Research Papers:

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci

Nicholas B. Larson _, Shannon K. McDonnell, Zach Fogarty, Melissa C. Larson, John Cheville, Shaun Riska, Saurabh Baheti, Alexandra M. Weber, Asha A. Nair, Liang Wang, Daniel O’Brien, Jaime Davila, Daniel J. Schaid and Stephen N. Thibodeau

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Oncotarget. 2017; 8:85896-85908. https://doi.org/10.18632/oncotarget.20717

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Nicholas B. Larson1, Shannon K. McDonnell1, Zach Fogarty1, Melissa C. Larson1, John Cheville2, Shaun Riska1, Saurabh Baheti1, Alexandra M. Weber3, Asha A. Nair1, Liang Wang4, Daniel O’Brien1, Jaime Davila1, Daniel J. Schaid1 and Stephen N. Thibodeau5

1Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

2Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

3Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

4Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA

5Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

Correspondence to:

Nicholas B. Larson, email: Larson.nicholas@mayo.edu

Keywords: prostate cancer, genetic risk, expression quantitative trait loci, mediation

Received: April 26, 2017     Accepted: July 29, 2017     Published: September 08, 2017


Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

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