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 disclosure includes 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 the patient, and likelihood that the patient will have a recurrence of prostate cancer, or to classify the tumor by likelihood of clinical outcome or TMPRSS2 fusion status.

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 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 algorithm-based molecular assays that involve measurement of expression levels of genes, or their co-expressed genes, from a biological sample obtained from a prostate cancer patient. The genes may be grouped into functional gene subsets for calculating a quantitative score useful to predict a likelihood of a clinical outcome for a prostate cancer patient.

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: 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: The present disclosure relates to uses of a multiple gene-expression based Genomic Prostate Score™ (GPS™) algorithm for assessment of various clinical endpoints in prostate cancer patients, such as risks of clinical recurrence (CR), biochemical recurrence (BCR), distant metastasis (Mets), and prostate cancer death (PCD). In some embodiments, GPS result is determined for low and intermediate risk prostate cancer patients in order to assist in determining treatment strategies for those patients.

Abstract: A predictive cancer model generates a cancer prediction for an individual of interest by analyzing values of one or more types of features that are derived from cfDNA obtained from the individual. Specifically, cfDNA from the individual is sequenced to generate sequence reads using one or more physical assays, examples of which include a small variant sequencing assay, whole genome sequencing assay, and methylation sequencing assay. The sequence reads of the physical assays are processed through corresponding computational analyses to generate each of small variant features, whole genome features, and methylation features. The values of features can be provided to a predictive cancer model that generates a cancer prediction. In some embodiments, the values of different types of features can be separately provided into different predictive models. Each separate predictive model can output a score that can serve as input into an overall model that outputs the cancer prediction.

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: The present disclosure includes 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 the patient, and likelihood that the patient will have a recurrence of prostate cancer, or to classify the tumor by likelihood of clinical outcome or TMPRSS2 fusion status.

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 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 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: 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.