Abstract: The present disclosure provides a method for generating a calculated cancer signature for a cancer-related phenotype based on copy number alterations (CNAs) in a patient sample. The calculated cancer signature may correspond to a somatic mutation, an mRNA expression signature, or a protein expression signature. The disclosure also provides a method treating a patient using the calculated cancer phenotype. In addition, the disclosure provides a method for generating a calculated signature based on CNAs to replicate a cancer phenotype.

Abstract: Methods and compositions are provided for determining a pan-cancer clustering of cluster assignment (COCA) subtype of a cancer in an individual by detecting the expression level of at least one classifier biomarker selected from a group of classifier biomarkers for COCA subtypes. Also provided herein are methods and compositions for determining the response of an individual with a COCA subtype to a therapy such as immunotherapy.

Abstract: Methods are provided for determining a subtype of head and neck squamous cell carcinoma (HNSCC) of an individual by detecting the expression level of at least one subtype classifier selected from a group of genes that are relevant for determining HNSCC subtypes. Also provided herein are methods for determining a suitable treatment and predicting the overall survival and the likelihood of metastasis for the HNSCC patients according to their subtypes.

Abstract: The present invention provides methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer. Methods of the invention further include means for evaluating gene expression profiles, including microarrays and quantitative polymerase chain reaction assays, as well as kits comprising reagents for practicing the methods of the invention.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: Methods and compositions are provided for determining a pan-cancer clustering of cluster assignment (COCA) subtype of a cancer in an individual by detecting the expression level of at least one classifier biomarker selected from a group of classifier biomarkers for COCA subtypes. Also provided herein are methods and compositions for determining the response of an individual with a COCA subtype to a therapy such as immunotherapy.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: This new method relates to the development of a chemoendocrine score (CES), based on the known analysis PAM50 for predicting whether a patient with breast cancer will respond to chemotherapy or to endocrine therapy, specifically in a patient with HR+/HER2? breast cancer beyond the risk of recurrence (ROR) and PAM50 intrinsic subtypes. Specifically, the clinical utility of this CES predictor is based on the intermediate PAM50 ROR group, the proportion of each CES group (sensitive to endocrine therapy, intermediate, and sensitive to chemotherapy) being greater than 25%.

Abstract: The present invention provides methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer. Methods of the invention further include means for evaluating gene expression profiles, including microarrays and quantitative polymerase chain reaction assays, as well as kits comprising reagents for practicing the methods of the invention.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: Compositions and methods useful in determining the major morphological types of lung cancer are provided. The methods include detecting expression of at least one gene or biomarker in a sample at the protein or nucleic level. The expression of the gene or biomarker can be indicative of the lung tumor subtype as well as prognostic and predictive for therapeutic response. The compositions and methods provided herein are suited for analysis of gene or biomarker expression at the protein or nucleic acid level in paraffin-embedded tissues.

Abstract: Compositions and methods useful in determining the major morphological types of lung cancer are provided. The methods include detecting expression of at least one gene or biomarker in a sample. The expression of the gene or biomarker is indicative of the lung tumor subtype. The compositions include subsets of genes that are monitored for gene expression. The gene expression is capable of distinguishing between normal lung parenchyma and the major morphological types of lung cancer. The gene expression and somatic mutation data are useful in developing a complete classification of lung cancer that is prognostic and predictive for therapeutic response. The methods are suited for analysis of paraffin-embedded tissues. Methods of the invention include means for monitoring gene or biomarker expression including PCR and antibody-based detection. The biomarkers of the invention are genes and/or proteins that are selectively expressed at a high or low level in certain tumor subtypes.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: Disclosed are compositions and methods related intrinsic gene sets and methods and compositions related to detecting and classifying cancer.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer.

Abstract: The application describes methods for screening subjects with breast cancer to determine if the breast cancer will be responsive to a breast cancer therapy including a taxane or a taxane derivative. The application also describes methods for treating subjects with breast cancer by screening them for the likelihood of the effectiveness of treating the cancer with a therapy including a taxane or a taxane derivative and administering the therapy in subjects when it is found that a taxane or a taxane derivative is likely to be effective.

Abstract: Methods for diagnosing and for evaluating the prognosis of a cancer patient, particularly a breast cancer patient, are provided. The methods include determining expression levels of at least five biomarkers in a body sample including a cancer cell from the patient, where expression levels of the biomarkers are indicative of cancer prognosis. Overexpression of the biomarkers of the invention is indicative of a poor prognosis. In some embodiments, the body sample is a breast tissue sample, particularly a primary breast tumor sample. The methods of the invention can be used in combination with assessment of conventional clinical factors and permit a more accurate evaluation of breast cancer prognosis.

Abstract: The application describes methods for screening subjects with breast cancer to determine if the breast cancer will be responsive to a breast cancer therapy including a taxane or a taxane derivative. The application also describes methods for treating subjects with breast cancer by screening them for the likelihood of the effectiveness of treating the cancer with a therapy including a taxane or a taxane derivative and administering the therapy in subjects when it is found that a taxane or a taxane derivative is likely to be effective.