摘要
目的探讨肝细胞肝癌相关基因及潜在的可能致病机制,并筛选判断预后的分子标志物。方法在GEO数据库中下载数据集GSE76297,并挑选其中肝细胞肝癌病例。用R语言统计分析差异表达基因(DEGs)并构建其蛋白互作网络(PPI)导入STRING数据库。使用Cytoscape软件对DEGs进行模块分析,并对这些模块进行功能途径富集分析。使用CytoHubba中的12种算法计算出现频率最高的核心基因。在TCGA上验证核心基因对肝细胞肝癌患者总生存期(OS)的预测价值。进一步采用qPCR和蛋白质印迹法分别检测肝细胞肝癌组织和正常肝组织样本差异表达的基因定量水平。结果 R语言统计分析得到总共752个DEGs,包括247个上调基因及505个下调基因,功能富集分析主要有肿瘤通路和肿瘤转录失调等。Cytoscape分析得到包括356个点和2 697个连接的PPI网络,并得到两个具有显著意义的模块,功能富集分析主要在M期和外源性药物分解过程等方面。出现频率最高的核心基因分别为TOP2A、ACACA、CDK1和FOXM1,OS分析提示其对肝细胞肝癌患者的预后均具有显著预测价值。qPCR和蛋白质印迹法定量分析发现,肝细胞肝癌组织中TOP2A、ACACA、CDK1、FOXM1表达水平均显著高于正常肝组织,P<0.05。结论 TOP2A、ACACA、CDK1和FOXM1可以作为肝细胞肝癌患者生存预后的潜在生物分子标记物。
Objective To find disease-associated genes and potential mechanisms in hepatocellular carcinoma.Methods The gene expression profiles of GSE76297 were downloaded from the Gene Expression Omnibus database and the hepatocellular carcinoma samples were selected.Differentially expressed genes(DEGs)were obtained with packages in R language and protein-protein interaction(PPI)network of the DEGs were constructed in STRING database.Subsequently,module analysis of the PPI network was performed in Cytoscape and functions and pathways of subnetwork were studied.We used 12 algorithms in cytoHubba plugin to calculate the hub genes that had the highest frequency.OS analysis was performed by using LIHC samples from the TCGA dataset.Quantitative analysis of differentially expressed genes in hepatocellular carcinoma(HCC)tumor tissue and normal liver tissue was performed by qPCR and Western blot.Results Total 752 DEGs were obtained,including of 247 up-regulated genes and 505 down-regulated genes,which were mainly enriched in the terms related to pathways in cancer,misregulation transcriptional in cancer and so on.A PPI network was constructed,consisted of 356 nodes and 2597 edges.Two significant modules were detected from the PPI network,and the enriched functions included M phase,exogenous drug catabolic process and so on.High expression of the four genes was associated with poor OS of patients in LIHC,including TOP2A,ACACA,CDK1,FOXM1.Quantitative analysis of qPCR and Western blot showed that TOP2 A,ACACA,CDK1 and FOXM1 in hepatocellular carcinoma tissue were significantly higher than those in normal liver tissue(P<0.05).Conclusion It is proposed that TOP2 A,ACACA,CDK1,FOXM1 may be further explored as potential biomarkers to aid liver cancer diagnosis and treatment.
作者
卓恩清
吴依霖
蔡长青
刘文哲
李昆松
赵文珍
ZHUO En-qing;WU Yi-lin;CAI Chang-qing;LIU Wen-zhe;LI Kun-song;ZHAO Wen-zhen(Department of Second Oncology,Guangdong Second Provincial General Hospital,Guangzhou 510317,China;Department of Clinical Lab,Nan fang Hospital,Southern Medical University,Guangzhou 510317,China)
出处
《中华肿瘤防治杂志》
CAS
北大核心
2021年第14期1093-1098,共6页
Chinese Journal of Cancer Prevention and Treatment
基金
广东省医学科学技术研究基金项目(A2018526)。
关键词
肝细胞肝癌
蛋白互作网络
预后生物分子标志物
功能富集分析
hepatocellular carcinoma
interaction network
prognostic biomarkers
function and pathway analysis
