Haitao Chen1,2,3, Hongjie Yu1, Jianqing Wang4, Zheng Zhang2, Zhengrong Gao2, Zhuo Chen2, Yulan Lu1, Wennuan Liu5, Deke Jiang1,5, S Lilly Zheng2,5, Gong-Hong Wei6, William B Issacs7, Junjie Feng2, Jianfeng Xu1,2,3,4,5. 1. State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, P.R. China. 2. Center for Cancer Genomics, Wake Forest University School of Medicine, Winston Salem, North Carolina. 3. Center for Genomic Translational Medicine and Prevention, Fudan School of Public Health, Fudan University, Shanghai, P.R. China. 4. Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, P.R. China. 5. Program for Personalized Cancer Care and Department of Surgery, North Shore University Health System, Evanston, Illinois. 6. Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland. 7. Department of Urology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Abstract
BACKGROUND: More than 100 prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) have been identified by genome wide association studies (GWAS). However, the molecular mechanisms are unclear for most of these SNPs. METHODS: All reported PCa risk-associated SNPs reaching the genome-wide significance level of P < 1 × 10(-7) (index SNPs), as well as SNPs in linkage disequilibrium (LD, r(2) ≥ 0.5) with them were cataloged. Genomic regions with potentially functional impact were also identified, including UCSC annotated coding regions (exon and snoRNA/miRNA) and regulatory regions, as well as binding regions for transcription factors (TFs), histone modifications (HMs), DNase I hypersensitivity (DHSs), and RNA Polymerase IIA (POLR2A) defined by ChIP-Seq in prostate cell lines and tissues. Enrichment analysis was performed to test whether PCa risk-associated SNPs are located in these functional regions more than expected. RESULTS: A total of 103 PCa risk-associated index SNPs and 7,244 SNPs in LD with these index SNPs were cataloged. Genomic regions with potentially functional impact, grouped in 30 different categories of functionalities, were identified. Enrichment analysis indicated that genomic regions in the following 15 categories were enriched for the PCa risk-associated SNPs: exons, CpG regions, 6 TFs (AR, ERG, FOXA1, HOXB13, CTCF, and NR3C1), 5 HMs (H3K4me1, H3K4me2, H3K4me3, H3K27AC, and H3T11P), DHSs and POLR2A. In contrast, significantly fewer PCa risk SNPs were mapped to binding regions for H3K27me3, a repressive chromatin marker. CONCLUSIONS: The PCa risk-associated SNPs discovered to date may affect PCa risk through multiple different mechanisms, especially by affecting binding regions of TFs/HMs.
BACKGROUND: More than 100 prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) have been identified by genome wide association studies (GWAS). However, the molecular mechanisms are unclear for most of these SNPs. METHODS: All reported PCa risk-associated SNPs reaching the genome-wide significance level of P < 1 × 10(-7) (index SNPs), as well as SNPs in linkage disequilibrium (LD, r(2) ≥ 0.5) with them were cataloged. Genomic regions with potentially functional impact were also identified, including UCSC annotated coding regions (exon and snoRNA/miRNA) and regulatory regions, as well as binding regions for transcription factors (TFs), histone modifications (HMs), DNase I hypersensitivity (DHSs), and RNA Polymerase IIA (POLR2A) defined by ChIP-Seq in prostate cell lines and tissues. Enrichment analysis was performed to test whether PCa risk-associated SNPs are located in these functional regions more than expected. RESULTS: A total of 103 PCa risk-associated index SNPs and 7,244 SNPs in LD with these index SNPs were cataloged. Genomic regions with potentially functional impact, grouped in 30 different categories of functionalities, were identified. Enrichment analysis indicated that genomic regions in the following 15 categories were enriched for the PCa risk-associated SNPs: exons, CpG regions, 6 TFs (AR, ERG, FOXA1, HOXB13, CTCF, and NR3C1), 5 HMs (H3K4me1, H3K4me2, H3K4me3, H3K27AC, and H3T11P), DHSs and POLR2A. In contrast, significantly fewer PCa risk SNPs were mapped to binding regions for H3K27me3, a repressive chromatin marker. CONCLUSIONS: The PCa risk-associated SNPs discovered to date may affect PCa risk through multiple different mechanisms, especially by affecting binding regions of TFs/HMs.
Authors: Andrew J Fritz; Prachi N Ghule; Joseph R Boyd; Coralee E Tye; Natalie A Page; Deli Hong; David J Shirley; Adam S Weinheimer; Ahmet R Barutcu; Diana L Gerrard; Seth Frietze; Andre J van Wijnen; Sayyed K Zaidi; Anthony N Imbalzano; Jane B Lian; Janet L Stein; Gary S Stein Journal: J Cell Physiol Date: 2017-06-22 Impact factor: 6.384
Authors: Yijun Tian; Alex Soupir; Qian Liu; Lang Wu; Chiang-Ching Huang; Jong Y Park; Liang Wang Journal: Hum Mol Genet Date: 2022-05-19 Impact factor: 5.121
Authors: Craig C Teerlink; Daniel Leongamornlert; Tokhir Dadaev; Alun Thomas; James Farnham; Robert A Stephenson; Shaun Riska; Shannon K McDonnell; Daniel J Schaid; William J Catalona; S Lilly Zheng; Kathleen A Cooney; Anna M Ray; Kimberly A Zuhlke; Ethan M Lange; Graham G Giles; Melissa C Southey; Liesel M Fitzgerald; Antje Rinckleb; Manuel Luedeke; Christiane Maier; Janet L Stanford; Elaine A Ostrander; Elina M Kaikkonen; Csilla Sipeky; Teuvo Tammela; Johanna Schleutker; Kathleen E Wiley; Sarah D Isaacs; Patrick C Walsh; William B Isaacs; Jianfeng Xu; Geraldine Cancel-Tassin; Olivier Cussenot; Diptasri Mandal; Cecelia Laurie; Cathy Laurie; Stephen N Thibodeau; Rosalind A Eeles; Zsofia Kote-Jarai; Lisa Cannon-Albright Journal: Hum Genet Date: 2016-06-04 Impact factor: 4.132