Abstract
Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung cancer was explored using sequential kernel association test (SKAT) analysis. For single variant analysis, we combined the result of specific study using fixed-effect meta-analysis. We performed functional exploration of significant associations based on features from public databases. To further detect the biological mechanism underlying identified observations, pathway enrichment analysis were conducted with R package “clusterProfiler.” SNP-set analysis revealed the overall associations between variants of 8 cancer types and lung cancer risk. Single variant analysis identified 6 novel SNPs related to lung cancer risk after multiple correction (Pfdr < 0.10), including rs1707302 (1p34.1, OR = 0.93, 95% CI: 0.90–0.97, P = 7.60 × 10−4), rs2516448 (6p21.33, OR = 1.07, 95% CI: 1.03–1.11, P = 1.00 × 10−3), rs3869062 (6p22.1, OR = 0.91, 95% CI: 0.86–0.96, P = 7.10 × 10−4), rs174549 (11q12.2, OR = 0.90, 95% CI: 0.87–0.94, P = 1.00 × 10−7), rs7193541 (16q23.1, OR = 0.93, 95% CI: 0.90–0.96, P = 1.20 × 10−4), and rs8064454 (17q12, OR = 1.07, 95% CI: 1.03–1.11, P = 4.30 × 10−4). The eQTL analysis and functional annotation suggested that these variants might modify lung cancer susceptibility through regulating the expression of related genes. Pathway enrichment analysis showed that genes modulated by these variants play important roles in cancer carcinogenesis. Our findings demonstrate the pleiotropic associations between non-lung cancer susceptibility loci and lung cancer risk, providing important insights into the shared mechanisms of carcinogenesis across cancers.
Highlights
With rapidly increasing incidence and mortality rates, lung cancer has become the most frequently diagnosed cancer and the leading cause of cancer-related death in recent years
Data from four existing lung cancer Genome-wide association studies (GWASs) including 12,843 lung cancer cases and 12,639 controls was used in this study: (i) Nanjing Medical University (NJMU) GWAS including 2,331 lung cancer cases and 3,077 controls [11], (ii) Female Lung Cancer Consortium in Asia (FLCCA) GWAS with 4,796 lung cancer cases and 3,741 controls [12], (iii) Environment and Genetics in Lung Cancer Etiology (EAGLE) GWAS consists of 1,937 lung cancer cases and 1,984 controls and (iv) Division of Cancer Epidemiology and Genetics (DCEG) Lung Cancer GWAS encompasses 3,779 cases and 3,837 controls [13]
In the single nucleotide polymorphisms (SNPs)-set analysis, we found that the GWAS SNPs of 8 cancer types, including, cervical/endometrial, bladder/renal, prostate, pancreatic, ovarian, leukemia/lymphoma, esophageal, and colorectal cancer, were significantly associated with lung cancer risk in the combined dataset (FDR < 0.05) (Supplementary Table 2)
Summary
With rapidly increasing incidence and mortality rates, lung cancer has become the most frequently diagnosed cancer and the leading cause of cancer-related death in recent years. Based on GLOBOCAN 2012, there were 1.82 million new lung cancer cases (12.9% of the total cancer cases) and 1.59 million deaths (19.4% of the total cancer deaths) around the world [1]. To identify genetic variants that contribute to lung cancer development, several GWASs have been performed and dozens of SNPs were identified over the past few years [3]. These identified loci could explain only a small fraction of susceptibility. The challenge remains to detect additional risk loci with small effects, which may partially account for the missing heritability [4, 5]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
