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

Background: 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.

Methods: We evaluated PD-L1 (combined positive score [CPS]), TMB, T-cell-inflamed gene expression profile (Tcell GEP), and HPV status. Associations between biomarkers were evaluated by logistic regression (ORR) and Cox regression (PFS, OS).

Results: 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 Tcell GEP. TMB, PD-L1, and Tcell 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 Tcell GEP (Spearman ρ = -0.03 and ρ = -0.13, respectively); PD-L1 and Tcell GEP were moderately correlated (Spearman ρ = 0.47). In multivariate models, TMB, PD-L1, and Tcell 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 Tcell GEP had the highest ORRs. Within HPV subgroups, higher versus lower distributions of biomarkers (PD-L1, TMB, and Tcell 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.

Conclusions: TMB and the inflammatory biomarkers PD-L1 and Tcell GEP, assessed alone or together, may be useful for characterizing clinical response to pembrolizumab in R/M HNSCC.