Bordeaux, Jennifer

9517 Background: Although PD-1/L1 axis directed therapies induce durable responses in some mm patients (pts), biomarkers of response remain elusive. We hypothesized that quantifying key immune suppression mechanisms within the tumor microenvironment would provide superior predictors of response to anti-PD-1 compared with single marker assessment. Methods: Pre-treatment tumor biopsies from 124 mm pts treated with anti-PD-1 at 7 academic centers were fluorescently stained with multiple immune markers in discovery (n = 24) and validation (n = 100) cohorts. Selected biomarker signatures, PD-1/PD-L1 interaction score (proportion of PD-1+ cells co-localized with PD-L1) and IDO1/HLA-DR co-expression were evaluated for anti-PD-1 treatment response and survival. Slides were imaged using Vectra; biomarker positive cells and their co-localization were objectively quantified in pathologist-selected regions using novel Automated Quantitative Analysis (AQUA) algorithms. Results: In the discovery cohort, high levels of PD-1/PD-L1 interaction score and/or IDO1/HLA-DR coexpression was strongly positively associated with response to anti-PD-1 (p = 0.0005). In contrast, other individual biomarkers (PD-1, PD-L1, CD8) were not associated with response or survival (p > 0.10). This finding was replicated in the validation cohort: pts with high PD-1/PD-L1 and/or IDO1/HLA-DR were more likely to respond to treatment (p = 0.009). These pts also experienced a three-fold increase in progression free survival (hazards ratio (HR) = 0.33; p = 0.003) and overall survival (HR = 0.34; p = 0.004). Multivariate analyses revealed that these findings were independent of BRAF mutation, stage, LDH and prior therapy. In the combined cohort (n = 124), 80% of responding pts had higher levels of PD-1/PD-L1 interaction scores and/or IDO1/HLA-DR. In contrast, PD-L1 expression alone (≥1% or ≥50%) was not predictive of PFS or OS (p > 0.1). Conclusions: This novel multiplexed method profiling key tumor-immune suppression pathways identified mm pts likely to respond to anti-PD-1 therapy. This method could help stratify patients for PD-1 monotherapy and be useful in guiding future clinical trials.

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.