Abstract: The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to extended treatment and cancer-free survival in a patient. In particular, the disclosure includes the identities of genes that are expressed in correlation with benefit in a switch in endocrine therapy used to treat a patient. The levels of gene expression are disclosed as a molecular index for predicting clinical outcome, and so prognosis, for the patient. The disclosure further includes methods for predicting cancer recurrence, and/or predicting occurrence of metastatic cancer, after initial treatment with an anti-estrogen agent. The disclosure further includes methods for determining or selecting the treatment of a subject based upon the likelihood of life expectancy, cancer recurrence, and/or cancer metastasis.

Abstract: The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to cancer. In particular, the disclosure includes the identities of genes that are expressed in correlation with tumor grade. The levels of gene expression are disclosed as a molecular index for determining tumor grade in a patient and predicting clinical outcome, and so prognosis, for the patient. The molecular grading of cancer may optionally be used in combination with a second molecular index for diagnosing cancer and its prognosis. The disclosure further includes methods for predicting cancer recurrence, and/or predicting occurrence of metastatic cancer. For diagnosis or prognosis, the disclosure further includes methods for determining or selecting the treatment of cancer based upon the likelihood of life expectancy, cancer recurrence, and/or cancer metastasis.

Abstract: The invention provides methods for the use of gene expression measurements to classify or identify tumors in samples obtained from a subject in a clinical setting, such as in cases of formalin fixed, paraffin embedded (FFPE) samples.

Abstract: Methods and compositions for the identification of breast cancer grade signatures are provided. The signature profiles are identified based upon multiple sampling of reference breast tissue samples from independent cases of breast cancer and provide a reliable set of molecular criteria for identification of cells as being in one or more particular stages and/or grades of breast cancer.

Abstract: Methods and compositions are provided for the identification of expression signatures in ER+ breast cancer cases, where the signatures correlate with responsiveness, or lack thereof, to treatment with tamoxifen or another antiestrogen agent against breast cancer The signature profiles are identified based upon sampling of reference breast tissue samples from independent cases of breast cancer and provide a reliable set of molecular criteria for predicting the efficacy of treating a subject with breast cancer with tamoxifen or another antiestrogen agent against breast cancer. Additional methods and compositions are provided for predicting responsiveness to tamoxifen or another antiestrogen agent against breast cancer in cases of breast cancer by use of three biomarkers. Two biomarkers display increased expression correlated with tamoxifen response while the third biomarker displays decreased expression correlated with tamoxifen response.

Abstract: The disclosure provides methods for the use of gene expression measurements to classify or identify among 54 cancer types in samples obtained from a subject in a clinical setting, such as in cases of formalin fixed, paraffin embedded (FFPE) samples.

Abstract: The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to cancer. In particular, the disclosure includes the identities of genes that are expressed in correlation with tumor grade. The levels of gene expression are disclosed as a molecular index for determining tumor grade in a patient and predicting clinical outcome, and so prognosis, for the patient. The molecular grading of cancer may optionally be used in combination with a second molecular index for diagnosing cancer and its prognosis. The disclosure further includes methods for predicting cancer recurrence, and/or predicting occurrence of metastatic cancer. For diagnosis or prognosis, the disclosure further includes methods for determining or selecting the treatment of cancer based upon the likelihood of life expectancy, cancer recurrence, and/or cancer metastasis.

Abstract: The disclosure provides methods for the use of gene expression measurements to classify or identify among 54 cancer types in samples obtained from a subject in a clinical setting, such as in cases of formalin fixed, paraffin embedded (FFPE) samples.

Abstract: Methods and compositions for the identification of breast cancer grade signatures are provided. The signature profiles are identified based upon multiple sampling of reference breast tissue samples from independent cases of breast cancer and provide a reliable set of molecular criteria for identification of cells as being in one or more particular stages and/or grades of breast cancer.

Abstract: The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to prostate cancer. In particular, the disclosure is based on the identities of genes that are correlated with patient survival and prostate cancer recurrence. The gene expression profiles may be embodied in nucleic acid expression, protein expression, or other expression formats and used to predict the survival of subjects afflicted with prostate cancer and to predict prostate cancer recurrence. The profiles may also be used in the study and/or diagnosis of prostate cancer cells and tissue as well as for the study and/or determination of prognosis of a patient. When used for diagnosis or prognosis, the profiles may be used to determine the treatment of prostate cancer based upon probable life expectancy and cancer recurrence and/or metastasis.

Abstract: Methods and compositions are provided for the identification of expression signatures in ER+ breast cancer cases, where the signatures correlate with responsiveness, or lack thereof, to tamoxifen treatment. The signature profiles are identified based upon sampling of reference breast tissue samples from independent cases of breast cancer and provide a reliable set of molecular criteria for predicting the efficacy of treating a subject with ER+ breast cancer with tamoxifen. Additional methods and compositions are provided for predicting tamoxifen responsiveness in cases of ER+ breast cancer by use of three biomarkers. Two biomarkers display increased expression correlated with tamoxifen response while the third biomarker displays decreased expression correlated with tamoxifen response.