Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy

Răzvan Cristescu(Merck & Co., Inc., Rahway, NJ, USA (United States)), Robin Mogg(Merck & Co., Inc., Rahway, NJ, USA (United States)), Mark Ayers(Merck & Co., Inc., Rahway, NJ, USA (United States)), Andrew Albright(Merck & Co., Inc., Rahway, NJ, USA (United States)), Erin Murphy(Merck & Co., Inc., Rahway, NJ, USA (United States)), Jennifer H. Yearley(Merck & Co., Inc., Rahway, NJ, USA (United States)), Xinwei Sher(Merck & Co., Inc., Rahway, NJ, USA (United States)), Xiao Qiao Liu(Merck & Co., Inc., Rahway, NJ, USA (United States)), Hongchao Lu(Merck & Co., Inc., Rahway, NJ, USA (United States)), Michael Nebozhyn(Merck & Co., Inc., Rahway, NJ, USA (United States)), Chunsheng Zhang(Merck & Co., Inc., Rahway, NJ, USA (United States)), Jared Lunceford(Merck & Co., Inc., Rahway, NJ, USA (United States)), Andrew K. Joe(Merck & Co., Inc., Rahway, NJ, USA (United States)), Jonathan D. Cheng(Merck & Co., Inc., Rahway, NJ, USA (United States)), Andrea L. Webber(Merck & Co., Inc., Rahway, NJ, USA (United States)), Nageatte Ibrahim(Merck & Co., Inc., Rahway, NJ, USA (United States)), Elizabeth R. Plimack(Fox Chase Cancer Center), Patrick A. Ott(Dana-Farber Cancer Institute), Tanguy Y. Seiwert(University of Chicago), Antoni Ribas(University of California, Los Angeles), Terrill K. McClanahan(Merck & Co., Inc., Rahway, NJ, USA (United States)), Joanne E. Tomassini(Merck & Co., Inc., Rahway, NJ, USA (United States)), Andrey Loboda(Merck & Co., Inc., Rahway, NJ, USA (United States)), David R. Kaufman(Merck & Co., Inc., Rahway, NJ, USA (United States))
Science
October 11, 2018
10.1126/science.aar3593
Cited by 2,314

Abstract

Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.

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