Pathway Analysis Of Oncoarray Data Identifies Biological Pathways Involved In Lung Cancer Development

Background:Genome-wide association studies (GWAS) have identified susceptible loci associated with lung cancer development. However, these variants only account for a small proportion of lung cancer heritability. With the aim to identify the missing heritability, we propose to conduct pathway analysis to test the joint effects of rare and common variants using the OncoArray data. By grouping SNPs into genes and pathways, we may shed light into the underlying mechanisms for lung cancer development and identify novel candidate genes and pathways.Methods:We applied sequence kernel association test (SKAT) to the OncoArray data of the Transdisciplinary Research of Cancer in lung of the International Lung Cancer Consortium (TRICL-ILCCO) that includes 34,432 individuals (19,028 cases and 15,404 controls) across over twenty lung cancer studies. A total of 403 KEGG and Biocarta pathways containing 5,555 genes and 58,717 SNPs were included in the study. As a score-based variance-component test, SKAT calculated p values for each pathway set by fitting the null model containing only age, gender, smoking, and first three PCAs. Results:KEGG neuroactive ligand receptor interaction (p=1.18×10-4, FDR=0.0285) and KEGG pancreatic cancer pathways (p=1.41×10-4, FDR=0.0285) were significantly associated with lung cancer. Gene-based analyses found that the most significant genes on the KEGG neuroactive ligand receptor interaction pathway to be CHRNA5 (p=2.33×10-8, FDR=0.0003), CHRNA3 (p=2.85×10-7, FDR=0.0019), and CHRNB4 (p=7.49×10-7, FDR=0.0034), while the most significant genes for KEGG pancreatic cancer pathway to be BRCA2 (p=2.23×10-5, FDR=0.0505). Stratified analyses highlighted five pathways (KEGG intestinal immune network for IGA production, KEGG leishmania infection, KEGG bladder cancer, KEGG pancreatic cancer, and KEGG axon guidance) for squamous cell carcinoma and one pathway (Biocarta ACH pathway) for adenocarcinoma with FWER Citation Format: Zhihui Wang, Ruyang Zhang, Li Su, Rayjean Hung, Christopher Amos, David C. Christiani. Pathway analysis of OncoArray data identifies biological pathways involved in lung cancer development [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 244.