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: Disclosed herein are biomarkers and methods of using the same for determining the risk of recurrence of cancer in a subject. The methods may include determining the level of expression of at least one MHCII gene, determining the level of expression of at least one TIL gene, and determining an Immune Activation Score for the subject. Further provided are methods of diagnosing a subject with triple-negative breast cancer (TNBC) as having TNBC Basal-like subtype, and methods of treating cancer in a subject.

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: 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: 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: 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 an anthracycline. 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 anthracycline and administering the therapy in subjects when it is found that anthracycline is likely to be effective.

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 an anthracycline. 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 anthracycline and administering the therapy in subjects when it is found that anthracycline is likely to be effective.

Abstract: The application describes methods and kits for screening subjects with breast cancer to determine if the breast cancer will be responsive to a post-mastectomy breast cancer therapy including radiation. The application further describes methods and kits for treating subjects with post-mastectomy breast cancer by screening them for the likelihood of the effectiveness of treating the cancer with a therapy including radiation and administering the therapy in subjects when it is found that radiation is likely to be effective.

Abstract: Disclosed are compositions and methods related intrinsic gene sets and methods and compositions related to detecting and classifying 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: 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 an anthracycline. 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 anthracycline and administering the therapy in subjects when it is found that anthracycline is likely to be effective.

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.