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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10447511/ https://www.ncbi.nlm.nih.gov/pubmed/37612283 http://dx.doi.org/10.1038/s41467-023-39858-8 |
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author | 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 |
author_facet | 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 |
author_sort | Ito, Shuji |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10447511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104475112023-08-25 Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects 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 Nat Commun Article 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. Nature Publishing Group UK 2023-08-23 /pmc/articles/PMC10447511/ /pubmed/37612283 http://dx.doi.org/10.1038/s41467-023-39858-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article 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 Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
title | Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
title_full | Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
title_fullStr | Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
title_full_unstemmed | Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
title_short | Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
title_sort | androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10447511/ https://www.ncbi.nlm.nih.gov/pubmed/37612283 http://dx.doi.org/10.1038/s41467-023-39858-8 |
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