Genomic Health, Inc.

Bristol-myers Squibb Compnay

Tara Maddala

Steven Shak

Dejan Knezevic

Audrey Goddard

Joffre B Baker

Michael C Kiefer

Michael R Crager

Frederick L Baehner

Wayne Cowens

Mark Lee

Robert J Pelham

Diana Cherbavaz

William F Novotny

Carl L Millward

Margarita Lopatin

Christer Svedman

George Andrew Watson

Drew Watson

Steve Shak

Shirin K Ford

Hugh Jeffrey Lawrence

William Novotny

Phillip Febbo

David J Mauro

Nan Zhang

Robert Pelham

Ruixiao Lu

Joffre Baker

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.

Method to use gene expression to determine likelihood of clinical outcome of renal cancer

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.

Gene expression profile algorithm for calculating a recurrence score for a patient with kidney cancer

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.

Gene expression profile algorithm and test for determining prognosis of prostate cancer

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.

Method for using gene expression to determine prognosis of prostate cancer

The present invention provides methods and compositions to facilitate determining whether an EGFR-expressing cancer in an individual is an EGFR inhibitor-responsive cancer, as well as methods for determining the likelihood that a patient having an EGFR-expressing cancer will exhibit a beneficial response to an EGFR inhibitor therapy. The methods generally involve determining a normalized expression level of a gene product that correlates with EGFR inhibitor responsiveness.

Predictors of patient response to treatment with EGF receptor inhibitors

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Sunnyvale, CA, United States of America

Tara Maddala