Merck Sharp + Dohme Corp.

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

The Wistar Institute

University of Pennsylvania

Michael V Nebozhyn

Andrey Loboda

Timothy J Yeatman

James J Mulé

Domenico Coppola

Terrill K McClanahan

Louise C Showe

Mark David Ayers

Jared K Lunceford

Steven M Albelda

Erin E Murphy

Michael Showe

Anil Vachani

Heather Hirsch

Audrey Loboda

James Watters

Michael Chastain

Laszlo Kari

Jared Lunceford

Terrill K Mcclanahan

Richard A Klinghoffer

James W Watters

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 treating subjects with breast cancer, based on tumor expression levels of chemokines.

Immune gene signatures in treating breast cancer

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

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

The present invention is a method distinguishing between head and neck squamous cell carcinoma and lung squamous cell carcinoma. In particular, a 10-gene classifier has been identified which can be used to distinguish between primary squamous cell carcinoma of the lung and metastatic head and neck squamous cell carcinoma. These genes include CXCL13, COL6A2, SFTPB, KRT14, TSPYL5, TMP3, KLK10, MMP1, GAS1, and MYH2. A panel of one or more of these genes, or proteins encoded thereby, can be used for early diagnosis and selection of an appropriate therapeutic treatment.

Method for distinguishing between head and neck squamous cell carcinoma and lung squamous cell carcinoma

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Yeadon, PA, United States of America

Michael V Nebozhyn