Abstract: Disclosed are gene signatures that may be used to predict the recurrence of colorectal cancer in a human patient. These signatures can be used to determine when to treat a patient with post-operative adjuvant chemotherapy, i.e., when a high risk of colorectal cancer recurrence is predicted.

Abstract: Disclosed are gene signatures that may be used to predict the recurrence of colorectal cancer in a human patient. These signatures can be used to determine when to treat a patient with post-operative adjuvant chemotherapy, i.e., when a high risk of colorectal cancer recurrence is predicted.

Abstract: Disclosed are gene signatures that may be used to predict the recurrence of colorectal cancer in a human patient. These signatures can be used to determine when to treat a patient with post-operative adjuvant chemotherapy, i.e., when a high risk of colorectal cancer recurrence is predicted.

Abstract: A two-tiered classification system that can be integrated with the current algorithm used by pathologists for identification of the site of origin for ‘malignancy with unknown primary’ is presented. In use, morphology, immunohistochemical (IHC) studies, and microarray-based top tier gene expression classifiers first subclassify cytokeratin positive carcinomas into adenocarcinoma, squamous cell carcinoma, neuroendocrine carcinoma and urothelial carcinoma. Subsequently, organ-specific IHC-markers, if available, are used in conjunction with microarray-based second tier gene expression classifiers to assign the primary site of origin to the sample. This new hybrid approach combines IHC with a hierarchy of quantitative gene expression based classifiers into an algorithmic method that can assist pathologists to further refine and support their decision making process.

Abstract: Actively dividing tumors appear to progress to a life threatening condition more rapidly than slowly dividing tumors. Assessing actively dividing tumors currently involves a manual assessment of the number of mitotic cells in a histological slide prepared from the tumor and assessed by a trained pathologist. Disclosed is a method for using cumulative information from a series of expressed genes to determine tumor prognosis. This cumulative information can be used to categorize tumor samples into high mitotic states or low mitotic states using a mathematical algorithm and gene expression data derived from microarrays or quantitative-Polymerase Chain Reaction (Q-PCR) data. The specific mathematical description outlines how the algorithm assesses the most informative subset of genes from the full list of genes during the assessment of each sample.

Abstract: In one aspect, methods, markers, and expression signatures are disclosed for assessing the degree to which a cell sample has epithelial cell-like properties or mesenchymal cell-like properties. In another aspect, methods are provided for predicting cancer patient prognosis based on whether the cancer is classified as having a high or low EMT Signature Score.

Abstract: A two-tiered classification system that can be integrated with the current algorithm used by pathologists for identification of the site of origin for ‘malignancy with unknown primary ’ is presented. In use, morphology, immunohistochemical (IHC) studies, and microarry-based top tier gene expression classifiers first subclassify cytokeratin positive carcinomas into adenocarcinoma, squamous cell carcinoma, neuroendocrine carcinoma and urothelial carcinoma. Subsequently, organ-specific IHC-markers, if available, are used in conjunction with microarray-based second tier gene expression classifiers to assign the primary site of origin to the sample. This new hybrid approach combines IHC with a hierarchy of quantitative gene expression based classifiers into an algorithmic method that can assist pathologists to further refine and support their decision making process.

Abstract: Computers, computer program products, and methods for identifying a plurality of subjects for a clinical trial are provided. A candidate set of molecular profiles in a stored plurality of molecular profiles are identified. Each such profile has measurements for a discriminating set of cellular constituents that match the measurements of corresponding cellular constituents in a responder set of biological samples, thereby identifying the plurality of subjects for the trial from those subjects from which the candidate set of molecular profiles were derived. Each respective molecular profile in the stored plurality of profiles has measurements of a plurality of cellular constituents from a respective biological sample in a plurality of samples obtained from a first plurality of subjects.

