ABSTRACT

Testicular germ cell tumours (TGCTs) are the most common cancer in young male adults (aged 15 to 40). Unlike most other cancer types, identification of molecular signatures in TGCT has rarely reported. In this study, we developed a novel integrative analysis framework to identify co-methylated and co-expressed genes [mRNAs and microRNAs (miRNAs)] modules in two TGCT subtypes: non-seminoma (NSE) and seminoma (SE). We first integrated DNA methylation and mRNA/miRNA expression data and then used a statistical method, CoMEx (Combined score of DNA Methylation and Expression), to assess differentially expressed and methylated (DEM) genes/miRNAs. Next, we identified co-methylation and co-expression modules by applying WGCNA (Weighted Gene Correlation Network Analysis) tool to these DEM genes/miRNAs. The module with the highest average Pearson’s Correlation Coefficient (PCC) after considering all pair-wise molecules (genes/miRNAs) included 91 molecules. By integrating both transcription factor and miRNA regulations, we constructed subtype-specific regulatory networks for NSE and SE. We identified four hub miRNAs (miR-182-5p, miR-520b, miR-520c-3p, and miR-7-5p), two hub TFs (MYC and SP1), and two genes (RECK and TERT) in the NSE-specific regulatory network, and two hub miRNAs (miR-182-5p and miR-338-3p), five hub TFs (ETS1, HIF1A, HNF1A, MYC, and SP1), and three hub genes (CDH1, CXCR4, and SNAI1) in the SE-specific regulatory network. miRNA (miR-182-5p) and two TFs (MYC and SP1) were common hubs of NSE and SE. We further examined pathways enriched in these subtype-specific networks. Our study provides a comprehensive view of the molecular signatures and co-regulation in two TGCT subtypes.

摘要

睾丸生殖细胞肿瘤 (TGCT) 是年轻男性（15 至 40 岁）中最常见的癌症。与大多数其他癌症类型不同，在 TGCT 中鉴定分子特征的报道很少。在这项研究中，我们开发了一种新的综合分析框架来识别两种 TGCT 亚型：非精原细胞瘤 (NSE) 和精原细胞瘤 (SE) 中的共甲基化和共表达基因 [mRNAs 和 microRNAs (miRNAs)] 模块。我们首先整合 DNA 甲基化和 mRNA/miRNA 表达数据，然后使用统计方法 CoMEx（DNA M乙基化和表达的组合评分）来评估差异表达和甲基化 (DEM) 基因/miRNA。接下来，我们通过应用 WGCNA ( W八这些DEM基因/miRNA 的基因C相关网络分析）工具。在考虑所有成对分子（基因/miRNA）后，具有最高平均 Pearson 的 C 相关系数（PCC）的模块包括91个分子。通过整合转录因子和 miRNA 调控，我们构建了 NSE 和 SE 的亚型特异性调控网络。我们鉴定了四个中枢 miRNA（miR-182-5p、miR-520b、miR-520c-3p 和 miR-7-5p）、两个中枢 TF（MYC 和 SP1）和两个基因（RECK和TERT）在 NSE 特异性调控网络中，以及两个中枢 miRNA（miR-182-5p 和 miR-338-3p）、五个中枢 TF（ETS1、HIF1A、HNF1A、MYC 和 SP1）和三个中枢基因（CDH1、 CXCR4和SNAI1）在 SE 特定的监管网络中。miRNA (miR-182-5p) 和两个 TFs (MYC 和 SP1) 是 NSE 和 SE 的共同枢纽。我们进一步检查了富含这些亚型特异性网络的途径。我们的研究提供了两种 TGCT 亚型中分子特征和共同调控的全面视图。