Background: Lung cancer is known be associated with over 20 germline single nucleotide polymorphisms (SNPs). Tobacco exposure is a known risk factor for developing lung cancer. Genotype by environment interaction (GxE) studies provide a framework to assess whether genomic and environmental effects are additive or whether there is an additional interaction. We describe here a GxE study to investigate associations between tobacco exposure, genetic risk, and lung cancer risk. Methods: Patients were identified from Vanderbilt University Medical Center's (VUMC) de-identified DNA biobank (BioVU), which is linked to electronic medical record data. Approximately 15,000 individuals of European ancestry who had Illumina exome array data were selected for this analysis. Tobacco exposure was ascertained by a novel natural language processing algorithm. Lung cancer diagnoses were determined by International Classification of Disease 9 (ICD-9) codes. We attempt to replicate 25 SNPs associated with lung cancer previously reported in the NHGRI catalog using a logistic regression with age and gender as covariates. To test for interactions between smoking and known lung cancer association SNPs, we modeled the data using logistic regression with age, gender, pack years, SNP, and pack years x SNP terms. We also used a two degree of freedom (2df) joint test of the SNP and the interaction term, controlling for the main effects of the remaining covariates. Results: Lung cancer-associated ICD-9 codes were found in 803 individuals. Smoking was strongly associated with risk of developing lung cancer across all SNPs. We replicated 5 of the 25 previously reported SNPs associated with lung cancer (p < 0.05). Five SNPs (below) showed interaction with tobacco exposure (p < 0.05).Conclusions: This study explores the relationship between genetic and environmental risk for lung cancer. Five of the SNPs showed a non-additive interaction with smoking. Individuals with these mutations may be more sensitive to tobacco exposure than those without the SNP.