Biomarkers that can predict response to anti–programmed cell death 1 (PD-1) therapy across multiple tumor types include a T-cell–inflamed gene-expression profile (GEP), programmed death ligand 1 (PD-L1) expression, and tumor mutational burden (TMB). Associations between these biomarkers and the clinical efficacy of pembrolizumab were evaluated in a clinical trial that encompassed 20 cohorts of patients with advanced solid tumors.

KEYNOTE-028 (ClinicalTrials.gov identifier: NCT02054806) is a nonrandomized, phase Ib trial that enrolled 475 patients with PD-L1–positive advanced solid tumors who were treated with pembrolizumab 10 mg/kg every 2 weeks for 2 years or until confirmed disease progression or unacceptable toxicity occurred. The primary end point was objective response rate (ORR; by RECIST v1.1, investigator review). Secondary end points included safety, progression-free survival (PFS), and overall survival (OS). Relationships between T-cell–inflamed GEP, PD-L1 expression, and TMB and antitumor activity were exploratory end points.

ORRs (with 95% CIs) ranged from 0% (0.0% to 14.2%) in pancreatic cancer to 33% (15.6% to 55.3%) in small-cell lung cancer. Across cohorts, median (95% CI) PFS ranged from 1.7 months (1.5 to 2.9 months) to 6.8 months (1.9 to 14.1 months) in pancreatic and thyroid cancers, respectively, and median OS from 3.9 months (2.8 to 5.5 months) to 21.1 months (9.1 to 22.4 months) in vulvar and carcinoid tumors, respectively. Higher response rates and longer PFS were demonstrated in tumors with higher T-cell–inflamed GEP, PD-L1 expression, and/or TMB. Correlations of TMB with GEP and PD-L1 were low. Response patterns indicate that patients with tumors that had high levels of both TMB and inflammatory markers (GEP or PD-L1) represent a population with the highest likelihood of response. Safety was similar and consistent with prior pembrolizumab reports.

A T-cell–-inflamed GEP, PD-L1 expression, and TMB predicted response to pembrolizumab in multiple tumor types. These biomarkers (alone/in combination) may help identify patients who have a higher likelihood of response to anti–PD-1 therapies across a broad spectrum of cancers.