for detecting the unique gene expression profiles associated with cancer.