Biomarkers predictive of response to pembrolizumab in head and neck cancer.

Abstract

We performed an integrated biomarker evaluation in pembrolizumab-treated patients with R/M HNSCC enrolled in KEYNOTE-012 or KEYNOTE-055. The relationship between biomarkers and HPV status was explored. We evaluated PD-L1 (combined positive score [CPS]), TMB, T-cell-inflamed gene expression profile (Tcellinf GEP), and HPV status. Associations between biomarkers were evaluated by logistic regression (ORR) and Cox regression (PFS, OS). Two hundred and fifty-seven patients (KEYNOTE-012, n=106; KEYNOTE-055, n=151) had TMB data available; of these, 254 had PD-L1 and 236 had Tcellinf GEP. TMB, PD-L1, and Tcellinf GEP were each significantly associated with ORR (p < 0.01). Kaplan-Meier curves at prespecified cutoffs generally showed PFS and OS separation in the anticipated direction for these biomarkers, except for OS and TMB. TMB did not correlate with PD-L1 or Tcellinf GEP (Spearman ρ=-0.03 and ρ=-0.13, respectively); PD-L1 and Tcellinf GEP were moderately correlated (Spearman ρ=0.47). In multivariate models, TMB, PD-L1, and Tcellinf GEP were each independently predictive for ORR (p < 0.001). ORR was higher in patients with high versus low levels of biomarkers when dichotomized using prespecified cutoffs; patients with higher versus lower levels of TMB and PD-L1 or TMB and Tcellinf GEP had the highest ORRs. Within HPV subgroups, higher versus lower distributions of biomarkers (PD-L1, TMB, and Tcellinf GEP) were associated with response. HPV detection by p16-immunohistochemistry and WES showed good concordance (81%); results were generally similar by HPV status, regardless of the detection method. TMB and the inflammatory biomarkers PD-L1 and Tcellinf GEP, assessed alone or together, may be useful for characterizing clinical response to pembrolizumab in R/M HNSCC.