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中国肝细胞癌相关候选基因和通路的生物信息学分析:基于公共数据库的研究。

Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.

机构信息

School of Graduates, Tianjin Medical University, Tianjin, China.

Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China.

出版信息

Pathol Oncol Res. 2021 Mar 26;27:588532. doi: 10.3389/pore.2021.588532. eCollection 2021.

Abstract

Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China. In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes' protein expression levels. A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were , , , , , , , , and . The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC. This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

摘要

肝细胞癌(HCC)是全球消化系统中一种侵袭性很强的恶性肿瘤。在中国,慢性乙型肝炎病毒(HBV)感染和黄曲霉毒素暴露是 HCC 的主要病因,而丙型肝炎病毒(HCV)感染和饮酒可能是其他国家的主要危险因素。因此,认识中国 HCC 的潜在分子机制是一个亟待解决的问题。在这项研究中,我们分析了来自基因表达综合数据库(GEO)的微阵列数据集(GSE84005、GSE84402、GSE101685 和 GSE115018),通过 R 软件获得共同的差异表达基因(DEGs)。此外,还通过数据库注释、可视化和综合发现(DAVID)进行基因本体论(GO)功能注释和京都基因与基因组百科全书(KEGG)通路分析。进一步构建了蛋白质-蛋白质相互作用(PPI)网络,并分别使用 Search Tool for the Retrieval of Interacting Genes(STRING)和 Cytoscape 识别关键基因。利用基因表达谱交互分析(GEPIA)验证了关键基因,在 TCGA HCC 数据集上分别使用 UALCAN 和 Kaplan-Meier Plotter 在线数据库进行了验证。此外,还使用人类蛋白质图谱(HPA)数据库验证了候选基因的蛋白质表达水平。筛选出 293 个共同的 DEGs,包括 103 个上调基因和 190 个下调基因。GO 分析表明,共同的 DEGs 主要参与氧化还原过程、细胞质和蛋白质结合。KEGG 通路富集分析表明,共同的 DEGs 主要富集在代谢途径、补体和凝血级联、细胞周期、p53 信号通路和色氨酸代谢中。在 PPI 网络中,使用分子复合物检测(MCODE)插件检测到三个得分较高的子网。鉴定出的前 10 个关键基因是、、、、、、、和。其他公共数据库证实,上述基因的高表达与 HCC 患者的整体生存率降低有关。本研究主要鉴定了中国 HCC 潜在机制中涉及的候选基因和通路,这有望为中国 HCC 的诊断和治疗提供新的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d33c/8262246/3b503fecf9f5/pore-27-588532-g001.jpg

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