학술논문
Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer.
Document Type
article
Author
Li, Donghui; Duell, Eric J; Yu, Kai; Risch, Harvey A; Olson, Sara H; Kooperberg, Charles; Wolpin, Brian M; Jiao, Li; Dong, Xiaoqun; Wheeler, Bill; Arslan, Alan A; Bueno-de-Mesquita, H Bas; Fuchs, Charles S; Gallinger, Steven; Gross, Myron; Hartge, Patricia; Hoover, Robert N; Holly, Elizabeth A; Jacobs, Eric J; Klein, Alison P; LaCroix, Andrea; Mandelson, Margaret T; Petersen, Gloria; Zheng, Wei; Agalliu, Ilir; Albanes, Demetrius; Boutron-Ruault, Marie-Christine; Bracci, Paige M; Buring, Julie E; Canzian, Federico; Chang, Kenneth; Chanock, Stephen J; Cotterchio, Michelle; Gaziano, J Michael; Giovannucci, Edward L; Goggins, Michael; Hallmans, Göran; Hankinson, Susan E; Hoffman Bolton, Judith A; Hunter, David J; Hutchinson, Amy; Jacobs, Kevin B; Jenab, Mazda; Khaw, Kay-Tee; Kraft, Peter; Krogh, Vittorio; Kurtz, Robert C; McWilliams, Robert R; Mendelsohn, Julie B; Patel, Alpa V; Rabe, Kari G; Riboli, Elio; Shu, Xiao-Ou; Tjønneland, Anne; Tobias, Geoffrey S; Trichopoulos, Dimitrios; Virtamo, Jarmo; Visvanathan, Kala; Watters, Joanne; Yu, Herbert; Zeleniuch-Jacquotte, Anne; Amundadottir, Laufey; Stolzenberg-Solomon, Rachael Z
Source
Carcinogenesis. 33(7)
Subject
Language
Abstract
Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case-control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10(-6), 1.6 × 10(-5), 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10(-5)), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.