Research On Bioinformatics Mining Prognostic Markers Of Hepatocellular Carcinoma And Potential Cancer-promoting Mechanisms

1.Purpose:Hepatic carcinoma is the 6th most usual cancer across the whole world and the number of deaths is fourth.In China,the disease rate of hepatic carcinoma ranks fourth,and the number of patients who died of hepatic carcinoma ranks second in China.This is all caused by its very high degree of malignancy.It is enough to see that hepatic carcinoma has great harm to the national health level.In the past few decades,whole-genome molecular analysis has played a key role in the rapid detection of differentially expressed genes involved in tumorigenesis and development,and has been proven to be a reliable technique for identifying core genes.In this research,our goal is to find out the molecular biological markers related to the occurrence and development of hepatic carcinoma through bio informatics analysis,and discover a certain molecular mechanism for the targeting treatment of hepatic carcinoma in the future.2.Experimental methodThe first step is to collect and download mRNA chips GSE14520,GSE29721,GSE84402 in NCBI's GEO gene expression database,and use R language to neatly process the data and identify differentially expressed genes(DEGs)between liver cancer tissues and adjacent tissues.The expression of the DEGs in three data sets are depicted by the volcano map,and the Venn map are used to take the intersection of the three data sets.In the second step,the DEGs obtained by the intersection of R language are used for GO analysis and KEGG analysis.PPI between DEGs are establish through the STRING database and visualized through the software Cytoscape.At the same time,we use the software plug-in CytoHubba to perform module analysis on the PPI network to screen out key candidate genes.Then we use survExpress to analyze the key candidate genes online and use GEPIA to analyze the expression of these key genes online.The ualcan database was used to analyze the methylation expression of key genes.In the cell function experiment,the key gene CDK1 was knocked down by siRNA,and the cell function was verified by CCK8 experiment.3.ResultsAfter the intersection analysis for the filtered data of the three datasets GSE 14520,GSE29721 and GSE84402,we get the intersection DEGs103.The GO biological function analysis and KEGG pathway enrichment analysis were used on 103 overlapping genes through the ClusterProfiler package of the R language.GO biological function enrichment analysis found that DEGs are mainly involved in coenzyme binding,amide binding,etc.;KEGG pathway enrichment analysis found that DEGs are mainly Participate in fluid shear stress and atherosclerosis,multiple idiopathic hemorrhagic sarcoma-related herpes virus infection,TNF signaling pathway,hepatitis B related signaling pathways,etc..Through analyzing the PPI network,10 key genes(CCNB2,AURKA,CDK1,UBE2C,BUB1B,TOP2A,RACGAP1,NUSAP1,ASPM,PRC1)closely related to liver cancer survival were identified Through the GEPIA database,we use the Kaplan-Meier diagram to study the patients'prognosis with hepatocellular carcinoma,evaluate the expression of 10 core genes and the overall survival(OS)and disease-free survival(Disease free survival,DFS)in the clinical data of hepatocellular carcinoma patients.In the GEPIA database,the prognostic analysis of 10 core genes was carried out,and it was found that in terms of disease-free survival rate,all 10 genes were statistically significant,and high gene expression was associated with poor disease-free survival,and low genes expression is correlated with better survival.In terms of overall survival rate,the 8 genes show statistical significance,namely AURKA,CDK1,BUB1B,TOP2A,RACGAPI,NUSAP1,ASPM and PRC1,and show that high gene expression is correlated with poor overall survival,while low gene expression is correlated with better overall survival.Gene Expression Profiling Interactive Analysis(GEPIA)database was used to analyze the expression differences of ten key genes in hepatocellular carcinoma tissues and adjacent tissues.The expression of CCNB2,AURKA,CDK1,UBE2C,BUB1B,TOP2A,RACGAP1,NUSAP1,ASPM and PRC1 in HCC patients was higher than that in the paracancerous tissues of HCC patients,and all of them were statistically significant.The methylation levels of ten key genes in hepatocellular carcinoma were studied by ualcan database.It was found that CCNB2,CDK1,PRC1,TOP2A and UBE2C showed low expression in HCC tissues and high expression in paracancerous tissues.The five genes may regulate the differential expression of genes through the differential expression of methylation level in HCC.CCK8 assay showed that the proliferation ability of hepatocellular carcinoma cell lines Hccl-M3 and Hep3B decreased significantly after CDK1 knockout by siRNA.4.ConclusionsIn this study,the characteristic genes identified by mRNA chip analysis can predict the prognosis of liver cancer and guide the treatment targets of liver cancer.