The regulatory variation is believed to play an important role in shaping phenotypic differences among individuals and thus is also very likely to influence disease susceptibility and progression. In this study, we propose to take advantage of the expression QTL mapping and co-expressed gene network analysis to identify and characterize candidate genes and genetic variants that are responsible for aggressive phenotype of prostate cancer. Our hypothesis is that most genetic variants responsible for an aggressive phenotype of prostate cancer have regulatory effect on candidate gene expression and complete understanding of regulatory SNPs can only be achieved by examining primary tissue (here, prostate). To test this hypothesis, we will use a case-case study design and apply an innovative yet feasible approach by integrating DNA sequence variation and gene expression with clinical trait information. The four Specific Aims are: 1. Identify novel aggressiveness-related candidate SNPs by utilizing an expression genetics-based eQTL mapping approach; 2, Identify novel aggressiveness-related candidate SNPs by utilizing an integrative systems genetics-based network analysis approach; 3. For the novel candidate SNPs identified in Aims 1 and 2, perform additional association-based studies to confirm their association with an aggressiveness-related phenotype for prostate cancer; and 4. Identify candidate causal-SNPs by fine mapping, recognizing that the candidate eSNPs identified in Aim 3 will most likely be in linkage disequilibrium with the causal-SNPs. Understanding genetic mechanisms underlying the aggressive phenotype will have significant impact on prevention strategies, prognosis and potentially targeted therapy.

Public Health Relevance

Prostate cancer can be relatively harmless or extremely aggressive. The goal of this study is to identify and characterize genetic causes of the aggressive (clinically more significant) form of prostate cancer. An understanding the genetic mechanism underlying the aggressive disease will have a significant impact on prevention strategies; prognosis and potentially targeted therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
7R01CA157881-02
Application #
8415383
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Elena, Joanne W
Project Start
2011-09-02
Project End
2016-07-31
Budget Start
2011-10-01
Budget End
2012-07-31
Support Year
2
Fiscal Year
2011
Total Cost
$637,767
Indirect Cost
Name
Medical College of Wisconsin
Department
Pathology
Type
Schools of Medicine
DUNS #
937639060
City
Milwaukee
State
WI
Country
United States
Zip Code
53226
Gao, Ping; Xia, Ji-Han; Sipeky, Csilla et al. (2018) Biology and Clinical Implications of the 19q13 Aggressive Prostate Cancer Susceptibility Locus. Cell 174:576-589.e18
Sipeky, Csilla; Gao, Ping; Zhang, Qin et al. (2018) Synergistic Interaction of HOXB13 and CIP2A Predisposes to Aggressive Prostate Cancer. Clin Cancer Res 24:6265-6276
Zhang, Peng; Xia, Ji-Han; Zhu, Jing et al. (2018) High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing. Nat Commun 9:2022
Larson, Nicholas B; McDonnell, Shannon K; Fogarty, Zach et al. (2017) Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci. Oncotarget 8:85896-85908
Zhu, Jing; Zhang, Fan; Du, Meijun et al. (2017) Molecular characterization of cell-free eccDNAs in human plasma. Sci Rep 7:10968
Winter, Jean M; Gildea, Derek E; Andreas, Jonathan P et al. (2017) Mapping Complex Traits in a Diversity Outbred F1 Mouse Population Identifies Germline Modifiers of Metastasis in Human Prostate Cancer. Cell Syst 4:31-45.e6
Yuan, Tiezheng; Huang, Xiaoyi; Woodcock, Mark et al. (2016) Plasma extracellular RNA profiles in healthy and cancer patients. Sci Rep 6:19413
Du, Meijun; Tillmans, Lori; Gao, Jianzhong et al. (2016) Chromatin interactions and candidate genes at ten prostate cancer risk loci. Sci Rep 6:23202
Xia, Yun; Huang, Chiang-Ching; Dittmar, Rachel et al. (2016) Copy number variations in urine cell free DNA as biomarkers in advanced prostate cancer. Oncotarget 7:35818-35831
Du, Meijun; Wang, Liang (2016) 3C-digital PCR for quantification of chromatin interactions. BMC Mol Biol 17:23

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