Abstract 2214: The genomic landscape of lung cancer in post-menopausal never-smoker women

Lung cancer is the deadliest form of cancer worldwide. Cigarette smoking is the primary risk factor for developing lung cancer, fueling global tobacco cessation programs. In the United States, it is projected that by 2065 there will be a 63% reduction in smoking-associated lung cancer burden. However, even with this decline, lung cancer will still account for a significant proportion of cancer-associate mortality, suggesting that factors beyond smoking contribute to lung tumorigenesis. Lung cancer in never smokers is a distinct sub-group that needs specific exploration. It is the 7th highest cause of cancer-deaths worldwide, with an increasing trend in its incidence. Thus far, the majority of tumor genome-wide sequencing efforts in lung cancer have been focused on patient cohorts with a smoking history. We know that LCNS is distinct from lung adenocarcinoma found in smokers at the genetic level, however large gaps in our understanding of this population persist. Through a unique collaboration with the Women's Health Initiative (WHI) we now have access to a large repository of tumor tissue from LCNS patients. We have performed exome-sequencing on this cohort and here we describe novel mutations, structural variants and copy number changes in this cohort. Whole-exome sequencing of 75 tumor-normal pairs was performed. Mutations were identified for the entire cohort using different computational methods. For the identification of single nucleotide variants a consensus dual-caller and filtering methodology was employed. Variants were then analyzed to identify genes with significant mutations using MutSig2CV. Structural variant analysis was performed using SvABA and copy number analysis was performed using TITAN. Finally, we perform correlative analysis of mutations with the metadata curated by the WHI and highlight key features of this cohort. Our mutational analysis reveals showed that there is an enrichment of known oncogenes including KRAS, EGFR and TP53. Additionally, we identified mutations in STK11. Here we describe novel genes and mutations previously unknown to occur in LCNS cohort and describe their potential functional implications. We also report novel structural variants and copy number alterations. Additionally we performed mutational signature analysis and identified novel signatures specific to this cohort. Mutational analysis of our LCNS cohort reveals that this cohort in general has a lower tumor mutational burden compared to their control coho