Abstract 2222: Using rare variants to characterize lung cancer risk

Abstract

Abstract The human genome is exposed to a variety of exogenous and endogenous assaults capable of inducing DNA damage and contributing to diseases like cancer. Multiple DNA repair mechanisms are tasked with identifying and repairing these aberrant nucleotides, but damage is occasionally missed giving rise to somatic mutations. As we age, the relative abundance of somatic mutations increases, which may increase our risk for developing cancer. In addition, inter-individual variation in somatic mutation prevalence suggests an inter-individual variation in (a) inherited DNA repair capacity and/or (b) exposure to environmental mutagens. Therefore, somatic mutation prevalence may serve as an end-point biomarker for cancer risk, as it provides critical information regarding both. While Next Generation Sequencing (NGS) has provided unparalleled access to the human genome and revolutionized the field of cancer genomics, its implementation into the clinical setting has been limited by technical errors introduced during library preparation and on the sequencing platform. This makes identification of rare variants below 10-4 mutations per nucleotide through NGS a challenge, and the use of somatic mutations to characterize cancer risk unfeasible. To address this issue, unique molecular indexes (UMI) were assigned to each genomic copy, enabling reliable identification of rare somatic mutations versus technical errors. We hypothesize that measurement of somatic mutation prevalence in normal bronchial epithelial cells (NBEC) will serve as an end-point biomarker for lung cancer risk by identifying both (a) inherited sub-optimal DNA repair/protection and (b) exposure to inhaled environmental mutagens including components of cigarette smoke, radon, and/or occupational hazards. In our initial pilot study, we used genomic DNA derived from an A549 cell line to optimize an ERCC5 gene-specific, dual-indexed PCR method for UMI assignment, followed by sequencing on the Illumina MiSeq platform. In parallel analyses, UMI correction using 25,000 genomic copies provided over 10-fold greater sensitivity in identifying somatic mutations compared to no UMI correction. Based on this pilot, we obtained three clinical NBEC specimens via cytology brush biopsy of grossly normal (non-cancerous) airway from (a) heavy smoker with lung cancer, (b) heavy smoker without lung cancer, and (c) non-smoking control. UMIs were assigned to 50,000 genomic copies at 16 loci, increasing our theoretical limit of detection to approximately 1 in 4x107 nucleotides. Results thus far support further application of this approach in studies to assess NBEC somatic mutation prevalence as a biomarker for cancer risk. Citation Format: Daniel J. Craig, Mazzin Elsamaloty, Thomas M. Blomquist, Erin L. Crawford, James C. Willey. Using rare variants to characterize lung cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2222.