综合生物信息学分析鉴定乙型肝炎病毒相关肝细胞癌中异常甲基化修饰的差异表达基因

doi:10.6040/j.issn.1671-7554.0.2023.0468

摘要/Abstract

摘要： 目的探讨与乙型肝炎病毒(HBV)相关肝细胞癌(HCC)发生发展相关的异常甲基化修饰的差异表达基因及分子机制,以期望用于肝癌的早期诊断。方法从公共基因表达数据库(GEO)中下载表达谱芯片GSE121248、GSE107170和DNA甲基化芯片GSE136319,采用R语言筛选HBV相关HCC中癌组织和癌旁组织间差异表达基因(DEGs)和差异甲基化基因(DMGs),并绘制可视化火山图。对甲基化差异表达基因(MDEGs)进行基因本体论(GO)和京都基因和基因组百科全书(KEGG)富集分析,构建蛋白质相互作用(PPI)网络,并使用Cytoscape软件进行分子复合物检测(MCODE)分析和利用cytoHubba插件筛选关键基因。通过癌症基因组图谱(TCGA)数据库验证关键基因的mRNA表达水平,并采用皮尔逊相关系数来评估关键基因在HCC中甲基化和基因表达之间的关系。使用HPA数据库、Cox比例风险回归模型、Kaplan Meier-plotter数据库和ROC分析对关键基因进行蛋白表达、生存分析验证以及预测准确率效能;并分析关键基因的表达与临床指标(肿瘤大小、病理分期)之间的相关性。结果从GSE121248和GSE107170数据集中分别筛选出921个和1 172个DEGs,其中下调表达基因分别为570个和714个,上调表达基因分别为351个和458个;DNA甲基化芯片GSE136319数据进行差异分析后,有7 952个高甲基化基因,2 630个低甲基化基因。综合分析DEGs和DMGs,共得到33个低甲基化修饰下表达上调的基因,和158个高甲基化修饰下表达下调的基因。GO富集分析表明,异常甲基化修饰的差异表达基因主要参与羧酸分解代谢、有机酸分解代谢和血红素结合等过程;KEGG通路主要为化学致癌DNA加合物、补体和凝血系统和PPAR信号通路等。STRING和 Cytoscape软件筛选出12个与甲基化表达相关的关键基因,包括FTCD、HRG、C8A、FOXM1、FGA、KLKB1、MBL2、FETUB、TTK、AURKA、PRC1和MAD2L1;经临床样本数据验证,FTCD、HRG、C8A、FOXM1、AURKA、PRC1、TTK和MAD2L1这8个基因在HBV相关HCC患者中差异表达,且与患者预后不良有关;FTCD、HRG、FOXM1、TTK、AURKA、PRC1和MAD2L1的表达水平与肿瘤大小和病理分期相关。结论 FTCD、HRG、C8A、FOXM1、TTK、AURKA、PRC1和MAD2L1在HBV相关HCC的发病过程中可能起着重要的作用,有可能作为HBV相关HCC的潜在诊断标志物及治疗靶点。

关键词: 乙型肝炎病毒, 肝细胞癌, DNA甲基化, 生物标志物, 生物信息学分析

Abstract: Objective To explore the differentially expressed genes(DEGs)and molecular mechanism of abnormal methylation modification associated with the development of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC)for the early diagnosis of this disease. Methods After the expression profile chips GSE121248, GSE107170 and DNA methylation chip GSE136319 were downloaded from the Gene Expression Database(GEO), the DEGs and differentially methylated genes(DMGs)between HBV-associated HCC tissues and adjacent tissues were screened with R language, and the visual volcano map was drawn. Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis of the methylated-differentially expressed genes(MDEGs)were performed to construct protein-protein interaction(PPI)networks. The molecular complex detection(MCODE)was conducted with Cytoscap, and key genes were screened with cytoHubba plugin. The mRNA expression levels of key genes were verified with the Cancer Genome Atlas(TCGA). The relationship between methylation and gene expression of key genes in HCC was determined with Pearson correlation coefficient. HPA database, Cox proportional hazard regression model, Kaplan Meier-plotter database and receiver operating characteristic(ROC)curve were used to verify the protein expressions of key genes, survival analysis and prediction accuracy. The correlation between the expressions of key genes and clinical indicators(tumor size, pathological stage)were analyzed. Results A total of 921 and 1,172 DEGs were screened from the GSE121248 and GSE107170 datasets, respectively, with 570 and 714 down-regulated and 351 and 458 upregulated genes, respectively. After differential analysis of GSE136319 data, 7 952 genes were hyptrmethylated and 2 630 genes were hypomethylated. A comprehensive analysis of DEGs and DMGs yielded 33 genes upregulated under hypomethylation modification and 158 genes downregulated under hypermethylation modification. GO enrichment analysis showed that the DEGs with abnormal methylation modification were mainly involved in organic acid catabolic process, carboxylic acid catabolic process and heme binding; KEGG pathways were mainly involved in chemical carcinogenesis, complements, coagulation cascades and PPAR signaling pathway. STRING and Cytoscape screened out 12 key genes related to methylation, including FTCD, HRG, C8A, FOXM1, FGA, KLKB1, MBL2, FETUB, TTK, AURKA, PRC1and MAD2L1. After clinical verification, FTCD, HRG, C8A, FOXM1, AURKA, PRC1, TTK and MAD2L1 were confirmed to be differentially expressed in HBV-related HCC and were associated with poor prognosis. The expression levels of FTCD, HRG, FOXM1, TTK, AURKA, PRC1 and MAD2L1 were correlated with tumor size and pathological stage. Conclusion FTCD, HRG, C8A, FOXM1, TTK, AURKA, PRC1 and MAD2L1 may play important roles in the pathogenesis of HBV-related HCC, which may serve as potential diagnostic markers and therapeutic targets.

Key words: Hepatitis B virus, Hepatocellular carcinoma, DNA methylation, Biomarker, Bioinformatics analysis

中图分类号:

R735.7

陈映均,刘同刚. 综合生物信息学分析鉴定乙型肝炎病毒相关肝细胞癌中异常甲基化修饰的差异表达基因[J]. 山东大学学报 (医学版), 2023, 61(9): 101-117.

CHEN Yingjun, LIU Tonggang. Comprehensive bioinformatics analysis to identify differentially expressed genes for aberrant methylation modification in HBV-associated HCC[J]. Journal of Shandong University (Health Sciences), 2023, 61(9): 101-117.

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