This is a revision of a competitive renewal of an existing funded project to identify prostate cancer (PCa) risk enhancers and their target genes. We intend to identify all target genes affected by newly identified enhancers that contain genetic variation at 77 known PCa risk loci. The major `problem' of genome-wide association (GWAS) loci is the lack of mechanistic understanding of how risk alleles function. This is exacerbated by the fact that the vast majority (>90% of PCa risk alleles) resides in non-coding DNA such as enhancers. This application therefore intends to systematically identify target genes of all the newly identified PCa risk enhancers using three independent approaches, formulated here as three specific aims under the auspices of three co-PIs. The three aims are: eQTL (Coetzee) to link SNP genotypes with levels of gene expression genome-wide, CRISPRs (Farnham) to edit enhancers in situ (deletion and allelic replacement) linking them with gene expression and finally 4C (Lu) to match enhancers with potential target genes by chromatin conformation capture. The strength of this plan is that common target genes identified by all three approaches are likely to be functionally significant. Results will elucidate previously unanticipated risk mechanisms and will provide rationale for diagnosis and prevention.

Public Health Relevance

Over the last few years genetic studies have found hundreds of common genetic variations in the population that affect a person's risk of a multitude of different diseases including heart disease, diabetes and cancer. In the present project we intend to build on work done in the previous grant cycle to identify genes involved in prostate cancer risk. We hope that the data to be acquired will inform preventive and clinical benefits to individuals at risk.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA136924-10
Application #
9626347
Study Section
Cancer Genetics Study Section (CG)
Program Officer
Fingerman, Ian M
Project Start
2008-12-01
Project End
2021-01-31
Budget Start
2019-02-01
Budget End
2021-01-31
Support Year
10
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Southern California
Department
Biochemistry
Type
Schools of Medicine
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Rhie, Suhn K; Schreiner, Shannon; Witt, Heather et al. (2018) Using 3D epigenomic maps of primary olfactory neuronal cells from living individuals to understand gene regulation. Sci Adv 4:eaav8550
Earp, Madalene; Tyrer, Jonathan P; Winham, Stacey J et al. (2018) Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility. PLoS One 13:e0197561
Rhie, Suhn Kyong; Schreiner, Shannon; Farnham, Peggy J (2018) Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq). Methods Mol Biol 1766:209-229
Guo, Yu; Perez, Andrew A; Hazelett, Dennis J et al. (2018) CRISPR-mediated deletion of prostate cancer risk-associated CTCF loop anchors identifies repressive chromatin loops. Genome Biol 19:160
Ong, Jue-Sheng; Hwang, Liang-Dar; Cuellar-Partida, Gabriel et al. (2018) Assessment of moderate coffee consumption and risk of epithelial ovarian cancer: a Mendelian randomization study. Int J Epidemiol 47:450-459
Rhie, Suhn Kyong; Yao, Lijun; Luo, Zhifei et al. (2018) ZFX acts as a transcriptional activator in multiple types of human tumors by binding downstream of transcription start sites at the majority of CpG island promoters. Genome Res :
Luo, Zhifei; Rhie, Suhn Kyong; Lay, Fides D et al. (2017) A Prostate Cancer Risk Element Functions as a Repressive Loop that Regulates HOXA13. Cell Rep 21:1411-1417
Kar, Siddhartha P; Adler, Emily; Tyrer, Jonathan et al. (2017) Enrichment of putative PAX8 target genes at serous epithelial ovarian cancer susceptibility loci. Br J Cancer 116:524-535
Amos, Christopher I; Dennis, Joe; Wang, Zhaoming et al. (2017) The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers. Cancer Epidemiol Biomarkers Prev 26:126-135
Hazelett, Dennis J; Conti, David V; Han, Ying et al. (2016) Reducing GWAS Complexity. Cell Cycle 15:22-4

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