A Gene Mutation Signature Predicting Immunotherapy Benefits in Patients With NSCLC.

Journal Article (Journal Article)

INTRODUCTION: Identification of patients who can benefit from immune checkpoint blockade (ICB) therapy is key for improved clinical outcome. Recently, U.S. Food and Drug Administration approved tumor mutational burden (TMB) high (TMB-H or TMB ≥ 10) as a biomarker for pembrolizumab treatment of solid tumors. We intend to test the hypothesis that mutations in select genes may be a better predictor of NSCLC response to ICB therapy than TMB-H. METHODS: We compiled a list of candidate genes that may predict for benefits from ICB treatment by use of data from a recently published cohort of 350 patients with NSCLC. We then evaluated the influences of different mutation signatures in the candidate genes on ICB efficacy. They were also compared with TMB-H. The predictive powers of different mutation signatures were then evaluated in an independent cohort of patients with NSCLC treated with ICB. RESULTS: A compound mutation signature, in which two or more of the 52 candidate genes were mutated, accounted for 145 of 350 patients with NSCLC and was associated with considerable ICB treatment benefits. Specifically, the median duration of overall survival was 36 versus 8 months in NSCLC in those with two or more versus none of the 52 genes mutated. Moreover, those patients with the compound mutation signature but had low TMB (<10) achieved significant overall survival benefits when compared with those without the signature but had TMB-H (≥10). Finally, in an independent cohort of 156 patients with ICB-treated NSCLC, the median duration of progression-free survival was 8.3 months versus 3.5 months in those with the compound mutation signature versus those with none mutated in the 52 genes. CONCLUSIONS: A genetic signature with mutations in at least two of 52 candidate genes was superior than TMB-H in predicting clinical benefits for ICB therapy in patients with NSCLC.

Full Text

Duke Authors

Cited Authors

  • Pan, D; Hu, AY; Antonia, SJ; Li, C-Y

Published Date

  • March 2021

Published In

Volume / Issue

  • 16 / 3

Start / End Page

  • 419 - 427

PubMed ID

  • 33307194

Pubmed Central ID

  • PMC7920921

Electronic International Standard Serial Number (EISSN)

  • 1556-1380

Digital Object Identifier (DOI)

  • 10.1016/j.jtho.2020.11.021

Language

  • eng

Conference Location

  • United States