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KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, mi...

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Autores principales: Lin, Hui-Yi, Huang, Po-Yu, Cheng, Chia-Ho, Tung, Heng-Yuan, Fang, Zhide, Berglund, Anders E., Chen, Ann, French-Kwawu, Jennifer, Harris, Darian, Pow-Sang, Julio, Yamoah, Kosj, Cleveland, John L., Awasthi, Shivanshu, Rounbehler, Robert J., Gerke, Travis, Dhillon, Jasreman, Eeles, Rosalind, Kote-Jarai, Zsofia, Muir, Kenneth, Schleutker, Johanna, Pashayan, Nora, Neal, David E., Nielsen, Sune F., Nordestgaard, Børge G., Gronberg, Henrik, Wiklund, Fredrik, Giles, Graham G., Haiman, Christopher A., Travis, Ruth C., Stanford, Janet L., Kibel, Adam S., Cybulski, Cezary, Khaw, Kay-Tee, Maier, Christiane, Thibodeau, Stephen N., Teixeira, Manuel R., Cannon-Albright, Lisa, Brenner, Hermann, Kaneva, Radka, Pandha, Hardev, Srinivasan, Srilakshmi, Clements, Judith, Batra, Jyotsna, Park, Jong Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084951/
https://www.ncbi.nlm.nih.gov/pubmed/33927218
http://dx.doi.org/10.1038/s41598-021-85169-7
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author Lin, Hui-Yi
Huang, Po-Yu
Cheng, Chia-Ho
Tung, Heng-Yuan
Fang, Zhide
Berglund, Anders E.
Chen, Ann
French-Kwawu, Jennifer
Harris, Darian
Pow-Sang, Julio
Yamoah, Kosj
Cleveland, John L.
Awasthi, Shivanshu
Rounbehler, Robert J.
Gerke, Travis
Dhillon, Jasreman
Eeles, Rosalind
Kote-Jarai, Zsofia
Muir, Kenneth
Schleutker, Johanna
Pashayan, Nora
Neal, David E.
Nielsen, Sune F.
Nordestgaard, Børge G.
Gronberg, Henrik
Wiklund, Fredrik
Giles, Graham G.
Haiman, Christopher A.
Travis, Ruth C.
Stanford, Janet L.
Kibel, Adam S.
Cybulski, Cezary
Khaw, Kay-Tee
Maier, Christiane
Thibodeau, Stephen N.
Teixeira, Manuel R.
Cannon-Albright, Lisa
Brenner, Hermann
Kaneva, Radka
Pandha, Hardev
Srinivasan, Srilakshmi
Clements, Judith
Batra, Jyotsna
Park, Jong Y.
author_facet Lin, Hui-Yi
Huang, Po-Yu
Cheng, Chia-Ho
Tung, Heng-Yuan
Fang, Zhide
Berglund, Anders E.
Chen, Ann
French-Kwawu, Jennifer
Harris, Darian
Pow-Sang, Julio
Yamoah, Kosj
Cleveland, John L.
Awasthi, Shivanshu
Rounbehler, Robert J.
Gerke, Travis
Dhillon, Jasreman
Eeles, Rosalind
Kote-Jarai, Zsofia
Muir, Kenneth
Schleutker, Johanna
Pashayan, Nora
Neal, David E.
Nielsen, Sune F.
Nordestgaard, Børge G.
Gronberg, Henrik
Wiklund, Fredrik
Giles, Graham G.
Haiman, Christopher A.
Travis, Ruth C.
Stanford, Janet L.
Kibel, Adam S.
Cybulski, Cezary
Khaw, Kay-Tee
Maier, Christiane
Thibodeau, Stephen N.
Teixeira, Manuel R.
Cannon-Albright, Lisa
Brenner, Hermann
Kaneva, Radka
Pandha, Hardev
Srinivasan, Srilakshmi
Clements, Judith
Batra, Jyotsna
Park, Jong Y.
author_sort Lin, Hui-Yi
collection PubMed
description Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10(–9)) and 3145 (P < 1 × 10(–5)) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.
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spelling pubmed-80849512021-04-30 KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness Lin, Hui-Yi Huang, Po-Yu Cheng, Chia-Ho Tung, Heng-Yuan Fang, Zhide Berglund, Anders E. Chen, Ann French-Kwawu, Jennifer Harris, Darian Pow-Sang, Julio Yamoah, Kosj Cleveland, John L. Awasthi, Shivanshu Rounbehler, Robert J. Gerke, Travis Dhillon, Jasreman Eeles, Rosalind Kote-Jarai, Zsofia Muir, Kenneth Schleutker, Johanna Pashayan, Nora Neal, David E. Nielsen, Sune F. Nordestgaard, Børge G. Gronberg, Henrik Wiklund, Fredrik Giles, Graham G. Haiman, Christopher A. Travis, Ruth C. Stanford, Janet L. Kibel, Adam S. Cybulski, Cezary Khaw, Kay-Tee Maier, Christiane Thibodeau, Stephen N. Teixeira, Manuel R. Cannon-Albright, Lisa Brenner, Hermann Kaneva, Radka Pandha, Hardev Srinivasan, Srilakshmi Clements, Judith Batra, Jyotsna Park, Jong Y. Sci Rep Article Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10(–9)) and 3145 (P < 1 × 10(–5)) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness. Nature Publishing Group UK 2021-04-29 /pmc/articles/PMC8084951/ /pubmed/33927218 http://dx.doi.org/10.1038/s41598-021-85169-7 Text en © The Author(s) 2021 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Lin, Hui-Yi
Huang, Po-Yu
Cheng, Chia-Ho
Tung, Heng-Yuan
Fang, Zhide
Berglund, Anders E.
Chen, Ann
French-Kwawu, Jennifer
Harris, Darian
Pow-Sang, Julio
Yamoah, Kosj
Cleveland, John L.
Awasthi, Shivanshu
Rounbehler, Robert J.
Gerke, Travis
Dhillon, Jasreman
Eeles, Rosalind
Kote-Jarai, Zsofia
Muir, Kenneth
Schleutker, Johanna
Pashayan, Nora
Neal, David E.
Nielsen, Sune F.
Nordestgaard, Børge G.
Gronberg, Henrik
Wiklund, Fredrik
Giles, Graham G.
Haiman, Christopher A.
Travis, Ruth C.
Stanford, Janet L.
Kibel, Adam S.
Cybulski, Cezary
Khaw, Kay-Tee
Maier, Christiane
Thibodeau, Stephen N.
Teixeira, Manuel R.
Cannon-Albright, Lisa
Brenner, Hermann
Kaneva, Radka
Pandha, Hardev
Srinivasan, Srilakshmi
Clements, Judith
Batra, Jyotsna
Park, Jong Y.
KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
title KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
title_full KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
title_fullStr KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
title_full_unstemmed KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
title_short KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
title_sort klk3 snp–snp interactions for prediction of prostate cancer aggressiveness
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084951/
https://www.ncbi.nlm.nih.gov/pubmed/33927218
http://dx.doi.org/10.1038/s41598-021-85169-7
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