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Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer.

About this Publication
Title
Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer.
Pubmed ID
30541042 (View this publication on the PubMed website)
Digital Object Identifier
Publication
J Natl Cancer Inst. 2019 Jun 1; Volume 111 (Issue 6): Pages 557-567
Authors
Walsh N, Zhang H, Hyland PL, Yang Q, Mocci E, Zhang M, Childs EJ, Collins I, Wang Z, Arslan AA, Beane-Freeman L, Bracci PM, Brennan P, Canzian F, Duell EJ, Gallinger S, Giles GG, Goggins M, Goodman GE, Goodman PJ, ...show more Hung RJ, Kooperberg C, Kurtz RC, Malats N, LeMarchand L, Neale RE, Olson SH, Scelo G, Shu XO, Van Den Eeden SK, Visvanathan K, White E, Zheng W, PanScan and PanC4 consortia, Albanes D, Andreotti G, Babic A, Bamlet WR, Berndt SI, Borgida A, Boutron-Ruault MC, Brais L, Brennan P, Bueno-de-Mesquita B, Buring J, Chaffee KG, Chanock S, Cleary S, Cotterchio M, Foretova L, Fuchs C, M Gaziano JM, Giovannucci E, Goggins M, Hackert T, Haiman C, Hartge P, Hasan M, Helzlsouer KJ, Herman J, Holcatova I, Holly EA, Hoover R, Hung RJ, Janout V, Klein EA, Kurtz RC, Laheru D, Lee IM, Lu L, Malats N, Mannisto S, Milne RL, Oberg AL, Orlow I, Patel AV, Peters U, Porta M, Real FX, Rothman N, Sesso HD, Severi G, Silverman D, Strobel O, Sund M, Thornquist MD, Tobias GS, Wactawski-Wende J, Wareham N, Weiderpass E, Wentzensen N, Wheeler W, Yu H, Zeleniuch-Jacquotte A, Kraft P, Li D, Jacobs EJ, Petersen GM, Wolpin BM, Risch HA, Amundadottir LT, Yu K, Klein AP, Stolzenberg-Solomon RZ
Affiliations
  • National Institute for Cellular Biotechnology, Dublin City University, Glasnevin, Dublin, Ireland.
  • Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
  • Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD.
  • Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
  • Department of Obstetrics and Gynecology, New York University School of Medicine, New York, NY.
  • Department of Epidemiology and Biostatistics, University of California, San Francisco, CA.
  • International Agency for Research on Cancer (IARC), Lyon, France.
  • Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute (IDIBELL), Catalan Institute of Oncology (ICO), Barcelona, Spain.
  • Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
...show more
  • Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD.
  • Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY.
  • Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO), Madrid, Spain.
  • Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI.
  • Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
  • Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
  • Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN.
  • Division of Research, Kaiser Permanente Northern California, Oakland, CA.
  • Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
  • Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA.
  • Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN.
  • Centre de Recherche en Épidémiologie et Santé des Populations (CESP, Inserm U1018), Facultés de Medicine, Université Paris-Saclay, UPS, UVSQ, Gustave Roussy, Villejuif, France.
  • Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
  • Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA.
  • Division of Hepatobiliary and Pancreas Surgery, Mayo Clinic, Rochester, MN.
  • Cancer Care Ontario, University of Toronto, Toronto, ON, Canada.
  • Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic.
  • Yale Cancer Center, New Haven, CT.
  • Division of Aging, Brigham and Women's Hospital, Boston, MA.
  • Department of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.
  • Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA.
  • Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX.
  • Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD.
  • Department of Radiation Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD.
  • Institute of Public Health and Preventive Medicine, Charles University, 2nd Faculty of Medicine, Prague, Czech Republic.
  • Department of Epidemiology and Public Health, Faculty of Medicine, University of Ostrava, Czech Republic.
  • Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH.
  • Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT.
  • Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland.
  • Epidemiology Research Program, American Cancer Society, Atlanta, GA.
  • CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
  • CIBERONC, Madrid, Spain.
  • Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden.
  • Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY.
  • MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
  • Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway.
  • Information Management Systems, Silver Spring, MD.
  • Perlmutter Cancer Center, New York University School of Medicine, New York, NY.
  • Department of Population Health, New York University School of Medicine, New York, NY.
  • Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
  • Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX.
Abstract

BACKGROUND: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes.

METHODS: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.

RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.

CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.

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