Abstract: Methods and compositions are provided for oligonucleotides that bind targets of interest. The targets include cells and microvesicles, such as those derived from various diseases. The oligonucleotides can be used for diagnostic and therapeutic purposes. The target of the oligonucleotides can be a target such as PARP1, HIST1H1B, HIST1H1D, NCL, FBL, SFPQ, RPL12, ACTB, HIST1H4A, SSBP1, NONO, H2AFJ, and DDX21, or a complex, subunit or fragment thereof.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that predict cancer patient benefit from PARP inhibitors.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that predict cancer patient benefit from immunotherapy such as checkpoint inhibitor therapy.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that correlate with response of cancer patients to platinum-based chemotherapy. Described herein are data structures, data processing, and machine learning models to predict a probability of benefit of a treatment for a disease or disorder of a subject having a particular set of biomarkers, as well as an exemplary application of such a model to precision medicine, e.g., to methods for selecting a treatment based on a molecular profile, e.g., a treatment comprising platinum therapy.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be used to train machine learning models using disease outcomes to identify biomarker signatures that can provide a prediction of such outcomes. This approach has been applied to identify biomarker signatures and machine learning models that can predict metastatic potential.

Abstract: Methods and compositions are provided for oligonucleotides that bind targets of interest. The targets include cells and microvesicles, such as those derived from various diseases. The oligonucleotides can be used for diagnostic and therapeutic purposes. The target of the oligonucleotides can be a target such as PARP1, HIST1H1B, HIST1H1D, NCL, FBL, SFPQ, RPL12, ACTB, HIST1H4A, SSBP1, NONO, H2AFJ, and DDX21, or a complex, subunit or fragment thereof.

Abstract: Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that predict cancer patient benefit from immunotherapy such as checkpoint inhibitor therapy.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. Here, we used molecular profiling data to identify biomarker signatures (biosignatures) that predict a tumor primary lineage, cancer category or type, organ group and/or histology. The signature may use genomic and transcriptome level information.

Abstract: Methods and compositions are provided for oligonucleotides that bind targets of interest. The targets include cells and microvesicles, such as those derived from various diseases. The oligonucleotides can be used for diagnostic and therapeutic purposes. The target of the oligonucleotides can be a target such as PARP1, HIST1H1B, HIST1H1D, NCL, FBL, SFPQ, RPL12, ACTB, HIST1H4A, SSBP1, NONO, H2AFJ, and DDX21, or a complex, subunit or fragment thereof.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that correlate with response of cancer patients to platinum-based chemotherapy. Described herein are data structures, data processing, and machine learning models to predict a probability of benefit of a treatment for a disease or disorder of a subject having a particular set of biomarkers, as well as an exemplary application of such a model to precision medicine, e.g., to methods for selecting a treatment based on a molecular profile, e.g., a treatment comprising platinum therapy.

Abstract: Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that strongly correlate with response of colorectal cancer patients to FOLFOX. Described herein are data structures, data processing, and machine learning models to predict effectiveness of a treatment for a disease or disorder of a subject having a particular set of biomarkers, as well as an exemplary application of such a model to precision medicine, e.g., to methods for selecting a treatment based on a molecular profile, e.g., a treatment comprising administration of 5-fluorouracil/leucovorin combined with oxaliplatin (FOLFOX) or with irinotecan (FOLFIRI).

Abstract: Methods and compositions are provided for oligonucleotide probes and oligonucleotide probe libraries that recognize targets of interest. The targets include circulating biomarkers such as microvesicles, including those derived from various diseases.

Abstract: Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that strongly correlate with response of colorectal cancer patients to FOLFOX. Described herein are data structures, data processing, and machine learning models to predict effectiveness of a treatment for a disease or disorder of a subject having a particular set of biomarkers, as well as an exemplary application of such a model to precision medicine, e.g., to methods for selecting a treatment based on a molecular profile, e.g., a treatment comprising administration of 5-fluorouracil/leucovorin combined with oxaliplatin (FOLFOX) or with irinotecan (FOLFIRI).

Abstract: Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Abstract: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. Here, we used molecular profiling data to identify biomarker signatures that predict a tumor primary lineage or organ group.

Abstract: Methods and compositions are provided for oligonucleotides that bind targets of interest. The targets include cells and microvesicles, such as those derived from various diseases. The oligonucleotides can be used for diagnostic and therapeutic purposes. The target of the oligonucleotides can be a therapeutic target such as Complement Component 1, Q Subcomponent (C1q) or a subunit thereof.

Abstract: Methods and compositions are provided for specific aptamers and aptamer pools that bind biomarkers of interest such as microvesicle surface antigens or functional fragments of microvesicle surface antigens. In various embodiments, aptamers of the invention are used in diagnostic, prognostic, or theranostic processes to screen a biological sample for the presence or levels of biomarkers such as microvesicles that are determined to provide a diagnostic, prognostic, or theranostic readout. The diagnosis, prognosis, or theranosis may be related to cancer or other diseases and disorders. The invention also provides methods and composition to facilitate aptamer library screening and aptamer detection methods.