Genetic Analysis of Lung Cancer and the Germline Impact on Somatic Mutation Burden

Abstract

Background Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking propensity and DNA repair genes, but further work is required to identify susceptibility variants. Methods To identify LC susceptibility loci, a family history-based genome-wide association (GWAx) study of LC (48,843 European “proxy” LC cases, 195,387 controls) was combined with previously LC GWAS (29,266 cases, 56,450 controls) by meta-analysis. Colocalisation was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic Risk Scores (PRS) were tested within an independent validation cohort (1,666 LC cases vs 6,664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumour resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided. Results The GWAx-GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1) and smoking propensity (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as sub-genome wide significant variants related to eQTLs and/or smoking propensity, assisted in LC genetic risk prediction (OR = 1.37, 95% CI 1.29–1.45, P = 1.44 x10-25). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumours. Conclusions This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

Common genetic variations in telomere length genes and lung cancer: a Mendelian randomisation study and its novel application in lung tumour transcriptome

“…Analyses of molecular phenotypes were performed using 343 lung adenocarcinoma samples of European ancestry from The Cancer Genome Atlas (TCGA) cohort with germline profile, RNA-sequencing, and epidemiological data available. Genotyping and imputation of germline variants have been described elsewhere ( Gabriel et al, 2022 ). The total somatic mutation burden of TCGA samples was obtained from Ellrott et al, 2018 , and DNA mutational signatures were extracted and attributed, as previously described ( Gabriel et al, 2022 ).…”

“…Genotyping and imputation of germline variants have been described elsewhere ( Gabriel et al, 2022 ). The total somatic mutation burden of TCGA samples was obtained from Ellrott et al, 2018 , and DNA mutational signatures were extracted and attributed, as previously described ( Gabriel et al, 2022 ). RNA-sequencing data were obtained from TCGA data portal using TCGA biolinks package in R (version 2.22.3; Colaprico et al, 2016 ).…”

Common genetic variations in telomere length genes and lung cancer

“…Analyses of molecular phenotypes were performed using 343 lung adenocarcinoma samples of European ancestry from The Cancer Genome Atlas (TGCA) cohort with both germline and RNA-sequencing data available. Genotyping and imputation of germline variants have been described elsewhere [21]. The total somatic mutation burden of TCGA samples were obtained from Ellrott et al, 2018 [22] and DNA mutational signatures were extracted and attributed, as previously described [21].…”

“…Genotyping and imputation of germline variants have been described elsewhere [21]. The total somatic mutation burden of TCGA samples were obtained from Ellrott et al, 2018 [22] and DNA mutational signatures were extracted and attributed, as previously described [21]. RNA-sequencing data were obtained from TCGA data portal using TCGAbiolinks package in R (version 2.22.3) [23].…”

“…Associations were estimated per standard deviation increase in the PRS, which was normalized to have a mean of zero across lung adenocarcinoma samples of European ancestry within the TCGA cohort. The associations between the eigenvalues of the gene expression principal components (outcome) and demographic, clinical, and genomic features related to genome stability (predictors derived from TCGA published papers and TCGA data portal, except for the DNA mutational signatures [21]), were calculated using a multivariate linear regression model.…”