Genome-wide association studies (GWASs) have identified more than 200 prostate cancer (PrCa) risk regions, which provide potential insights into causal mechanisms. Multiple lines of evidence show that a significant proportion of PrCa risk can be explained by germline causal variants that dysregulate nearby target genes in prostate-relevant tissues, thus altering disease risk. The traditional approach to explore this hypothesis has been correlating GWAS variants with steady-state transcript levels, referred to as expression quantitative trait loci (eQTLs). In this work, we assess the utility of chromosome conformation capture (3C) coupled with immunoprecipitation (HiChIP) to identify target genes for PrCa GWAS risk loci. We find that interactome data confirm previously reported PrCa target genes identified through GWAS/eQTL overlap (e.g., MLPH). Interestingly, HiChIP identifies links between PrCa GWAS variants and genes well-known to play a role in prostate cancer biology (e.g., AR) that are not detected by eQTL-based methods. HiChIP predicted enhancer elements at the AR and NKX3-1 prostate cancer risk loci, and both were experimentally confirmed to regulate expression of the corresponding genes through CRISPR interference (CRISPRi) perturbation in LNCaP cells. Our results demonstrate that looping data harbor additional information beyond eQTLs and expand the number of PrCa GWAS loci that can be linked to candidate susceptibility genes.

全基因组关联研究 (GWAS) 已经确定了 200 多个前列腺癌 (PrCa) 风险区域，这些区域提供了对因果机制的潜在见解。多条证据表明，很大一部分 PrCa 风险可以通过生殖系因果变异来解释，这些变异使前列腺相关组织中附近的靶基因失调，从而改变疾病风险。探索这一假设的传统方法是将 GWAS 变体与稳态转录水平相关联，称为表达数量性状基因座 (eQTL)。在这项工作中，我们评估了染色体构象捕获 (3C) 与免疫沉淀 (HiChIP) 在识别 PrCa GWAS 风险位点的靶基因方面的效用。我们发现相互作用组数据证实了先前报道的通过 GWAS/eQTL 重叠鉴定的 PrCa 靶基因（例如，MLPH）。有趣的是，HiChIP 确定了 PrCa GWAS 变体与众所周知的在前列腺癌生物学中发挥作用的基因（例如，AR）之间的联系，这些基因无法通过基于 eQTL 的方法检测到。HiChIP 预测了AR和NKX3-1前列腺癌风险基因座的增强子元件，并且实验证实两者都通过 CRISPR 干扰 (CRISPRi) 扰动在 LNCaP 细胞中调节相应基因的表达。我们的结果表明，循环数据包含超出 eQTL 的额外信息，并扩大了与候选易感基因相关的 PrCa GWAS 基因座的数量。