22 results about "Response to therapy" patented technology

The present invention relates to a method for assessing whether a subject has Polycystic Ovarian Syndrome (PCOS) or is at risk of developing PCOS, to a method of selecting a patient for therapy of PCOS, to a method for monitoring PCOS progression or for monitoring response to treatment and to a computer-implemented method for assessing a subject with suspected PCOS, by determining the amount or concentration of Fibroblast Growth Factor-Binding Protein 1 (FGFBP1) in a sample of the subject.

The present disclosure provides methods and systems for screening or detecting a colorectal cancer or following colorectal disease progression that may be applied to cell-free nucleic acids such as cell-free DNA. The method may use detection of methylation signals within a single sequencing read in identified genomic regions as input features to train a machine learning model and generate a classifier useful for stratifying populations of individuals. The method may comprise extracting DNA from a cell-free sample obtained from a subject, converting the DNA for methylation sequencing, generating sequencing reads, and detecting colon proliferative cell disorder-associated signals in the sequencing information and training a machine learning model to provide a discriminator capable of distinguishing groups in a subject population such as healthy, cancer or distinguishing disease subtype or stage. The method may be used for, e.g., predicting, prognosticating, and / or monitoring response to treatment, tumor load, relapse, or colorectal cancer development.

Disclosed are methods and agents for predicting response to therapy, immune status and / or disease progression. More particularly, disclosed are methods, agents and kits for analyzing cellular distribution of PD-L2, including its nuclear localization, for stratifying a patient as a likely responder or non-responder to a therapy, for managing treatment of a patient with a therapy, for monitoring a disease in a patient following treatment with a therapy, for determining the status of a disease and / or for determining the immune status of a patient.

The present invention is directed to methods for detecting a plasma cell dyscrasia like myeloma or MGUS, methods for determining whether a plasma cell dyscrasiais stable or progressive, methods for determining a risk for disease relapse, and methods for determining a response by a subject having a plasma cell dyscrasia to a therapy.

This invention discloses a method and system for predicting a subject's response to a therapy by: obtaining a first plurality of nucleic acid sequences targeting genomic DNA from a sample of the subject's gut; determining multiple genomic abundance values ​​for various gut bacteria from the nucleic acid sequences; and applying a model to the plurality of genomic abundance values ​​to obtain a prediction of the subject's response to the therapy as the output of the model.

Disclosed are method and apparatus for identifying biomarkers and in particular for identifying biomarkers for use in making clinical assessments, such as early diagnostic, diagnostic, disease stage, disease severity, disease subtype, response to therapy or prognostic assessments. In one particular example, the techniques are applied to allow assessments of patients suffering from, suspected of suffering from, or with clinical signs of SIRS (Systemic Inflammatory Response Syndrome) being either infection-negative SIRS or infection-positive SIRS.

The present disclosure relates to methods of using biomarkers in cancer patients to predict responsiveness of the cancer patients to treatment.

Most drugs entering clinical trials fail, often related to an incomplete understanding of the mechanisms governing drug response. Machine learning techniques hold immense promise for better drug response predictions, but most have not reached clinical practice due to their lack of interpretability and their focus on monotherapies. Systems and methods described herein relate to DrugCell, an interpretable deep learning model of human cancer cells trained on the responses of 1,235 tumor cell lines to 684 drugs. Tumor genotypes induce states on cellular subsystems which are integrated with drug structure to predict response to therapy and, simultaneously, learn biological mechanisms underlying the drug response. DrugCell predictions are accurate in cell lines and also stratify clinical outcomes. Analysis of DrugCell mechanisms leads directly to design of synergistic drug combinations, which can be validate systematically. DrugCell provides a blueprint for constructing interpretable models for predictive medicine.

Provided herein are methods and kits that use specific biomarkers to identify subtypes of follicular lymphoma, selectively treat subtypes of follicular lymphoma (FL), identify subjects likely to be responsive to FL treatment, and predict the responsiveness of subjects to FL treatment. TIFF2026529040000042.tif122150

Disclosed herein are methods and systems for classifying a cancer from a subject. The methods and systems classify the cancer based on similar characteristics, e.g., molecular profiles. The methods and systems may be predictive of the subject's response to treatments based on the classification of the cancer. The methods and systems may be used to define improved therapies for subjects with cancers with limited treatment options, e.g., rare cancers.

The present invention relates to novel compounds of formula (I), or detectably labeled compounds, stereoisomers, racemic mixtures, pharmaceutically acceptable salts, hydrates, or solvates thereof, which can be used to image and quantify alpha-synuclein aggregates. Furthermore, the compounds can be used to diagnose diseases, disorders, or conditions associated with alpha-synuclein aggregates (e.g., Parkinson's disease or multiple system atrophy (MSA)), determine a predisposition to such diseases, disorders, or conditions, prognose such diseases, disorders, or conditions, monitor the progression of such diseases, disorders, or conditions in patients suffering from such diseases, disorders, or conditions, monitor the progression of such diseases, disorders, or conditions, and predict the responsiveness of patients suffering from such diseases, disorders, or conditions to treatment.

The invention is a method of predicting response to therapy in a cancer patient by serial sampling the patient's cell-free tumor nucleic acids to determine a change in the number of mutations per amount of plasma.

