A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT–CLPTM1L gene region on chromosome 5p15.33. Because this region is characterized by low linkage disequilibrium, we sought to identify whether additional single nucleotide polymorphisms (SNPs) could be related to pancreatic cancer risk, independently of rs401681. We performed an in‐depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, odds ratio = 0.85; 95% confidence interval = 0.80–0.90, p = 8.3 × 10−8). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low linkage disequilibrium between them (r2 = 0.07, D′ = 0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (p = 3.0 × 10−5), rs4583925 (p = 4.0 × 10−5) and rs2735948 (p = 5.0 × 10−5). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants.
Abstract 2214: Genome-wide gene-diabetes and gene-obesity interaction scan in the pancreatic cancer case control consortium
Abstract Introduction Pancreatic cancer is a highly lethal malignancy due to late diagnosis and aggressiveness of the tumor. Characterization of high-risk populations for monitoring, intervention and early detection remains challenging. Obesity and diabetes are potentially modifiable contributors to pancreatic cancer. Genetic factors modifying the risk of obesity- and diabetes-induced pancreatic cancer have previously not been fully investigated at the genome-wide level. Hypothesis There are potential genetic factors modifying the associations between obesity/diabetes and pancreatic cancer. Methods Integrating genotype with risk factor data from a GWAS for the Pancreatic Cancer Case Control Consortium, we performed a genome-wide gene-environment interaction (G x E) scan for 457,688 SNPs in a discovery study of 2,028 cases and 2,109 controls using state-of-the-art methods including case-only (CO), case-control (CC), Empirical Hierarchical Bayes (EHB), Empirical-Bayes test (EB) and three 2-step approaches (DG2, EG2, DGEG2). Results We detected a genome-wide significant (P < 1.09 x 10-7 ) interaction of diabetes with rs13061928 (in CNTN4) in CO (P = 8.8 x 10-8 ), which was independent of diabetes in control group (P = 0.08). The minor allele was in a synergism with diabetes on the cancer risk: diabetics carrying GA/AA genotype had a 3.39-fold (95% CI: 2.47-4.65) increased disease risk compared with non-diabetics carrying GG genotype. Consistently, the SNP-diabetes interaction had a high ranking statistic in EHB (No.1) and high p-value ranks for EG2 and DGEG2 methods (No.1, P= 5.44 x 10-5). Conclusions These observations, once validated/confirmed, may help define at-risk subpopulation and initiate targeted intervention and prevention of pancreatic cancer. Genome-wide G x E analysis requires larger sample size than genetic main effects scan; combining the CO method with alternative methods may be the optimal scheme for genome-wide G x E analysis. Citation Format: Hongwei Tang, Eric J. Duell, Harvey A. Risch Risch, Sara H. Olson, H. Bas Bueno-de-Mesquita, Steven Gallinger, Elizabeth A. Holly, Gloria M. Petersen, Paige M. Bracci, Robert R. McWilliams, Mazda Jenab, Elio Riboli, Anne Tjønneland, Marie Christine Boutron-Ruault, Rudolf Kaaks, Dimitrios Trichopoulos, Salvatore Panico, Malin Sund, Petra H. M Peeters, Kay-Tee Khaw, Christopher I Amos, Donghui Li, Peng Wei. Genome-wide gene-diabetes and gene-obesity interaction scan in the pancreatic cancer case control consortium. [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 2214. doi:10.1158/1538-7445.AM2014-2214
Analysis of 60 Reported Glioma Risk SNPs Replicates Published GWAS Findings but Fails to Replicate Associations From Published Candidate‐Gene Studies
Genomewide association studies (GWAS) and candidate‐gene studies have implicated single‐nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case‐control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate‐gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate‐gene studies was associated in the full case‐control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate‐gene approach lay in selecting both appropriate genes and relevant SNPs within these genes.