Foundation Medicine, Inc.

Genentech, Inc.

Vanderbilt University

Gritstone Bio, Inc.

James Xin Sun

Roman Yelensky

Philip James Stephens

Garrett Michael Frampton

David Fabrizio

Priti Hegde

Sanjeev Mariathasan

Richard Bourgon

Gregg Fine

Vincent A Miller

Ciaran Daniel Scallan

Leonid Gitlin

Marcin Kowanetz

Karin Jooss

David Shames

Amy Rachel Rappaport

Douglas B Johnson

Jeffrey Alan Sosman

Christine Marie Lovly

Monica Lane

Christine Denise Palmer

Wei Zou

Caitlin F Connelly

Zachary R Chalmers

Philip J Stephens

Garrett Michaell Frampton

Priti Hedge

Methods and systems for analyzing genetic variants are disclosed. The methods and systems can be used to classify a variant in a tumor sample as germline, somatic, subclonal, or ambiguous. The variant can be classified by fitting a genome-wide copy number model to a sequence coverage input and a SNP allele frequency input. The fitted model can be used to determine a tumor purity, and a total copy number and a minor allele copy number for each of a plurality of genomic segments. Using the tumor purity, the total copy number and the minor allele copy number for the genomic segment comprising the variant, and the variant allele frequency for the variant in the tumor sample, the variant can be classified as germline, somatic, subclonal or ambiguous.

Analysis of genetic variants

The present invention provides therapeutic and diagnostic methods and compositions for cancer, for example, bladder cancer. The invention provides methods of treating bladder cancer, methods of determining whether a patient suffering from bladder cancer is likely to respond to treatment comprising a PD-L1 axis binding antagonist, methods of predicting responsiveness of a patient suffering from bladder cancer to treatment comprising a PD-L1 axis binding antagonist, and methods of selecting a therapy for a patient suffering from bladder cancer, based on somatic mutation levels of genes of the invention (e.g., somatic mutation levels in a tumor sample obtained from the patient).

Therapeutic and diagnostic methods for cancer

Disclosed herein are compositions that include antigen-encoding nucleic acid sequences having multiple iterations of KRAS neoepitope-encoding sequences and/or lacking immunodominant epitopes. Also disclosed are nucleotides, cells, and methods associated with the compositions including their use as vaccines.

Multiepitope vaccine cassettes

Methods and compositions for treating cancer such as melanomas are disclosed.

Methods of treating cancer

The present invention provides therapeutic and diagnostic methods and compositions for cancer, for example, lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma. The invention provides methods of treating cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma), methods of determining whether a patient suffering from cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma) is likely to respond to treatment comprising a PD-L1 axis binding antagonist, methods of predicting responsiveness of a patient suffering from cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma) to treatment comprising a PD-L1 axis binding antagonist, and methods of selecting a therapy for a patient suffering from cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma), based on a tissue tumor mutational burden (tTMB) score, which reflects somatic mutation levels of genes in a tumor tissue sample obtained from the patient, alone or in combination with PD-L1 expression levels (e.g., PD-L1 expression levels in tumor or tumor-infiltrating immune cells in a tumor sample (tumor area) obtained from the patient).

Methods and systems for analyzing genetic variants are disclosed.

Growing community of inventors

Cambridge, MA, United States of America

James Xin Sun