Scientific Reports (Apr 2021)
KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness
- Hui-Yi Lin,
- Po-Yu Huang,
- Chia-Ho Cheng,
- Heng-Yuan Tung,
- Zhide Fang,
- Anders E. Berglund,
- Ann Chen,
- Jennifer French-Kwawu,
- Darian Harris,
- Julio Pow-Sang,
- Kosj Yamoah,
- John L. Cleveland,
- Shivanshu Awasthi,
- Robert J. Rounbehler,
- Travis Gerke,
- Jasreman Dhillon,
- Rosalind Eeles,
- Zsofia Kote-Jarai,
- Kenneth Muir,
- UKGPCS collaborators,
- Johanna Schleutker,
- Nora Pashayan,
- APCB (Australian Prostate Cancer BioResource),
- David E. Neal,
- Sune F. Nielsen,
- Børge G. Nordestgaard,
- Henrik Gronberg,
- Fredrik Wiklund,
- Graham G. Giles,
- Christopher A. Haiman,
- Ruth C. Travis,
- Janet L. Stanford,
- Adam S. Kibel,
- Cezary Cybulski,
- Kay-Tee Khaw,
- Christiane Maier,
- Stephen N. Thibodeau,
- Manuel R. Teixeira,
- Lisa Cannon-Albright,
- Hermann Brenner,
- Radka Kaneva,
- Hardev Pandha,
- The PRACTICAL consortium,
- Srilakshmi Srinivasan,
- Judith Clements,
- Jyotsna Batra,
- Jong Y. Park
Affiliations
- Hui-Yi Lin
- Biostatistics Program, School of Public Health, Louisiana State University Health Sciences Center
- Po-Yu Huang
- Computational Intelligence Technology Center, Industrial Technology Research Institute
- Chia-Ho Cheng
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center & Research Institute
- Heng-Yuan Tung
- Biostatistics Program, School of Public Health, Louisiana State University Health Sciences Center
- Zhide Fang
- Biostatistics Program, School of Public Health, Louisiana State University Health Sciences Center
- Anders E. Berglund
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center & Research Institute
- Ann Chen
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center & Research Institute
- Jennifer French-Kwawu
- Biostatistics Program, School of Public Health, Louisiana State University Health Sciences Center
- Darian Harris
- Biostatistics Program, School of Public Health, Louisiana State University Health Sciences Center
- Julio Pow-Sang
- Department of Genitourinary Oncology, Moffitt Cancer Center & Research Institute
- Kosj Yamoah
- Department of Radiation Oncology, Moffitt Cancer Center & Research Institute
- John L. Cleveland
- Department of Tumor Biology, Moffitt Cancer Center & Research Institute
- Shivanshu Awasthi
- Department of Cancer Epidemiology, Moffitt Cancer Center & Research Institute
- Robert J. Rounbehler
- Department of Tumor Biology, Moffitt Cancer Center & Research Institute
- Travis Gerke
- Department of Cancer Epidemiology, Moffitt Cancer Center & Research Institute
- Jasreman Dhillon
- Department of Pathology, Moffitt Cancer Center & Research Institute
- Rosalind Eeles
- The Institute of Cancer Research
- Zsofia Kote-Jarai
- The Institute of Cancer Research
- Kenneth Muir
- Division of Population Health, Health Services Research, and Primary Care, University of Manchester
- UKGPCS collaborators
- Johanna Schleutker
- Institute of Biomedicine, University of Turku
- Nora Pashayan
- Department of Applied Health Research, University College London
- APCB (Australian Prostate Cancer BioResource)
- David E. Neal
- Nuffield Department of Surgical Sciences, University of Oxford
- Sune F. Nielsen
- Health and Medical Sciences, University of Copenhagen
- Børge G. Nordestgaard
- Health and Medical Sciences, University of Copenhagen
- Henrik Gronberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute
- Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute
- Graham G. Giles
- Cancer Epidemiology Division
- Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center
- Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford
- Janet L. Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center
- Adam S. Kibel
- Division of Urologic Surgery, Brigham and Womens Hospital
- Cezary Cybulski
- Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University
- Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge
- Christiane Maier
- Humangenetik Tuebingen
- Stephen N. Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic
- Manuel R. Teixeira
- Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto)
- Lisa Cannon-Albright
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine
- Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ)
- Radka Kaneva
- Department of Medical Chemistry and Biochemistry, Molecular Medicine Center, Medical University of Sofia
- Hardev Pandha
- University of Surrey
- The PRACTICAL consortium
- Srilakshmi Srinivasan
- Translational Research Institute
- Judith Clements
- Translational Research Institute
- Jyotsna Batra
- Translational Research Institute
- Jong Y. Park
- Department of Cancer Epidemiology, Moffitt Cancer Center & Research Institute
- DOI
- https://doi.org/10.1038/s41598-021-85169-7
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 15
Abstract
Abstract 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.
