An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

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作者
Lang Wu
Yaohua Yang
Xingyi Guo
Xiao-Ou Shu
Qiuyin Cai
Xiang Shu
Bingshan Li
Ran Tao
Chong Wu
Jason B. Nikas
Yanfa Sun
Jingjing Zhu
Monique J. Roobol
Graham G. Giles
Hermann Brenner
Esther M. John
Judith Clements
Eli Marie Grindedal
Jong Y. Park
Janet L. Stanford
Zsofia Kote-Jarai
Christopher A. Haiman
Rosalind A. Eeles
Wei Zheng
Jirong Long
机构
[1] University of Hawaii at Manoa,Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center
[2] Vanderbilt University Medical Center,Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt
[3] Vanderbilt University,Ingram Cancer Center
[4] Vanderbilt University Medical Center,Department of Molecular Physiology & Biophysics
[5] Vanderbilt University Medical Center,Vanderbilt Genetics Institute
[6] Florida State University,Department of Biostatistics
[7] Genomix Inc,Department of Statistics
[8] Longyan University,Research & Development
[9] Erasmus University Medical Center,College of Life Science
[10] University of Melbourne,Department of Urology
[11] Cancer Council Victoria,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health
[12] German Cancer Research Center (DKFZ),Cancer Epidemiology & Intelligence Division
[13] German Cancer Research Center (DKFZ),Division of Clinical Epidemiology and Aging Research
[14] German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT),German Cancer Consortium (DKTK)
[15] Stanford University School of Medicine,Division of Preventive Oncology
[16] Queensland University of Technology,Department of Medicine (Oncology) and Stanford Cancer Institute
[17] Translational Research Institute,Australian Prostate Cancer Research Centre
[18] Oslo University Hospital,QLD, Institute of Health and Biomedical Innovation and School of Biomedical Science
[19] Moffitt Cancer Center,Department of Medical Genetics
[20] Fred Hutchinson Cancer Research Center,Department of Cancer Epidemiology
[21] University of Washington,Division of Public Health Sciences
[22] The Institute of Cancer Research,Department of Epidemiology, School of Public Health
[23] and The Royal Marsden NHS Foundation Trust,Division of Genetics and Epidemiology
[24] University of Southern California,Department of Preventive Medicine
[25] Case Western Reserve University,Department of Population and Quantitative Health Sciences
[26] Seidman Cancer Center,Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
[27] University Hospitals,Division of Population Health, Health Services Research and Primary Care
[28] Strangeways Research Laboratory,Warwick Medical School
[29] University of Cambridge,Division of Cancer Epidemiology and Genetics
[30] Department of Clinical Neurosciences,Department of Medical Epidemiology and Biostatistics
[31] University of Manchester,Epidemiology Research Program
[32] University of Warwick,SWOG Statistical Center
[33] National Cancer Institute,Institute of Health and Biomedical Innovation and School of Biomedical Sciences
[34] NIH,Centre for Cancer Genetic Epidemiology, Department of Oncology
[35] Karolinska Institute,Tyks Microbiology and Genetics, Department of Medical Genetics
[36] American Cancer Society,Division of Nutritional Epidemiology, Institute of Environmental Medicine
[37] Fred Hutchinson Cancer Research Center,Department of Surgical Sciences
[38] Queensland University of Technology,Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, Manchester NIHR Biomedical Research Centre
[39] University College London,Department of Epidemiology
[40] Department of Applied Health Research,Department of Molecular Medicine
[41] University of Cambridge,Department of Clinical Medicine
[42] Strangeways Laboratory,University of Cambridge, Department of Oncology
[43] Institute of Biomedicine,Cancer Research UK Cambridge Research Institute
[44] Kiinamyllynkatu 10,Nuffield Department of Surgical Sciences, Faculty of Medical Science
[45] FI-20014 University of Turku,School of Social and Community Medicine
[46] Turku University Hospital,Department of Surgical Oncology
[47] Karolinska Institutet,Department of Radiation Oncology
[48] Uppsala University,Department of Genetics and Genomic Sciences
[49] The Christie Hospital NHS Foundation Trust,Centre for Molecular Oncology, Barts Cancer Institute
[50] Harvard School of Pubic Health,Division of Urologic Surgery
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摘要
It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.
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