KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.
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DOI:
10.1038/s41598-021-85169-7
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发表时间:
2021-04-29
期刊:
影响因子:
4.6
通讯作者:
Park JY
Park JY
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Lin HY;Huang PY;Cheng CH;Tung HY;Fang Z;Berglund AE;Chen A;French-Kwawu J;Harris D;Pow-Sang J;Yamoah K;Cleveland JL;Awasthi S;Rounbehler RJ;Gerke T;Dhillon J;Eeles R;Kote-Jarai Z;Muir K;UKGPCS collaborators;Schleutker J;Pashayan N;APCB (Australian Prostate Cancer BioResource);Neal DE;Nielsen SF;Nordestgaard BG;Gronberg H;Wiklund F;Giles GG;Haiman CA;Travis RC;Stanford JL;Kibel AS;Cybulski C;Khaw KT;Maier C;Thibodeau SN;Teixeira MR;Cannon-Albright L;Brenner H;Kaneva R;Pandha H;PRACTICAL consortium;Srinivasan S;Clements J;Batra J;Park JY

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前列腺癌(PCa)侵袭性的风险分类和潜在机制仍不充分。单核苷酸多态(SNPs)之间的相互作用可能为填补这些空白提供一种解决方案。为了确定与PCa侵袭性相关的四条途径(血管生成、线粒体、miRNA和雄激素代谢相关途径)中SNP-SNP的相互作用,我们测试了来自PCa联盟的20,729例患者的8587个SNP。我们发现了3个KLK3SNP,其中1083(P < 3.5 × 10-9)和3145(P < 1 × 10-5)SNP-SNP交互作用对与PCa侵袭性显著相关。这些与PCA攻击性相关的SNP对比它们各自构成的SNP个体效应更显著。在3145对中,大部分(98.6%)涉及KLK3。最常见的3种基因-基因相互作用是KLK3-COL4A1:COL4A2、KLK3-CDH13和KLK3-TGFBR3。基于24个SNP对的基于SNP相互作用的多基因风险评分的预测是有希望的。在我们的队列中,前列腺癌侵袭性的患病率分别为49.8%、21.9%和7.0%,风险分布在前1%、中50%和后1%。基因表达和蛋白质-蛋白质相互作用结果支持KLK3SNP-SNP相互作用的潜在生物学功能。我们的研究结果表明,KLK3SNP的相互作用可能在前列腺癌的侵袭性中发挥重要作用。
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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发表时间: 2009-06
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