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Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects

Author

Listed:
  • Shuji Ito

    (The Laboratory for Statistical and Translational Genetics
    The Laboratory for Bone and Joint Diseases
    Shimane University)

  • Xiaoxi Liu

    (The Laboratory for Statistical and Translational Genetics)

  • Yuki Ishikawa

    (The Laboratory for Statistical and Translational Genetics)

  • David D. Conti

    (University of Southern California)

  • Nao Otomo

    (The Laboratory for Statistical and Translational Genetics
    Keio University)

  • Zsofia Kote-Jarai

    (The Institute of Cancer Research)

  • Hiroyuki Suetsugu

    (The Laboratory for Statistical and Translational Genetics
    Kyushu University)

  • Rosalind A. Eeles

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

  • Yoshinao Koike

    (The Laboratory for Statistical and Translational Genetics
    Hokkaido University Graduate School of Medicine)

  • Keiko Hikino

    (The Laboratory for Pharmacogenomics)

  • Soichiro Yoshino

    (The Laboratory for Statistical and Translational Genetics
    Kyushu University)

  • Kohei Tomizuka

    (The Laboratory for Statistical and Translational Genetics)

  • Momoko Horikoshi

    (The Laboratory for Genomics of Diabetes and Metabolism)

  • Kaoru Ito

    (The Cardiovascular Genomics and Informatics)

  • Yuji Uchio

    (Shimane University)

  • Yukihide Momozawa

    (The Laboratory for Genotyping Development)

  • Michiaki Kubo

    (Haradoi Hospital)

  • Yoichiro Kamatani

    (The University of Tokyo)

  • Koichi Matsuda

    (Human Genome Center
    Department of Computational Biology and Medical Sciences)

  • Christopher A. Haiman

    (University of Southern California)

  • Shiro Ikegawa

    (The Laboratory for Bone and Joint Diseases)

  • Hidewaki Nakagawa

    (Laboratory for Cancer Genomics)

  • Chikashi Terao

    (The Laboratory for Statistical and Translational Genetics
    The Clinical Research Center
    The Department of Applied Genetics)

Abstract

Prostate cancer (PrCa) is the second most common cancer worldwide in males. While strongly warranted, the prediction of mortality risk due to PrCa, especially before its development, is challenging. Here, we address this issue by maximizing the statistical power of genetic data with multi-ancestry meta-analysis and focusing on binding sites of the androgen receptor (AR), which has a critical role in PrCa. Taking advantage of large Japanese samples ever, a multi-ancestry meta-analysis comprising more than 300,000 subjects in total identifies 9 unreported loci including ZFHX3, a tumor suppressor gene, and successfully narrows down the statistically finemapped variants compared to European-only studies, and these variants strongly enrich in AR binding sites. A polygenic risk scores (PRS) analysis restricting to statistically finemapped variants in AR binding sites shows among cancer-free subjects, individuals with a PRS in the top 10% have a strongly higher risk of the future death of PrCa (HR: 5.57, P = 4.2 × 10−10). Our findings demonstrate the potential utility of leveraging large-scale genetic data and advanced analytical methods in predicting the mortality of PrCa.

Suggested Citation

  • Shuji Ito & Xiaoxi Liu & Yuki Ishikawa & David D. Conti & Nao Otomo & Zsofia Kote-Jarai & Hiroyuki Suetsugu & Rosalind A. Eeles & Yoshinao Koike & Keiko Hikino & Soichiro Yoshino & Kohei Tomizuka & Mo, 2023. "Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39858-8
    DOI: 10.1038/s41467-023-39858-8
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    References listed on IDEAS

    as
    1. Tunç Morova & Daniel R. McNeill & Nada Lallous & Mehmet Gönen & Kush Dalal & David M. Wilson & Attila Gürsoy & Özlem Keskin & Nathan A. Lack, 2020. "Androgen receptor-binding sites are highly mutated in prostate cancer," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    2. Ryo Takata & Atsushi Takahashi & Masashi Fujita & Yukihide Momozawa & Edward J. Saunders & Hiroki Yamada & Kazuhiro Maejima & Kaoru Nakano & Yuichiro Nishida & Asahi Hishida & Keitaro Matsuo & Kenji W, 2019. "12 new susceptibility loci for prostate cancer identified by genome-wide association study in Japanese population," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    3. Meilin Wang & Atsushi Takahashi & Fang Liu & Dingwei Ye & Qiang Ding & Chao Qin & Changjun Yin & Zhengdong Zhang & Koichi Matsuda & Michiaki Kubo & Rong Na & Xiaoling Lin & Haowen Jiang & Shancheng Re, 2015. "Large-scale association analysis in Asians identifies new susceptibility loci for prostate cancer," Nature Communications, Nature, vol. 6(1), pages 1-7, December.
    4. Kornelia Polyak & Yong Xia & Jay L. Zweier & Kenneth W. Kinzler & Bert Vogelstein, 1997. "A model for p53-induced apoptosis," Nature, Nature, vol. 389(6648), pages 300-305, September.
    5. Chikashi Terao & Akari Suzuki & Yukihide Momozawa & Masato Akiyama & Kazuyoshi Ishigaki & Kazuhiko Yamamoto & Koichi Matsuda & Yoshinori Murakami & Steven A. McCarroll & Michiaki Kubo & Po-Ru Loh & Yo, 2020. "Chromosomal alterations among age-related haematopoietic clones in Japan," Nature, Nature, vol. 584(7819), pages 130-135, August.
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    Cited by:

    1. Yuki Ishikawa & Nao Tanaka & Yoshihide Asano & Masanari Kodera & Yuichiro Shirai & Mitsuteru Akahoshi & Minoru Hasegawa & Takashi Matsushita & Kazuyoshi Saito & Sei-ichiro Motegi & Hajime Yoshifuji & , 2024. "GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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