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

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 m...

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Veröffentlicht in:Nature communications Jg. 14; H. 1; S. 4863 - 10
Hauptverfasser: Ito, Shuji, Liu, Xiaoxi, Ishikawa, Yuki, Conti, David D., Otomo, Nao, Kote-Jarai, Zsofia, Suetsugu, Hiroyuki, Eeles, Rosalind A., Koike, Yoshinao, Hikino, Keiko, Yoshino, Soichiro, Tomizuka, Kohei, Horikoshi, Momoko, Ito, Kaoru, Uchio, Yuji, Momozawa, Yukihide, Kubo, Michiaki, Kamatani, Yoichiro, Matsuda, Koichi, Haiman, Christopher A., Ikegawa, Shiro, Nakagawa, Hidewaki, Terao, Chikashi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 23.08.2023
Nature Publishing Group
Nature Portfolio
Schlagworte:
45/43
631/208/69
631/67/68
692/4028/67/589/466
Androgen receptors
Androgens
Binding sites
Data analysis
Genetic analysis
Health risks
Humanities and Social Sciences
Meta-analysis
Mortality
Mortality risk
multidisciplinary
Predictions
Prostate cancer
Receptors
Risk analysis
Science
Science (multidisciplinary)
Tumor suppressor genes
ISSN:2041-1723, 2041-1723
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Zusammenfassung: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. The prediction of mortality due to prostate cancer remains challenging. Here, the authors perform trans-ancestry metaanalysis with a focus on binding sites of the androgen receptor and develop a polygenic risk score.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-023-39858-8