| Literature DB >> 30309915 |
Razvan Cristescu1, Robin Mogg2, Mark Ayers2, Andrew Albright2, Erin Murphy2, Jennifer Yearley2, Xinwei Sher2, Xiao Qiao Liu2, Hongchao Lu2, Michael Nebozhyn2, Chunsheng Zhang2, Jared K Lunceford2, Andrew Joe2, Jonathan Cheng2, Andrea L Webber2, Nageatte Ibrahim2, Elizabeth R Plimack3, Patrick A Ott4, Tanguy Y Seiwert5, Antoni Ribas6, Terrill K McClanahan2, Joanne E Tomassini2, Andrey Loboda2, David Kaufman2.
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.Entities:
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Year: 2018 PMID: 30309915 PMCID: PMC6718162 DOI: 10.1126/science.aar3593
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728