Abstract: The present invention relates, in general, to gene expression profiles, and in particular, to a gene expression profile of an environmental exposure, ionizing radiation. The invention further relates to methods of screening patients for radiation exposure based on gene expression profiling and to kits suitable for use in such methods.

Abstract: The present invention relates, in general, to gene expression profiles, and in particular, to a gene expression profile of an environmental exposure, ionizing radiation. The invention further relates to methods of screening patients for radiation exposure based on gene expression profiling and to kits suitable for use in such methods.

Abstract: The invention provides for compositions and methods for predicting an individual's responsitivity to cancer treatments and methods of treating cancer. In certain embodiments, the invention provides compositions and methods for predicting an individual's responsitivity to chemotherapeutics, including platinum-based chemotherapeutics, to treat cancers such as ovarian cancer. Furthermore, the invention provides for compositions and methods for predicting an individual's responsivity to salvage therapeutic agents. By predicting if an individual will or will not respond to platinum-based chemotherapeutics, a physician can reduce side effects and toxicity by administering a particular additional salvage therapeutic agent. This type of personalized medical treatment for ovarian cancer allows for more efficient treatment of individuals suffering from ovarian cancer.

Abstract: Provided herein are methods for predicting the responsiveness of a cancer to a chemotherapeutic agent using gene expression profiles. In particular, methods for predicting the responsiveness to 5-fluorouracil, adriamycin, cytotoxan, docetaxol, etoposide, taxol, topotecan, PB kinase inhibitors and Src inhibitors are provided. Methods for developing treatment plans for individuals with cancer are also provided. Kits including gene chips and instructions for predicting responsiveness and computer readable media comprising responsivity information are also provided.

Abstract: Provided herein are methods for the use of gene expression profiling to determine whether an individual afflicted with cancer will respond to a therapy, and in particular to therapeutic agents such as platinum-based agents and antimetabolite agents. Methods for the treatment of individuals with the therapeutic agents are also provided. Methods of predicting the efficacy of cancer therapeutic agents such as platinum-based and antimetabolite therapeutic agents are also provided. Kits including gene chips and instructions for predicting responsiveness are also provided.

Abstract: The invention provides methods of estimating the likelihood of lung cancer recurrence in a subject, including those afflicted with NSCLC. The methods of the invention are useful for developing a therapeutic treatment plan to prevent cancer recurrence for subjects deemed to be at high risk, and withholding treatments from those subjects deemed to be at low risk. The invention also provides methods of generating and using metagene-based prediction tree models for estimating the likelihood of lung cancer recurrence. The invention also provides reagents, such as DNA microarrays, software and computer systems useful for estimating cancer recurrence, and provides methods of conducting a diagnostic business for the prediction of cancer recurrence.

Abstract: The statistical analysis described and claimed is a predictive statistical tree model that overcomes several problems observed in prior statistical models and regression analyses, while ensuring greater accuracy and predictive capabilities. Although the claimed use of the predictive statistical tree model described herein is directed to the prediction of a disease in individuals, the claimed model can be used for a variety of applications including the prediction of disease states, susceptibility of disease states or any other biological state of interest, as well as other applicable non-biological states of interest. This model first screens genes to reduce noise, applies k-means correlation-based clustering targeting a large number of clusters, and then uses singular value decompositions (SVD) to extract the single dominant factor (principal component) from each cluster.

Abstract: The disclosure relates to identifying deregulated pathways in cancer. In certain embodiments, the methods of the disclosure can be used to evaluate therapeutic agents for the treatment of cancer.

Abstract: The invention provides for compositions and methods for predicting an individual's responsitivity to cancer treatments and methods of treating cancer. In certain embodiments, the invention provides compositions and methods for predicting an individual's responsitivity to chemotherapeutics, including salvage agents, to treat cancers such as ovarian cancer. The invention also provides reagents, such as DNA microarrays, software and computer systems useful for personalizing cancer treatments, and provides methods of conducting a diagnostic business for personalizing cancer treatments.

Abstract: The statistical analysis described and claimed is a predictive statistical tree model that overcomes several problems observed in prior statistical models and regression analyses, while ensuring greater accuracy and predictive capabilities. Although the claimed use of the predictive statistical tree model described herein is directed to the prediction of estrogen receptor status in individuals, the claimed model can be used for a variety of applications including the prediction of disease states, susceptibility of disease states or any other biological state of interest, as well as other applicable non-biological states of interest. This model first screens genes to reduce noise, applies k-means correlation-based clustering targeting a large number of clusters, and then uses singular value decompositions (SVD) to extract the single dominant factor (principal component) from each cluster.

Abstract: Genes whose expression is correlated with and determinant of an atherosclerotic phenotype are provided. Also provided are methods of using the subject atherosclerotic determinant genes in diagnosis and treatment methods, as well as drug screening methods. In addition, reagents and kits thereof that find use in practicing the subject methods are provided. Also provided are methods of determining whether a gene is correlated with a disease phenotype, where correlation is determined using at least one parameter that is not expression level and is preferably determined using a Bayesian analysis.

Abstract: The present invention provides methods for detecting the oncogenic state of cells by detecting the complex formation between the E2F transcription factor and the retinoblastoma (Rb) protein. A first embodiment is a diagnostic assay for detecting the state of Rb function of cells by collecting a cell sample and then detecting free E2F in the cell sample, the presence of free E2F indicating the loss of Rb function of the cells. A second embodiment is a bioassay for screening test compounds for the ability to inhibit the oncogenic state of cells. The bioassay comprises contacting a test compound to a cell capable of producing a complex of the Rb protein and the E2F transcription factor, the cell containing a virus expressing a viral oncoprotein capable of disrupting the complex, and then detecting the appearance of the E2F-Rb complex in the cells, the presence of the E2F-Rb complex indicating the oncogenic state of said cells.