Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
More mutations predict better efficacy
Despite the remarkable success of cancer immunotherapies, many patients do not respond to treatment. Rizvi et al. studied the tumors of patients with non–small-cell lung cancer undergoing immunotherapy. In two independent cohorts, treatment efficacy was associated with a higher number of mutations in the tumors. In one patient, a tumor-specific T cell response paralleled tumor regression.
Science, this issue p. 124
Abstract
Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. To unravel the genomic determinants of response to this therapy, we used whole-exome sequencing of non–small cell lung cancers treated with pembrolizumab, an antibody targeting programmed cell death-1 (PD-1). In two independent cohorts, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. Efficacy also correlated with the molecular smoking signature, higher neoantigen burden, and DNA repair pathway mutations; each factor was also associated with mutation burden. In one responder, neoantigen-specific CD8+ T cell responses paralleled tumor regression, suggesting that anti–PD-1 therapy enhances neoantigen-specific T cell reactivity. Our results suggest that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.
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Supplementary Material
Summary
Materials and Methods
Figs. S1 to S12
Tables S1 to S6
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References and Notes
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Volume 348 | Issue 6230
3 April 2015
3 April 2015
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Received: 21 October 2014
Accepted: 27 February 2015
Published in print: 3 April 2015
Acknowledgments
We thank the members of the Thoracic Oncology Service and the Chan and Wolchok laboratories at Memorial Sloan Kettering Cancer Center (MSKCC) for helpful discussions. We thank the Immune Monitoring Core at MSKCC, including L. Caro, R. Ramsawak, and Z. Mu, for exceptional support with processing and banking peripheral blood lymphocytes. We thank P. Worrell and E. Brzostowski for help in identifying tumor specimens for analysis. We thank A. Viale for superb technical assistance. We thank D. Philips, M. van Buuren, and M. Toebes for help performing the combinatorial coding screens. The data presented in this paper are tabulated in the main paper and in the supplementary materials. Data are publicly available at the Cancer Genome Atlas (TCGA) cBio portal and database (www.cbioportal.org; study ID: Rizvi lung cancer). All genotype and phenotype data are deposited at dpGAP under accession no. phs000980.v1.p1. T.A.C. is the inventor on a patent (provisional application number 62/083,088). The application is directed toward methods for identifying patients who will benefit from treatment with immunotherapy. This work was supported by the Geoffrey Beene Cancer Research Center (M.D.H., N.A.R., T.A.C., J.D.W., and A.S.), the Society for Memorial Sloan Kettering Cancer Center (M.D.H.), Lung Cancer Research Foundation (W.L.), Frederick Adler Chair Fund (T.A.C.), The One Ball Matt Memorial Golf Tournament (E.B.G.), Queen Wilhelmina Cancer Research Award (T.N.S.), The STARR Foundation (T.A.C. and J.D.W.), the Ludwig Trust (J.D.W.), and a Stand Up To Cancer-Cancer Research Institute Cancer Immunology Translational Cancer Research Grant (J.D.W., T.N.S., and T.A.C.). Stand Up To Cancer is a program of the Entertainment Industry Foundation administered by the American Association for Cancer Research.
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