Abstract

Genome-wide association studies have identified over 150 risk loci that increase prostate cancer risk. However, few causal variants and their regulatory mechanisms have been characterized. In this study, we utilized our previously developed single-nucleotide polymorphisms sequencing (SNPs-seq) technology to test allele-dependent protein binding at 903 SNP sites covering 28 genomic regions. All selected SNPs have shown significant cis-association with at least one nearby gene. After preparing nuclear extract using LNCaP cell line, we first mixed the extract with dsDNA oligo pool for protein–DNA binding incubation. We then performed sequencing analysis on protein-bound oligos. SNPs-seq analysis showed protein-binding differences (>1.5-fold) between reference and variant alleles in 380 (42%) of 903 SNPs with androgen treatment and 403 (45%) of 903 SNPs without treatment. From these significant SNPs, we performed a database search and further narrowed down to 74 promising SNPs. To validate this initial finding, we performed electrophoretic mobility shift assay in two SNPs (rs12246440 and rs7077275) at CTBP2 locus and one SNP (rs113082846) at NCOA4 locus. This analysis showed that all three SNPs demonstrated allele-dependent protein-binding differences that were consistent with the SNPs-seq. Finally, clinical association analysis of the two candidate genes showed that CTBP2 was upregulated, while NCOA4 was downregulated in prostate cancer (p < 0.02). Lower expression of CTBP2 was associated with poor recurrence-free survival in prostate cancer. Utilizing our experimental data along with bioinformatic tools provides a strategy for identifying candidate functional elements at prostate cancer susceptibility loci to help guide subsequent laboratory studies.

Highlights

  • Prostate cancer is the second most common cancer and the fifth leading cause of cancer death among men, with almost 1.3 million new cases and 359,000 associated deaths in 2018 worldwide [1].Histological phenotypes of prostate cancer include adenocarcinoma, squamous cell carcinoma, and neuroendocrine carcinoma

  • We counted sequence reads with a perfect match to one of 1806 oligo template sequences and found that the mappable rate was 75–78% for test samples and 93% for input controls (Figure 2c)

  • We reported a significant fraction of single-nucleotide polymorphisms (SNPs) showing allelic difference for protein binding

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Summary

Introduction

Prostate cancer is the second most common cancer and the fifth leading cause of cancer death among men, with almost 1.3 million new cases and 359,000 associated deaths in 2018 worldwide [1].Histological phenotypes of prostate cancer include adenocarcinoma, squamous cell carcinoma, and neuroendocrine carcinoma. Prostate cancer is the second most common cancer and the fifth leading cause of cancer death among men, with almost 1.3 million new cases and 359,000 associated deaths in 2018 worldwide [1]. Risk factors of prostate cancer involve age, genetics (family history and ethnicity), environmental and lifestyle (smoking and alcohol consumption), and gene–environment interaction [2,3,4]. To identify genetic determinants of prostate cancer risk, over 39 genome-wide association studies (GWAS) on prostate cancer have reported approximately 482 unique prostate cancer risk single-nucleotide polymorphisms (SNPs), based on the NHGRI-EBI catalogue of published GWASs (http://www.ebi.ac.uk/gwas) [5,6]. Potential causal variants and their biological mechanisms at risk loci are largely unknown, even though many post-GWAS studies have unraveled new gene networks and signaling pathways associated with germline variants [7]

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