| Literature DB >> 28150878 |
Jieyun Yin1,2,3, Hongliang Liu2,3, Zhensheng Liu2,3, Kouros Owzar2,4, Younghun Han5, Li Su6,7, Yongyue Wei6,7, Rayjean J Hung8, Yonathan Brhane8, John McLaughlin9, Paul Brennan10, Heike Bickeboeller11, Albert Rosenberger11, Richard S Houlston12, Neil Caporaso13, Maria Teresa Landi13, Joachim Heinrich14,15, Angela Risch16,17,18, David C Christiani6,7, Christopher I Amos5, Qingyi Wei2,3.
Abstract
The fatty acids (FAs) metabolism is suggested to play a pivotal role in the development of lung cancer, and we explored that by conducting a pathway-based analysis. We performed a meta-analysis of published datasets of six genome wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium, which included 12 160 cases with lung cancer and 16 838 cancer-free controls. A total of 30 722 single-nucleotide polymorphisms (SNPs) from 317 genes relevant to FA metabolic pathways were identified. An additional dataset from the Harvard Lung Cancer Study with 984 cases and 970 healthy controls was also added to the final meta-analysis. In the initial meta-analysis, 26 of 28 SNPs that passed false discovery rate multiple tests were mapped to the CYP4F3 gene. Among the 26 top ranked hits was a proxy SNP, CYP4F3 rs4646904 (P = 8.65 × 10-6 , FDR = 0.018), which is suggested to change splicing pattern/efficiency and to be associated with gene expression levels. However, after adding data of rs4646904 from the Harvard GWAS, the significance in the combined analysis was reduced to P = 3.52 × 10-3 [odds ratio (OR) = 1.07, 95% confidence interval (95%CI) = 1.03-1.12]. Interestingly, the small Harvard dataset also pointed to the same direction of the association in subgroups of smokers (OR = 1.07) and contributed to a combined OR of 1.13 (95% CI = 1.06-1.20, P = 6.70 × 10-5 ). The results suggest that a potentially functional SNP in CYP4F3 (rs4646904) may contribute to the etiology of lung cancer, especially in smokers. Additional mechanistic studies are warranted to unravel the potential biological significance of the finding.Entities:
Keywords: fatty acid metabolism; genome wide association study; lung cancer; tumor markers
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Year: 2017 PMID: 28150878 PMCID: PMC5423820 DOI: 10.1002/mc.22622
Source DB: PubMed Journal: Mol Carcinog ISSN: 0899-1987 Impact factor: 4.784