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

作者：Răzvan Cristescu, Robin Mogg, Mark Ayers, Andrew Albright, Erin Murphy, Jennifer H. Yearley, Xinwei Sher, Xiao Qiao Liu, Hongchao Lu, Michael Nebozhyn, Chunsheng Zhang, Jared Lunceford, Andrew K. Joe, Jonathan D. Cheng, Andrea L. Webber, Nageatte Ibrahim, Elizabeth R. Plimack, Patrick A. Ott, Tanguy Y. Seiwert, Antoni Ribas, Terrill K. McClanahan, Joanne E. Tomassini, Andrey Loboda, David R. Kaufman · 发表于：Science · 年份：2018 · DOI：10.1126/science.aar3593 · 被引用次数：2390 · 研究领域：Cancer Immunotherapy and Biomarkers、Cancer Genomics and Diagnostics、CAR-T cell therapy research

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.