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. Pretreatment tumor biopsies from 166 patients treated with anti-PD-1 across 10 academic cancer centers were fluorescently stained with multiple markers in discovery ( = 24) and validation ( = 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... More
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. Pretreatment tumor biopsies from 166 patients treated with anti-PD-1 across 10 academic cancer centers were fluorescently stained with multiple markers in discovery ( = 24) and validation ( = 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. 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 ( = 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 ( = 0.0096). These patients also experienced significantly improved progression-free survival (HR = 0.36; = 0.0004) and overall survival (HR = 0.39; = 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 ( = 0.000004). In contrast， PD-L1 expression was not predictive of survival. 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.
