Clinical Cancer Research · 2018 · 176 citations · 26 references
Life SciencesImmunologyOncologyImmunotherapyTumor ImmunologyTumor MicroenvironmentCancer BiomarkersCancer ImmunotherapyCheckpoint Inhibitor TherapyImmune Checkpoint InhibitorsImmuno-oncology BiomarkersTumor-associated AntigensBiomarkersImmune Biomarker ProfilingImmune Checkpoint Inhibitor BiomarkersPd-l1 BlockadeProgrammed Cell Death Protein 1 (Pd-1) PathwayTumor Immune Microenvironment ProfilingTumor Microenvironment BiomarkersTumor Microenvironment Mapping
Abstract Purpose: PD-1/L1 axis–directed therapies produce clinical responses in a subset of patients; therefore, biomarkers of response are needed. We hypothesized that quantifying key immunosuppression mechanisms within the tumor microenvironment by multiparameter algorithms would identify strong predictors of anti–PD-1 response. Experimental Design: Pretreatment tumor biopsies from 166 patients treated with anti–PD-1 across 10 academic cancer centers were fluorescently stained with multiple markers in discovery (n = 24) and validation (n = 142) cohorts. Biomarker-positive cells and their colocalization were spatially profiled in pathologist-selected tumor regions using novel Automated Quantitative Analysis algorithms. Selected biomarker signatures, PD-1/PD-L1 interaction score, and IDO-1/HLA-DR coexpression were evaluated for anti–PD-1 treatment outcomes. Results: In the discovery cohort, PD-1/PD-L1 interaction score and/or IDO-1/HLA-DR coexpression was strongly associated with anti–PD-1 response (P = 0.0005). In contrast, individual biomarkers (PD-1, PD-L1, IDO-1, HLA-DR) were not associated with response or survival. This finding was replicated in an independent validation cohort: patients with high PD-1/PD-L1 and/or IDO-1/HLA-DR were more likely to respond (P = 0.0096). These patients also experienced significantly improved progression-free survival (HR = 0.36; P = 0.0004) and overall survival (HR = 0.39; P = 0.0011). In the combined cohort, 80% of patients exhibiting higher levels of PD-1/PD-L1 interaction scores and IDO-1/HLA-DR responded to PD-1 blockers (P = 0.000004). In contrast, PD-L1 expression was not predictive of survival. Conclusions: Quantitative spatial profiling of key tumor-immune suppression pathways by novel digital pathology algorithms could help more reliably select melanoma patients for PD-1 monotherapy. Clin Cancer Res; 24(21); 5250–60. ©2018 AACR.
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