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

Razvan Cristescu, Robin Mogg, Mark Ayers, Andrew Albright, Erin Murphy, Jennifer Yearley, Xinwei Sher, Xiao Qiao Liu, Hongchao Lu, Michael Nebozhyn, Chunsheng Zhang, Jared K. Lunceford, Andrew Joe, Jonathan Cheng, Andrea L. Webber, Nageatte Ibrahim, Elizabeth R. Plimack, Patrick A. Ott, Tanguy Y. Seiwert, Antoni RibasTerrill K. McClanahan, Joanne E. Tomassini, Andrey Loboda, David Kaufman

Research output: Contribution to journalArticlepeer-review

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 Tcell-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 Tcell 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.

Original languageEnglish (US)
Article numbereaar3593
JournalScience
Volume362
Issue number6411
DOIs
StatePublished - Oct 12 2018
Externally publishedYes

ASJC Scopus subject areas

  • General

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