Abstract: Computers, computer program products, and methods for identifying a plurality of subjects for a clinical trial are provided. A candidate set of molecular profiles in a stored plurality of molecular profiles are identified. Each such profile has measurements for a discriminating set of cellular constituents that match the measurements of corresponding cellular constituents in a responder set of biological samples, thereby identifying the plurality of subjects for the trial from those subjects from which the candidate set of molecular profiles were derived. Each respective molecular profile in the stored plurality of profiles has measurements of a plurality of cellular constituents from a respective biological sample in a plurality of samples obtained from a first plurality of subjects.

Abstract: Computers, computer program products, and methods for identifying a plurality of subjects for a clinical trial are provided. A candidate set of molecular profiles in a stored plurality of molecular profiles are identified. Each such profile has measurements for a discriminating set of cellular constituents that match the measurements of corresponding cellular constituents in a responder set of biological samples, thereby identifying the plurality of subjects for the trial from those subjects from which the candidate set of molecular profiles were derived. Each respective molecular profile in the stored plurality of profiles has measurements of a plurality of cellular constituents from a respective biological sample in a plurality of samples obtained from a first plurality of subjects.

Abstract: The invention provides a molecular marker set that can be used for prognosis of breast cancer in a patient using histologically normal tissue. The invention also provides methods for evaluating prognosis of breast cancer in a patient based on a molecular molecular signature.

Abstract: A classifier to predict cellular radiation sensitivity based on gene expression profiles in thirty-five cell lines from the NCI panel of 60 cancer cell lines (NCI-60), using a novel approach to predictive gene analysis. Three novel genes are provided, retinoblastoma binding protein 4 (RbAp48), G-protein signaling regulator 19 (RGS19) and ribose-5-phosphate isomerase A (R5PIA) whose expression values were correlated with radiation sensitivity.

Abstract: Actively dividing tumors appear to progress to a life threatening condition more rapidly than slowly dividing tumors. Assessing actively dividing tumors currently involves a manual assessment of the number of mitotic cells in a histological slide prepared from the tumor and assessed by a trained pathologist. Disclosed is a method for using cumulative information from a series of expressed genes to determine tumor prognosis. This cumulative information can be used to categorize tumor samples into high mitotic states or low mitotic states using a mathematical algorithm and gene expression data derived from microarrays or quantitative-Polymerase Chain Reaction (Q-PCR) data. The specific mathematical description outlines how the algorithm assesses the most informative subset of genes from the full list of genes during the assessment of each sample.

Abstract: Computers, computer program products, and methods for identifying a plurality of subjects for a clinical trial are provided. A candidate set of molecular profiles in a stored plurality of molecular profiles are identified. Each such profile has measurements for a discriminating set of cellular constituents that match the measurements of corresponding cellular constituents in a responder set of biological samples, thereby identifying the plurality of subjects for the trial from those subjects from which the candidate set of molecular profiles were derived. Each respective molecular profile in the stored plurality of profiles has measurements of a plurality of cellular constituents from a respective biological sample in a plurality of samples obtained from a first plurality of subjects.

Abstract: The invention provides a molecular marker set that can be used for prognosis of colorectal cancer in a colorectal cancer patient. The invention also provides methods and computer systems for evaluating prognosis of colorectal cancer in a colorectal cancer patient based on the molecular marker set. The invention also provides methods and computer systems for determining chemotherapy for a colorectal cancer patient and for enrolling patients in clinical trials.

Abstract: The present invention pertains to specific gene signatures for cancer that are used to predict survival and novel processes for identifying such gene signatures. In one embodiment, gene signatures for human colorectal cancer are identified and outcomes are linked to the specific gene signatures using significance analysis of microarrays (SAM) and support vector machines (SVM) to provide a prognosis/survival classifier.

Abstract: A classifier to predict cellular radiation sensitivity based on gene expression profiles in thirty-five cell lines from the NCI panel of 60 cancer cell lines (NCI-60), using a novel approach to predictive gene analysis. Three novel genes are provided, retinoblastoma binding protein 4 (RbAp48), G-protein signaling regulator 19 (RGS19) and ribose-5-phosphate isomerase A (R5PIA) whose expression values were correlated with radiation sensitivity.