Clinical and Molecular Correlates of Tumor Mutation Burden in Non-Small Cell Lung Cancer. (August 2020) - Sharpnack, Michael F.; Cho, Ju Hwan; Johnson, Travis S.; Otterson, Gregory A.; Shields, Peter G.; Huang, Kun; Carbone, David P.; He, Kai
Highlights: Smoking history is not a surrogate biomarker for tumor mutation burden We create a predictive model of tumor mutation burden We discover genome stability genes associated with high tumor mutation burden, including REV3L . ABSTRACT: Introduction: Recent clinical studies have identified tumor mutation burden (TMB) as a promising therapeutic biomarker of anti-tumor immune checkpoint blockade. However, given the relatively slow turnaround time and high expense in measuring TMB, tobacco smoking history (TSH) is an attractive replacement biomarker. The carcinogenic effects of tobacco smoking may be modified by the protective effects of genome stability genes. This study aims to test the associations between tobacco smoking, genome stability gene inactivation, and TMB. Methods: Publicly available TSH and DNA somatic alteration data from NSCLC were downloaded from The Cancer Genome Atlas. Correlations and enrichments were calculated with Spearman and Fisher's exact test methods, respectively. Multivariate modeling of TMB was performed with penalized linear regression. Results: 85% of never smokers in adenocarcinomas (LUAD) had low TMB, but a positive TSH was not predictive of hypermutancy. The limited utility of TSH in predicting TMB was reproduced on an independent LUAD dataset. To expand our search for predictors of TMB, we further investigated the contributions of genome stability related genes (GSGs) to TMB. 242/461 (52%) and 300/465 (65%) patients with LUAD and squamous carcinomas (LUSC), respectively, showed evidence of loss of function in at least one of the 182 GSGs. 182 GSGs from 16 pathways were assessed for associations with TMB high tumor status using Fisher's exact test. We performed univariate gene and pathway enrichments in TMB high tumors and found roles for POLE, REV3L, and FANCE genes, as well as several key GSG pathways. Conclusions: This study comprehensively tested the association between GSG, tobacco smoking, and TMB in NSCLC. In LUAD, never-smoking status was predictive of low TMB, but overall TSH was not an adequate surrogate biomarker for TMB in NSCLC. Furthermore, we identified an association between GSG inactivation and TMB.