Merck Sharp + Dohme Corp.

H. Lee Moffitt Cancer Center and Research Institute, Inc.

The Wistar Institute

Andrey Loboda

Michael V Nebozhyn

Terrill K McClanahan

Timothy J Yeatman

Mark David Ayers

Domenico Coppola

James J Mulé

Jared K Lunceford

Louise C Showe

Erin E Murphy

Michael Showe

Heather Hirsch

James Watters

Laszlo Kari

Jacqueline W Pierce

Valeria R Fantin

Jared Lunceford

Terrill K Mcclanahan

Richard A Klinghoffer

James W Watters

Pearl S Huang

A gene expression platform, which is a combination of a set of genes that are correlated with response to a PD-1 antagonist in multiple tumor types and a normalization gene set, is disclosed. A method and system of using the gene expression platform to derive gene signature biomarkers of anti-tumor response to a PD-1 antagonist and to test patient samples for predictive gene signature biomarkers are also disclosed.

System and methods for deriving gene signature biomarkers of response to PD-1 antagonists

The present disclosure describes baseline and on treatment blood-based gene signature biomarkers that are predictive of tumor sensitivity to therapy with a PD-1 antagonist. The on-treatment biomarkers comprise a PD-L1 gene signature or an interferon gamma gene signature and the baseline gene signature biomarker comprises genes associated with the oxidative phosphorylation pathway. The disclosure also provides methods and kits for testing tumor samples for these biomarkers, as well as methods for treating subjects with a PD-1 antagonist based on the test results.

Blood-based biomarkers of tumor sensitivity to PD-1 antagonists

This invention relates to methods for selecting a treatment, treating, and predicting survival time in subjects with cancer, such as colorectal cancer, based on tumor expression levels of chemokines, cytotoxic genes, and/or dendritic cell genes.

Immune gene signatures in cancer

Methods, biomarkers, and expression signatures are disclosed for assessing the regulation status of growth factor pathway signaling in a cell sample or subject. More specifically, several aspects of the invention provide a set of genes which can be used as biomarkers and gene signatures for evaluating growth factor pathway deregulation status in a sample; classifying a cell sample as having a deregulated or regulated growth factor signaling pathway; determining whether an agent modulates the growth factor signaling pathway in sample; predicting response of a subject to an agent that modulates the growth factor signaling pathway; assigning treatment to a subject; and predicting evaluating the pharmacodynamic effects of cancer therapies designed to regulate growth factor pathway signaling.

Methods and gene expression signature for assessing growth factor signaling pathway regulation status

The invention disclosed herein describes novel biomarkers useful for risk assessment, screening, prognosis and selection and monitoring of therapy for HDAC mediated cell proliferative disorders. In particular, the invention provides the identities of three particular proteins whose expression patterns are strongly predictive of a particular patient's treatment outcome, e.g., non-responsiveness to SAHA. The expression profile, or pattern, whether embodied in nucleic acid expression, protein expression, or other expression formats will find use in identifying and selecting patients afflicted with a particular HDAC mediated cancer who are likely to be non-responsive to SAHA-based therapy and thus candidates for other treatments.

Methods for predicting treatment response based on the expression profiles of protein and transcription biomarkers

A method of developing a gene expression profile indicative of the presence or stage of a selected a disease, disorder or genetic pathology in a mammalian subject employs penalized discriminant analysis with recursive feature elimination. A method of diagnosing a cancer in a mammalian subject includes the steps of examining a sample containing the subject's immune cells and detecting a variance in the expression of a statistically significant number of genes, e.g., at least 10 non-tumor genes from those same genes in a characteristic disease or healthy gene expression profile. A significant variance in expression of these genes when compared to a gene expression profile, preferably an average gene expression profile of a normal control, or significant similarities to an average gene profile of subjects with cancer, correlates with a specific type of cancer and/or location of tumor.

Method of diagnosis of cancer based on gene expression profiles in cells

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Philadelphia, PA, United States of America

Andrey Loboda