肝细胞癌中异常甲基化差异表达基因和通路的生物信息学分析。
Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma.
机构信息
Department of Ultrasound, The First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
出版信息
World J Gastroenterol. 2018 Jun 28;24(24):2605-2616. doi: 10.3748/wjg.v24.i24.2605.
AIM
To discover methylated-differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC) and to explore relevant hub genes and potential pathways.
METHODS
The data of expression profiling GSE25097 and methylation profiling GSE57956 were gained from GEO Datasets. We analyzed the differentially methylated genes and differentially expressed genes online using GEO2R. Functional and enrichment analyses of MDEGs were conducted using the DAVID database. A protein-protein interaction (PPI) network was performed by STRING and then visualized in Cytoscape. Hub genes were ranked by cytoHubba, and a module analysis of the PPI network was conducted by MCODE in Cytoscape software.
RESULTS
In total, we categorized 266 genes as hypermethylated, lowly expressed genes (Hyper-LGs) referring to endogenous and hormone stimulus, cell surface receptor linked signal transduction and behavior. In addition, 161 genes were labelled as hypomethylated, highly expressed genes (Hypo-HGs) referring to DNA replication and metabolic process, cell cycle and division. Pathway analysis illustrated that Hyper-LGs were enriched in cancer, Wnt, and chemokine signalling pathways, while Hypo-HGs were related to cell cycle and steroid hormone biosynthesis pathways. Based on PPI networks, , , , , and were identified as hub genes for Hyper-LGs, and , , , , , and were hub genes for Hypo-HGs by combining six ranked methods of cytoHubba.
CONCLUSION
In the study, we disclose numerous novel genetic and epigenetic regulations and offer a vital molecular groundwork to understand the pathogenesis of HCC. Hub genes, including , , , , , , , , , , and , can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of HCC.
目的
发现肝细胞癌（HCC）中甲基化差异表达基因（MDEGs），并探讨相关的枢纽基因和潜在途径。
方法
从 GEO 数据集获得表达谱 GSE25097 和甲基化谱 GSE57956 的数据。我们在线使用 GEO2R 分析差异甲基化基因和差异表达基因。使用 DAVID 数据库对 MDEGs 进行功能和富集分析。通过 STRING 构建蛋白质-蛋白质相互作用（PPI）网络，并在 Cytoscape 中可视化。使用 cytoHubba 对枢纽基因进行排名，并在 Cytoscape 软件中使用 MCODE 对 PPI 网络进行模块分析。
结果
总共将 266 个基因归类为内源性和激素刺激、细胞表面受体连接的信号转导和行为的高甲基化、低表达基因（Hyper-LGs）。此外，161 个基因被标记为低甲基化、高表达基因（Hypo-HGs），与 DNA 复制和代谢过程、细胞周期和分裂有关。通路分析表明，Hyper-LGs 富集在癌症、Wnt 和趋化因子信号通路中，而 Hypo-HGs 与细胞周期和甾体激素生物合成通路有关。基于 PPI 网络，通过结合 cytoHubba 的六种排序方法，确定了 、 、 、 、 、 为 Hyper-LGs 的枢纽基因，确定了 、 、 、 、 、 、 、 和 为 Hypo-HGs 的枢纽基因。
结论
在本研究中，我们揭示了许多新的遗传和表观遗传调控，并为理解 HCC 的发病机制提供了重要的分子基础。枢纽基因，包括 、 、 、 、 、 、 、 和 ，可以作为基于异常甲基化的 HCC 准确诊断和治疗的生物标志物。
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