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| 001 | 168679 | ||
| 005 | 20240229133612.0 | ||
| 024 | 7 | _ | |a 10.1038/s41598-021-85169-7 |2 doi |
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| 037 | _ | _ | |a DKFZ-2021-00987 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 600 |
| 100 | 1 | _ | |a Lin, Hui-Yi |b 0 |
| 245 | _ | _ | |a KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness. |
| 260 | _ | _ | |a [London] |c 2021 |b Macmillan Publishers Limited, part of Springer Nature |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1620224496_814 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a 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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| 700 | 1 | _ | |a Huang, Po-Yu |b 1 |
| 700 | 1 | _ | |a Cheng, Chia-Ho |b 2 |
| 700 | 1 | _ | |a Tung, Heng-Yuan |b 3 |
| 700 | 1 | _ | |a Fang, Zhide |b 4 |
| 700 | 1 | _ | |a Berglund, Anders E |b 5 |
| 700 | 1 | _ | |a Chen, Ann |b 6 |
| 700 | 1 | _ | |a French-Kwawu, Jennifer |b 7 |
| 700 | 1 | _ | |a Harris, Darian |b 8 |
| 700 | 1 | _ | |a Pow-Sang, Julio |b 9 |
| 700 | 1 | _ | |a Yamoah, Kosj |b 10 |
| 700 | 1 | _ | |a Cleveland, John L |b 11 |
| 700 | 1 | _ | |a Awasthi, Shivanshu |b 12 |
| 700 | 1 | _ | |a Rounbehler, Robert J |b 13 |
| 700 | 1 | _ | |a Gerke, Travis |b 14 |
| 700 | 1 | _ | |a Dhillon, Jasreman |b 15 |
| 700 | 1 | _ | |a Eeles, Rosalind |b 16 |
| 700 | 1 | _ | |a Kote-Jarai, Zsofia |b 17 |
| 700 | 1 | _ | |a Muir, Kenneth |b 18 |
| 700 | 1 | _ | |a UKGPCS collaborators |b 19 |e Collaboration Author |
| 700 | 1 | _ | |a Schleutker, Johanna |b 20 |
| 700 | 1 | _ | |a Pashayan, Nora |b 21 |
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| 700 | 1 | _ | |a Neal, David E |b 23 |
| 700 | 1 | _ | |a Nielsen, Sune F |b 24 |
| 700 | 1 | _ | |a Nordestgaard, Børge G |b 25 |
| 700 | 1 | _ | |a Gronberg, Henrik |b 26 |
| 700 | 1 | _ | |a Wiklund, Fredrik |b 27 |
| 700 | 1 | _ | |a Giles, Graham G |b 28 |
| 700 | 1 | _ | |a Haiman, Christopher A |b 29 |
| 700 | 1 | _ | |a Travis, Ruth C |b 30 |
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| 700 | 1 | _ | |a Kaneva, Radka |b 40 |
| 700 | 1 | _ | |a Pandha, Hardev |b 41 |
| 700 | 1 | _ | |a consortium, PRACTICAL |b 42 |e Collaboration Author |
| 700 | 1 | _ | |a Srinivasan, Srilakshmi |b 43 |
| 700 | 1 | _ | |a Clements, Judith |b 44 |
| 700 | 1 | _ | |a Batra, Jyotsna |b 45 |
| 700 | 1 | _ | |a Park, Jong Y |b 46 |
| 700 | 1 | _ | |a Eeles, Rosalind |b 47 |
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| 700 | 1 | _ | |a Clements, Judith |b 50 |
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| 700 | 1 | _ | |a Kaneva, Radka |b 75 |
| 700 | 1 | _ | |a Pandha, Hardev |b 76 |
| 773 | _ | _ | |a 10.1038/s41598-021-85169-7 |g Vol. 11, no. 1, p. 9264 |0 PERI:(DE-600)2615211-3 |n 1 |p 9264 |t Scientific reports |v 11 |y 2021 |x 2045-2322 |
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