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Even though genome-wide association studies (GWASs) have identified dozens of single nucleotide polymorphisms (SNPs) affecting the susceptibility to lung cancer, only a tiny fraction of heritability can be explained. Regulating the expression of surrounding genes is one of the important mechanisms for SNPs to exert their effect. So it is necessary to systematically evaluate the associations between expression quantitative trait loci (eQTL) and lung cancer risk. In this study, a two-stage case–control design was used to evaluate the associations of eQTL SNPs (eSNPs) defined by GTEx in normal lung tissues with the risk of lung cancer based on two GWAS datasets, including 7127 cases and 6818 controls. Promising variants were replicated in an independent population with 1026 lung cancer cases and 1006 controls. Functional annotations of the identified eSNPs and related genes were performed based on multiple public databases. Finally, we identified two potential eSNPs associated with the risk of lung cancer in 3q28 [rs505974, OR = 0.90 (0.86 – 0.94), P = 6.51 × 10−6] and 21q22.3 [rs79589812, OR = 1.38 (1.21 – 1.58), P = 2.46 × 10−6]. Subgroup analysis showed rs505974 might interact with smoking behaviour. Gene-set enrichment and pathway analysis revealed that rs505974 may affect the susceptibility to lung cancer via regulating the expression of CLDN16, which may be involved in the chemical carcinogenesis pathway, whereas rs79589812 may regulate the expression of SPATC1L, which may be involved in the base excision repair pathway. These results provide an overview of the associations between eSNPs and lung cancer in Asian populations. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-related deaths worldwide. By now, genome-wide association studies (GWAS) have identified numerous loci associated with the risk of developing lung cancer. However, these loci account for only a small fraction of the familial lung cancer risk. We hypothesized that epistasis may contribute to the missing heritability. To test this hypothesis, we systematically evaluated the association of epistasis of genetic variants with risk of lung cancer in Han Chinese cohorts. We conducted a pairwise genetic interaction analysis of 591370 variants, using BOolean Operation-based Screening and Testing (BOOST), in an ongoing GWAS of lung cancer that includes 2331 cases and 3077 controls. Pairs of epistatic loci with PBOOST ≤ 1.00×10−6 were further evaluated by a logistic regression model (LRM) with covariate adjustment. Four promising epistatic pairs identified at the screening stage (PLRM ≤ 2.86×10−13) were validated in two replication cohorts: the first from Beijing (1534 cases and 1489 controls) and the second from Shenyang and Guangzhou (2512 cases and 2449 controls). Using this combined analysis, we identified an interaction between rs2562796 and rs16832404 at 2p32.2 that was significantly associated with the risk of developing lung cancer (PLRM = 1.03×10−13 in total 13 392 subjects). This study is the first investigation of epistasis for lung cancer on a genome-wide scale in Han Chinese. It addresses part of the missing heritability in lung cancer risk and provides novel insight into the multifactorial etiology of lung cancer. [ABSTRACT FROM PUBLISHER]

Cell cycle regulation, apoptosis, oxidative stress and inflammation response play critical roles in the development of smoking-induced lung cancer. However, it is still not well known whether their genetic variants are associated with lung cancer susceptibility. In this study, we performed imputation-based association analyses to investigate the influence of common genetic variants in these pathways and their interactions with smoking on lung cancer susceptibility. We first selected 24 042 unvalidated genetic variants in 798 genes from the imputed dataset of the previous lung cancer genome-wide association study in 2331 cases and 3077 controls, and then conducted additional two-stage validations in 4133 cases and 4522 controls. We found a genome-wide significant (P < 5.0 × 10–8) association for rs2282987 in CDK6 at 7q21.2 [odds ratio (OR) = 1.18, combined Padd = 2.27 × 10–9] and a consistent association for rs2706748 in SH3RF1 at 4q32.3 (OR = 1.17, combined Padd = 5.10 × 10–6). Interaction analyses showed that rs2282987 and rs2706748 interacted with both smoking status (Pinteraction were 1.04 × 10–2 and 3.03 × 10–2, respectively) and smoking history (Pinteraction were 1.21 × 10–2 and 5.21 × 10–2, respectively) to contribute to lung cancer susceptibility in subjects aged 51–60 years. These results further underscore the contribution of genetic variants involved in pathways of cell cycle regulation and apoptosis to lung cancer susceptibility, and highlight gene–environment interactions in lung cancer etiology, especially in subjects aged 51–60 years. [ABSTRACT FROM AUTHOR]

Tobacco smoke is the major environmental risk factor underlying lung carcinogenesis. However, approximately one-tenth smokers develop lung cancer in their lifetime indicating there is significant individual variation in susceptibility to lung cancer. And, the reasons for this are largely unknown. In particular, the genetic variants discovered in genome-wide association studies (GWAS) account for only a small fraction of the phenotypic variations for lung cancer, and gene-environment interactions are thought to explain the missing fraction of disease heritability. The ability to identify smokers at high risk of developing cancer has substantial preventive implications. Thus, we undertook a gene-smoking interaction analysis in a GWAS of lung cancer in Han Chinese population using a two-phase designed case-control study. In the discovery phase, we evaluated all pair-wise (591,370) gene-smoking interactions in 5,408 subjects (2,331 cases and 3,077 controls) using a logistic regression model with covariate adjustment. In the replication phase, promising interactions were validated in an independent population of 3,023 subjects (1,534 cases and 1,489 controls). We identified interactions between two single nucleotide polymorphisms (SNPs) and smoking. The interaction p values are 6.73 × 10-6 and 3.84 × 10-6 for rs1316298 and rs4589502, respectively, in the combined dataset from the two phases. An antagonistic interaction (rs1316298-smoking) and a synergetic interaction (rs4589502-smoking) were observed. The two interactions identified in our study may help explain some of the missing heritability in lung cancer susceptibility and present strong evidence for further study of these gene-smoking interactions, which are benefit to intensive screening and smoking cessation interventions. [ABSTRACT FROM AUTHOR]