基于生物信息学方法筛选肝细胞癌核心生物标志物及预后关联性分析

Bioinformatics analysis and prognosis correlation assessment of liver cancer associated core biomarkers

目的利用生物信息学分析技术筛选和鉴定参与肝细胞癌(HCC)进展的核心基因,并评价其在HCC发展及预后中的潜在价值。方法从GEO数据库筛选出HCC基因数据集GSE101685、GSE84402和GSE46408,利用GEO2R对差异表达基因(DEGs)进行分析。采用DAVID数据库构建基因功能注释和通路富集分析。利用STRING数据库构建蛋白质互作网络(PPI)图,并用Cytoscape进行可视化分析,筛选出关键模块并获得核心基因。使用cBioPortal数据库进行生存分析。通过ONCOMINE数据库分析核心基因与HCC进展的关系。结果在3个基因数据集中共筛选到261个DEGs,其中上调基因124个,下调基因137个。KEGG分析结果表明,DEGs主要参与细胞周期、DNA复制、视黄醇代谢等通路。PPI分析鉴定出10个核心基因,其中OIP5、HGFAC、FLVCR1与HCC分级、卫星结节和血管浸润有关,FLVCR1与患者生存情况有关。结论该研究成功筛选出与HCC相关的DEGs和核心基因,其中OIP5、HGFAC、FLVCR1有望成为HCC诊疗和预后的生物标志物。

Objective To identify the core genes involved in hepatocellular carcinoma(HCC)by bioinformatics analysis,and to evaluate their potential value in the development and prognosis of HCC.Methods HCC gene datasets GSE101685,GSE84402 and GSE46408 were screened from GEO database,and the differentially expressed genes(DEGs)were analyzed by GEO2R.DAVID database was used to construct functional annotation and pathway enrichment analysis of DEGs.Protein-protein interaction(PPI)network was constructed by STRING database and visualized by Cytoscape to screen out the key modules and obtain the core genes.The cBioPortal database was used to survival analysis of the core differentially expressed genes in HCC tissues and para-carcinoma tissues.The relationship between the core genes and HCC progression was analyzed by ONCOMINE database.Results A total of 261 DEGs were screened from three gene datasets including 124 up-regulated genes and 137 down-regulated genes.KEGG analysis showed that most DEGs were mainly involved in cell cycle,DNA replication,retinol metabolism pathways.Ten hub genes were identified by PPI analysis,among which OIP5,HGFAC and FLVCR1 were associated with HCC grade,satellite nodule and vascular invasion,and FLVCR1 was significantly associated with patient survival situation.Conclusion This study successfully screened the DEGs and core genes related to HCC,among which OIP5,HGFAC and FLVCR1 are expected to be biomarkers for the diagnosis and prognosis of HCC.