Cristescu et al. evaluated the independent and combined application of two potential biomarkers of anti-PD-1 therapy response – tumor mutational burden (TMB) and T cell-inflamed gene expression profile (GEP) – using discovery and validation cohorts from HNSCC and pan-tumor trials. TMB, with a cutoff of ~80-200 mutations depending on tumor type, and GEP independently separated responders from non-responders. Both overall response rate and progression free survival were highest in TMBhi/GEPhi patients. The frequency of TMBhi/GEPhi varied across tumor types and reflected the observed checkpoint therapy responsiveness.
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.