Abstract Background: Lung cancer is the leading cause of cancer-related death in men and women, and cigarette smoking is the most significant preventable risk factor. Early detection through annual low dose CT screening reduces mortality but has low positive predictive value and specificity, in part due to low lung cancer incidence (<10%) among those who currently meet screening criteria. Thus, there is a need for biomarkers that reliably detect those at highest lung cancer risk, thereby enabling more effectivescreening. The purpose of this study was to test the hypothesis that high risk for lung cancer is characterized by high prevalence of low variant allele frequency (VAF) somatic mutations among known lung cancer driver genes in normal airway epithelial cells (AEC). Methods: Synthetic DNA internal standards (IS) were prepared for each of 11 lung cancer driver genes and mixed with each AEC genomic (g)DNA specimen prior to competitive multiplex PCR amplicon NGS library preparation. A custom Perl script was developed to separate IS reads and respective specimen gDNA reads from each target into separate files for parallel variant frequency analysis. This approach enabled reliable detection of mutations with VAF as low as 5 x 10-4 (0.05%). This method was then applied in a retrospective case-control study. Specifically, AEC specimens were collected by bronchoscopic brush biopsy from the normal airways of 19 subjects, including eleven lung cancer cases and eight non-cancer controls, and the association of lung cancer risk with AEC driver gene mutations was tested. Results: TP53 mutations with 0.05-1.0% VAF were more prevalent (p<0.005) and significantly more enriched for tobacco smoke and age-associated mutation signatures in AEC from lung cancer cases compared to non-cancer controls matched for smoking and age. Further, PIK3CA and BRAF mutations in this VAF range were identified in AEC from cases but not controls. Conclusions: Measurement of very low frequency mutations in the 0.05-1.0% VAF range enabled identification of an AEC somatic mutation field of injury associated with lung cancer risk. A biomarker comprising TP53, PIK3CA, and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes. Citation Format: Daniel J. Craig, Thomas Morrison, Sadik Khuder, Erin L. Crawford, Leihong Wu, Joshua Xu, Thomas M. Blomquist, James C. Willey. TP53, PIK3CA, and BRAF somatic mutations in airway epithelial field of injury associated with lung cancer risk [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4609.