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目的通过功能富集与网络分析方法,对肝癌浸润相关候选基因进行生物信息学分析,旨在从分子水平系统探究肝癌浸润的发病机制,并为后续实验提供一些有意义的信息。方法首先,从与肝癌相关公共数据库Liverome下载与肝癌浸润相关的差异表达基因,共涉及278个相关候选基因。然后,通过Topp Fun、STRING、Network Analyzer等生物信息学分析工具,对涉及的278个与肝癌浸润相关候选基因进行系统的分析。最后,通过网络映射分析方法,对与肝癌浸润相关候选基因进行关键基因(Hub Gene)筛选,并通过i HOP在线软件,以及Pubmed文献检索方法对这些基因进行文献挖掘分析。结果通过对与肝癌浸润相关候选基因进行功能富集分析发现,这些基因主要参与细胞周期与增殖、细胞迁移与黏附、细胞骨架、血管形成等生物过程,而且这些基因共表达于肝癌与肝癌转移上调和下调等基因功能。对相关基因进行通路富集分析发现,这些基因参与调控细胞周期与增殖、能量供给、赖氨酸降解等生物通路,对肝癌浸润的发生、发展发挥调控作用。除此之外,通过网络分析方法,找到PLK1、AURKB、CDC20、CDK4、MCM3等20个处于网络关键节点的基因(Hub Gene)。之后,通过文献检索方式,对关键基因进行与肝癌浸润相关的功能验证,发现并预测CDC20、CDCA8、NUP37、ZWINT基因与肝癌浸润过程存在关联但作用机制尚未被挖掘。结论利用生物信息学手段,能够有效分析肝癌浸润的相关基因,并可以从分子水平系统探究其发病机制,为临床诊疗及后续实验提供一些有价值的信息。
Objective To analyze the bioinformatics of liver cancer infiltration related candidate genes through functional enrichment and network analysis methods, aiming to explore the pathogenesis of liver cancer infiltration from the molecular level system, and provide some meaningful information for follow-up experiments. Methods Firstly, differentially expressed genes related to hepatocellular carcinoma infiltration were downloaded from Live Rome, a public database related to liver cancer. A total of 278 related candidate genes were involved. Then, through the use of bioinformatics analysis tools such as Topp Fun, STRING, and Network Analyzer, 278 involved candidate genes involved in hepatocarcinogenesis were systematically analyzed. Finally, the key genes (Hub Gene) were screened for candidate genes related to hepatocellular carcinoma infiltration through network mapping analysis methods, and these genes were analyzed by literature retrieval using i HOP online software and Pubmed literature search methods. Results Through functional enrichment analysis of candidate genes related to hepatocellular carcinoma infiltration, these genes were mainly involved in cell cycle and proliferation, cell migration and adhesion, cytoskeleton, angiogenesis and other biological processes, and these genes were co-expressed in the metastasis of liver cancer and liver cancer. And down-regulate isogenic functions. Pathway enrichment analysis of related genes revealed that these genes involved in the regulation of cell cycle and proliferation, energy supply, lysine degradation and other biological pathways, play a regulatory role in the occurrence and development of liver cancer infiltration. In addition, 20 network genes (Hub Gene) such as PLK1, AURKB, CDC20, CDK4, and MCM3 were found through network analysis methods. Afterwards, through the literature search, the key genes were tested for functional infiltration related to hepatocellular carcinoma, and it was discovered and predicted that CDC20, CDCA8, NUP37, and ZWINT genes are associated with the invasive process of liver cancer but the mechanism of action has not yet been explored. Conclusion The use of bioinformatics methods can effectively analyze the genes involved in hepatocellular carcinoma invasion, and can explore its pathogenesis from the molecular level system, providing some valuable information for clinical diagnosis and treatment and follow-up experiments.