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

Author

Listed:
  • Lang Wu

    (University of Hawaii at Manoa)

  • Yaohua Yang

    (Vanderbilt University Medical Center)

  • Xingyi Guo

    (Vanderbilt University Medical Center)

  • Xiao-Ou Shu

    (Vanderbilt University Medical Center)

  • Qiuyin Cai

    (Vanderbilt University Medical Center)

  • Xiang Shu

    (Vanderbilt University Medical Center)

  • Bingshan Li

    (Vanderbilt University
    Vanderbilt University Medical Center)

  • Ran Tao

    (Vanderbilt University Medical Center
    Vanderbilt University Medical Center)

  • Chong Wu

    (Florida State University)

  • Jason B. Nikas

    (Genomix Inc)

  • Yanfa Sun

    (University of Hawaii at Manoa
    Longyan University)

  • Jingjing Zhu

    (University of Hawaii at Manoa)

  • Monique J. Roobol

    (Erasmus University Medical Center)

  • Graham G. Giles

    (University of Melbourne
    Cancer Council Victoria)

  • Hermann Brenner

    (German Cancer Research Center (DKFZ)
    German Cancer Research Center (DKFZ)
    German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT))

  • Esther M. John

    (Stanford University School of Medicine)

  • Judith Clements

    (Queensland University of Technology
    Translational Research Institute)

  • Eli Marie Grindedal

    (Oslo University Hospital)

  • Jong Y. Park

    (Moffitt Cancer Center)

  • Janet L. Stanford

    (Fred Hutchinson Cancer Research Center
    University of Washington)

  • Zsofia Kote-Jarai

    (The Institute of Cancer Research, and The Royal Marsden NHS Foundation Trust)

  • Christopher A. Haiman

    (University of Southern California)

  • Rosalind A. Eeles

    (The Institute of Cancer Research, and The Royal Marsden NHS Foundation Trust)

  • Wei Zheng

    (Vanderbilt University Medical Center)

  • Jirong Long

    (Vanderbilt University Medical Center)

Abstract

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.

Suggested Citation

  • 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, 2020. "An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17673-9
    DOI: 10.1038/s41467-020-17673-9
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    Cited by:

    1. Yaohua Yang & Yaxin Chen & Shuai Xu & Xingyi Guo & Guochong Jia & Jie Ping & Xiang Shu & Tianying Zhao & Fangcheng Yuan & Gang Wang & Yufang Xie & Hang Ci & Hongmo Liu & Yawen Qi & Yongjun Liu & Dan L, 2024. "Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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