Putative Biomarkers of Clinical Benefit With Pembrolizumab in Advanced Urothelial Cancer: Results from the KEYNOTE-045 and KEYNOTE-052 Landmark Trials.
Academic Article
Overview
abstract
PURPOSE: In an exploratory analysis, we investigated the association between programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), T-cell-inflamed gene expression profile (TcellinfGEP), and stromal signature with outcomes of pembrolizumab in urothelial carcinoma (UC). PATIENTS AND METHODS: Patients with advanced UC received first-line pembrolizumab 200 mg every 3 weeks in the single-arm phase II KEYNOTE-052 trial (NCT02335424) and salvage pembrolizumab 200 mg every 3 weeks or chemotherapy (paclitaxel/docetaxel/vinflunine) in the randomized phase III KEYNOTE-045 trial (NCT02256436). The association of each biomarker (continuous variable) with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) was evaluated using logistic regression (ORR) and Cox PH (PFS, OS), adjusted for ECOG PS; nominal P values were calculated without multiplicity adjustment (one-sided, pembrolizumab; two-sided, chemotherapy). Significance was prespecified at α = 0.05. RESULTS: In KEYNOTE-052, PD-L1, TMB, and TcellinfGEP were significantly associated with improved outcomes; stromal signature was significantly associated with worse outcomes. In KEYNOTE-045, although findings for TMB and TcellinfGEP with pembrolizumab were consistent with those of KEYNOTE-052, PD-L1 was not significantly associated with improved outcomes, nor was stromal signature associated with worse outcomes with pembrolizumab; chemotherapy was not associated with outcomes in a consistent manner for any of the biomarkers. Hazard ratio (HR) estimates at prespecified cutoffs showed an advantage for pembrolizumab versus chemotherapy regardless of PD-L1 or TMB, with a trend toward lower HRs in the combined positive score ≥10 and the TMB ≥175 mutation/exome subgroup. For TcellinfGEP, PFS and OS HRs were lower in the TcellinfGEP-nonlow subgroup regardless of treatment. CONCLUSIONS: Multiple biomarkers characterizing the tumor microenvironment may help predict response to pembrolizumab monotherapy in UC, and potential clinical utility of these biomarkers may be context-dependent.