Comprehensive Genomic Profiling Identifies Novel Genetic Predictors of Response to Anti–PD-(L)1 Therapies in Non–Small Cell Lung Cancer

Abstract Purpose: Immune checkpoint inhibitors (ICI) have revolutionized cancer management. However, molecular determinants of response to ICIs remain incompletely understood. Experimental Design: We performed genomic profiling of 78 patients with non–small cell lung cancer (NSCLC) who underwent anti–PD-(L)1 therapies by both whole-exome and targeted next-generation sequencing (a 422-cancer-gene panel) to explore the predictive biomarkers of ICI response. Tumor mutation burden (TMB), and specific somatic mutations and copy-number alterations (CNA) were evaluated for their associations with immunotherapy response. Results: We confirmed that high TMB was associated with improved clinical outcomes, and TMB quantified by gene panel strongly correlated with WES results (Spearman's ρ = 0.81). Compared with wild-type, patients with FAT1 mutations had higher durable clinical benefit (DCB, 71.4% vs. 22.7%, P = 0.01) and objective response rates (ORR, 57.1% vs. 15.2%, P = 0.02). On the other hand, patients with activating mutations in EGFR/ERBB2 had reduced median progression-free survival (mPFS) compared with others 51.0 vs. 70.5 days, P = 0.0037, HR, 2.47; 95% confidence interval (CI), 1.32–4.62. In addition, copy-number loss in specific chromosome 3p segments containing the tumor-suppressor ITGA9 and several chemokine receptor pathway genes, were highly predictive of poor clinical outcome (survival rates at 6 months, 0% vs. 31%, P = 0.012, HR, 2.08; 95% CI, 1.09–4.00). Our findings were further validated in two independently published datasets comprising multiple cancer types. Conclusions: We identified novel genomic biomarkers that were predictive of response to anti–PD-(L)1 therapies. Our findings suggest that comprehensive profiling of TMB and the aforementioned molecular markers could result in greater predictive power of response to ICI therapies in NSCLC.