The present invention relates to novel compounds of formula (I), or detectably labeled compounds, stereoisomers, racemic mixtures, pharmaceutically acceptable salts, hydrates, or solvates thereof, which can be used to image and quantify alpha-synuclein aggregates. Furthermore, the compounds can be used to diagnose diseases, disorders, or conditions associated with alpha-synuclein aggregates (e.g., Parkinson's disease or multiple system atrophy (MSA)), determine a predisposition to such diseases, disorders, or conditions, prognose such diseases, disorders, or conditions, monitor the progression of such diseases, disorders, or conditions in patients suffering from such diseases, disorders, or conditions, monitor the progression of such diseases, disorders, or conditions, and predict the responsiveness of patients suffering from such diseases, disorders, or conditions to treatment.

The present invention relates to an in vitro method for diagnosing or assessing the progression of a condition in an individual or assessing the responsiveness / response of an individual to a treatment, comprising: counting the number of cells of interest and the number of cell debris of interest; -determining a circulating disease load (CDL) parameter which is a function of the number of target cells and the number of target cell debris; and-correlating the circulating disease load (CDL) parameter with the presence or progression of a condition or responsiveness / response to treatment in the individual.

Disclosed herein are methods, devices, and systems for accurately detecting and / or diagnosing a child having or at risk of developing necrotizing enterocolitis (NEC). In most embodiments, the child is currently suffering from congenital heart disease (CHD). The disclosed methods, devices, and systems may be useful in monitoring the administration and / or response to therapy for CHD and / or NEC. The disclosed methods, devices, and systems may involve detecting one or more biomarkers in a sample from the child, for example a plasma sample, wherein the sample is less than or equal to about 20 microliters.

Disclosed herein are differences in the features of immune cell populations in subjects with monoclonal gammopathy of unknown significance (MGUS) or smoldering myeloma (SMM), compared to subjects with multiple myeloma (MM). These features are useful in methods for monitoring progression from MGUS or SMM to MM in a subject. In some instances, certain features are also useful in methods for predicting the response of a subject's MM to therapy.

The present invention provides a quantitative liquid biopsy diagnostic system and methods for performing diagnostic assays. The system offers a liquid biopsy method using circulating tumor cells (CTCs) or White Blood Cells (WBC) subpopulations for precision cancer diagnosis, early detection of disease evolution, and cancer patient management. The invention utilizes selective plane illumination microscopy (SPIM) to deliver high sensitivity and specificity for the detection and isolation of individual CTCs, superseding the efficacy of existing methodologies for early cancer detection. Isolated CTCs can be analyzed for their molecular fingerprint, which can lead to matching genetic abnormalities with specific drug treatments. The system allows ex vivo observation of live CTC or WBC response to treatment. This observation of live cells offers the oncologist a new potential for optimizing therapeutic protocols by testing a patient's own cells, and then administering treatment to the patient with the expectation of improving efficacy and reducing toxicity to normal cells.

Disclosed are method and apparatus for identifying biomarkers and in particular for identifying biomarkers for use in making clinical assessments, such as early diagnostic, diagnostic, disease stage, disease severity, disease subtype, response to therapy or prognostic assessments. In one particular example, the techniques are applied to allow assessments of patients suffering from, suspected of suffering from, or with clinical signs of SIRS (Systemic Inflammatory Response Syndrome) being either infection-negative SIRS or infection-positive SIRS.

A method for detecting cancer susceptibility, early detection and predicting cancer behaviour by using specific markers and parameters described below: screening persons with high risk of getting / having a type of cancer; identifying CNV / SNP / MNP / Indel loci and / or CNV / SNP / MNP / Indel mutations specific to a cancer / cancer stage and common in the buffy coat and tumor of cancer patients / stage of cancer; predicting mutations that will occur when metastasis or recurrence of cancer / tumor occurs by identifying CNV / Indel / SNP / MNP loci and / or Indel / SNP / CNV / MNP mutations in buffy coat and tumor by analysis of defined and timed samples of buffy coat, primary, secondary / recurrent tumor; determining loci and mutations indicative of the tumor behaviour, selected from responsiveness to treatment, toxicity of therapies, dose optimization, minimal residual disease; indicative of progression of disease, timing of recurrence and determining pathways responsible for various behaviours.

The present disclosure relates to methods for characterizing cancer testis antigen burden ("CTAB"), for predicting cancer survival outcomes using CTAB analysis, and for recommending and / or treating cancer using CTAB analysis. Particularly, aspects are directed to measuring expression of a panel of cancer testis antigen (CTA) gene markers in a tumor sample from a subject, determining a CTAB based on the measured expression of the CTA gene markers, classifying, by comparing to a reference CTAB score from the same cancer or tumor type, the CTAB score as a high-CTAB score or a low-CTAB score, and identifying the subject as responsive to a treatment wherein (i) the high-CTAB score is indicative of responsiveness to the treatment, or (ii) the low-CTAB score is indicative of responsiveness to the treatment. The cancer is preferably non-small cell lung cancer (NSCLC).

A treatment of lung cancer, particularly small cell lung cancer, in a human subject using an anti-PD-1 antibody and optionally a chemotherapy is provided. In some embodiments, the small cell lung cancer is an advanced (e.g., locally advanced) or diffusive (e.g., stage III or stage IV), non-resectable or metastatic (e.g., with liver, lung or lymph node metastasis, e.g., with 2, 3 or more metastatic sites) lung cancer. In some embodiments, the chemotherapy is carboplatin and / or cis-platinum, and optionally further etoposide. In some embodiments, the SCLC is a small cell carcinoma. In some embodiments, the SCLC is a complex small cell carcinoma. In some embodiments, the treatment is a first-line treatment. In some embodiments, the claimed therapies are effective in the treatment of SCLC. In some embodiments, the human subject is a responder to a treatment by at least one measurement of a response to the treatment.