Abstract 4154: Pathway-based approach to genome-wide gene-environment interaction analysis for occupational exposures in lung cancer susceptibility
Authors: Malhotra Jyoti , Sartori Samantha , Brennan Paul , Boffetta Paolo 
Published: May 2015

Background: Occupational exposures are known risk factors for lung cancer with asbestos, silica, polycyclic aromatic hydrocarbons and heavy metals being the major contributors. Few studies have addressed the role of genetically determined host factors in the pathogenesis of lung cancer associated with exposure to these agents. We used data from a genome-wide association (GWA) analysis to identify gene-occupation interactions and related pathways associated with increased lung cancer risk.

Methods: For our analysis, we used data from a previously published GWA analysis based on a case-control study conducted in six countries in Central and Eastern Europe from 1998 to 2002. Genotyping on samples from study participants was performed using Illumina Sentrix HumanHap300 BeadChip. Occupational exposure data was collected by trained interviewers and coders using semi-structured questionnaires. Single marker association analysis was performed using PLINK 1.07 for each exposure using logistic regression after adjusting for age, gender, smoking history, country/center and risk score calculated using history of exposure to other occupational exposures. Interaction term for genotypes and exposure was included in this model. Pathway analysis was performed using gene-set enrichment analyses approach. False discovery rate (FDR) was calculated to adjust for multiple comparisons. We analyzed 312,605 SNPs and occupational exposure to 70 agents from 1802 lung cancer cases and 1725 cancer-free controls.

Results: Mean age of study participants was 60.1 ± 9.1 years and 75% were male. We found SNPs showing gene-environment interaction p-values &lt; 1 x 10-5 for asbestos, diesel and kerosene, coal products, silica, oil mists and metals/alloys. Pathway analysis identified pathways related to response to environmental information processing via signal transduction as being most significant. More than 15 occupational exposures including asbestos, chromate, gasoline and diesel/kerosene showed significant gene-occupation interactions with signal transduction pathways (p&lt;0.001, FDR&lt;0.05), especially for MAPK, GPCR, TNFR and WNT signaling. Gasoline and diesel/kerosene gene-interaction analysis also showed enrichment in pathways related to immune processes (Toll-like receptor signaling pathway, FDR 0.05 and T cell activation, FDR 0.07). Diesel and petrol engine emissions showed significant gene interaction association with xenobiotic metabolism pathway, which regulates metabolism of carcinogens (FDR 0.008 and 0.04 respectively).

Conclusion: Our findings suggest that pathways involved in signal transduction, immune process and xenobiotic metabolism may be involved in lung cancer pathogenesis in interaction with occupational carcinogens. Further studies are needed to elucidate these molecular pathways.

Citation Format: Jyoti Malhotra, Samantha Sartori, Paul Brennan, Paolo Boffetta. Pathway-based approach to genome-wide gene-environment interaction analysis for occupational exposures in lung cancer susceptibility. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4154. doi:10.1158/1538-7445.AM2014-4154