Abstract:
The present disclosure provides gene and gene sets, the expression of which is important in the classification and/or prognosis of cancer, in particular of renal cell carcinoma.
Abstract:
The present disclosure provides gene and gene sets, the expression of which is important in the classification and/or prognosis of cancer, in particular of renal cell carcinoma.
Abstract:
The present invention provides algorithm-based molecular assays that involve measurement of expression levels of genes from a biological sample obtained from a kidney cancer patient. The present invention also provides methods of obtaining a quantitative score for a patient with kidney cancer based on measurement of expression levels of genes from a biological sample obtained from a kidney cancer patient. The genes may be grouped into functional gene subsets for calculating the quantitative score and the gene subsets may be weighted according to their contribution to cancer recurrence.
Abstract:
The present invention provides gene sets the expression of which is important in the diagnosis and/or prognosis of cancer, in particular of breast cancer.
Abstract:
The present invention provides algorithm-based molecular assays that involve measurement of expression levels of genes from a biological sample obtained from a kidney cancer patient. The present invention also provides methods of obtaining a quantitative score for a patient with kidney cancer based on measurement of expression levels of genes from a biological sample obtained from a kidney cancer patient. The genes may be grouped into functional gene subsets for calculating the quantitative score and the gene subsets may be weighted according to their contribution to cancer recurrence.
Abstract:
The present invention provides gene expression information useful for predicting whether a cancer patient is likely to have a beneficial response to treatment with chemotherapy, comprising measuring, in a biological sample comprising a breast tumor sample obtained from the patient, the expression levels of gene subsets to obtain a risk score associated with a likelihood of a beneficial response to chemotherapy, wherein the score comprises at least one of the following variables: (i) Recurrence Score, (ii) ESRI Group Score; (iii) Invasion Group Score; (iv) Proliferation Group Score; and (v) the expression level of the RNA transcript of at least one of MYBL2 and SCUBE2, or the corresponding expression product. The invention further comprises a molecular assay-based algorithm to calculate the likelihood that the patient will have a beneficial response to chemotherapy based on the risk score.
Abstract:
The present disclosure provides gene and gene sets, the expression of which is important in the classification and/or prognosis of cancer, in particular of renal cell carcinoma.
Abstract:
The present invention provides algorithm-based molecular assays that involve measurement of expression levels of genes from a biological sample obtained from a kidney cancer patient. The present invention also provides methods of obtaining a quantitative score for a patient with kidney cancer based on measurement of expression levels of genes from a biological sample obtained from a kidney cancer patient. The genes may be grouped into functional gene subsets for calculating the quantitative score and the gene subsets may be weighted according to their contribution to cancer recurrence.
Abstract:
Molecular assays that involve measurement of expression levels of prognostic biomarkers, or co-expressed biomarkers, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likely prognosis for said patient, and likelihood that said patient will have a recurrence of prostate cancer, or to classify the tumor by likelihood of clinical outcome or TMPRSS2 fusion status, are provided herein.
Abstract:
Molecular assays that involve measurement of expression levels of prognostic biomarkers, or co-expressed biomarkers, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likely prognosis for said patient, and likelihood that said patient will have a recurrence of prostate cancer, or to classify the tumor by likelihood of clinical outcome or TMPRSS2 fusion status, are provided herein.