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Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy
- Cristescu, Razvan;
- Mogg, Robin;
- Ayers, Mark;
- Albright, Andrew;
- Murphy, Erin;
- Yearley, Jennifer;
- Sher, Xinwei;
- Liu, Xiao Qiao;
- Lu, Hongchao;
- Nebozhyn, Michael;
- Zhang, Chunsheng;
- Lunceford, Jared K;
- Joe, Andrew;
- Cheng, Jonathan;
- Webber, Andrea L;
- Ibrahim, Nageatte;
- Plimack, Elizabeth R;
- Ott, Patrick A;
- Seiwert, Tanguy Y;
- Ribas, Antoni;
- McClanahan, Terrill K;
- Tomassini, Joanne E;
- Loboda, Andrey;
- Kaufman, David
Published Web Location
https://doi.org/10.1126/science.aar3593Abstract
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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