Exome analysis reveals genomic markers associated with better efficacy of nivolumab in lung cancer patients.
Corentin Richard, Jean-David Fumet, Sandy Chevrier, Valentin Derangère, Fanny Ledys, Aurélie Lagrange, Laure Favier, Bruno Coudert, Laurent Arnould, Caroline Truntzer, Romain Boidot and Francois Ghiringhelli.
Abstract
Purpose: Immune checkpoint inhibitors revolutionized the treatment of non-small cell lung cancer (NSCLC). However, only one-quarter of patients benefit from these new therapies. PD-L1 assessment and tumor mutational burden (TMB) are available tools to optimize use of checkpoint inhibitors but novel tools are needed. Exome sequencing could generate many variables but their role in identifying predictors of response is unknown.
Experimental Design: We performed somatic and constitutional exome analyses for 77 patients with NSCLC treated with nivolumab. We studied: 1-tumor-related characteristics: aneuploidy, CNA clonality, mutational signatures, TMB, mutations in WNT, AKT, MAPK and DNA repair pathways, and 2-immunological characteristics: number of intratumoral TCR clones, HLA types and number of neoantigens; and 6 clinical parameters.
Results: A high TMB per Mb, a high number of neoantigens, mutational signatures 1A and 1B, mutations in DNA repair pathways and a low number of TCR clones are associated with greater PFS. Using a LASSO method, we established an exome-based model with 9 exome parameters that could discriminate patients with good or poor PFS (p<0.0001) and overall survival (p=0.002). This model shows better ability to predict outcomes compared with a PD-L1 clinical model with or without TMB. It was externally validated on two cohorts of NSCLC patients treated with pembrolizumab or with nivolumab and ipilimumab as well as in urothelial tumors treated with atezolizumab.
Conclusions: Altogether, these data provide a validated biomarker that predicts the efficacy of nivolumab or pembrolizumab in NSCLC patients. Our biomarker appears to be superior to PD-L1 labelling and TMB models.