Bioinformatics Analysis Of Key Gene For Liver Cancer Based On GEO And TCGA Databases

Liver cancer is a common malignant tumor.Its occurrence and development is a complex process involving the abnormal expression and regulation of multiple genes.The application of bioinformatics methods to analyze the genes related to the occurrence and development of liver cancer,and to screen out key genes that have important regulatory roles from them,will contribute to in-depth understanding of the pathogenesis of liver cancer.In this paper,we first screened the key genes of RFC4 and FEN1 in liver cancer based on the GEO database,then analyzed the key genes of liver cancer by bioinformatics methods based on the TCGA database,and verified the expression of key genes through experiments.Finally,we designed and developed a platform for bioinformatics analysis of liver cancer.The main contents are as follows:(1)Discovery of liver cancer key genes of RFC4 and FEN1 based on GEO database:Select the GSE25097,GSE36376,and GSE14520 datasets from the GEO database,common differentially expressed genes were screened through differential expression analysis,and enrichment analysis was conducted on common differentially expressed genes,as well as the construction of protein-protein interaction networks.Based on the MCC algorithm,it was found that ASPM,AURKA,CDC20,FEN1,NUSAP1,RACGAP1,RFC4,and TOP2 A were hub genes associated with the occurrence and development of liver cancer.All eight hub genes were significantly overexpressed in liver cancer,and overexpression were significantly associated with poor prognosis.KEGG enrichment analysis of eight genes revealed that FEN1 and RFC4 were significantly enriched in the DNA replication pathway(P=0.0176).Therefore,RFC4 and FEN1 were key genes in the occurrence and development of liver cancer.(2)Bioinformatics analysis of liver cancer key genes of RFC4 and FEN1 based on TCGA database: m RNA expression analysis showed that RFC4 and FEN1 had significantly abnormal expression in various types of cancer,while RFC4 and FEN1 were significantly overexpressed in liver cancer.Based on protein expression data from the CPTAC dataset and immunohistochemical staining data from the HPA database,it was found that RFC4 and FEN1 proteins were also significantly overexpressed in liver cancer.The survival analysis of liver cancer found that there was a significant difference in the overall survival rate between the high expression group and the low expression group,and high expression may lead to poor prognosis.The ROC curve revealsd that RFC4 and FEN1 had good predictive performance for the diagnosis and prognosis of liver cancer.Correlation analysis of clinical factors also found that there were significant differences in the expression of RFC4 and FEN1 among different races,histological grades,pathological stages,and AFP expression.From the perspective of genetic and epigenetic alteration,it was found that copy gain was significantly correlated with RFC4 and FEN1 overexpression.DNA methylation levels were significantly negatively correlated with RFC4 and FEN1 overexpression.In addition,hsa-mi R-18a-5p was selected as a potential regulatory mi RNA for identifying RFC4 and FEN1.hsa-mi R-18a-5p was significantly upregulated in liver cancer tissue,and its expression was significantly positively correlated with the two genes.High expression of hsa-mi R-18a-5p was associated with poor OS and DFI.The cox regression model composed of RFC4 and FEN1 can also be used for the diagnosis and prognosis prediction of liver cancer.Finally,there was a significant positive correlation between the two gene expression and the expression of various immune lymphocytes and immune checkpoint genes.Therefore,RFC4 and FEN1 were significantly related to the occurrence and development of liver cancer,and they were key genes for liver cancer,which may become new diagnostic and prognostic markers and therapeutic targets for liver cancer.(3)Cell experimental verification of RFC4 and FEN1 expression in liver cancer:real-time quantitative polymerase chain reaction technology found that RFC4 and FEN1 were significantly overexpressed in liver cancer cells.Western blot and laser confocal microscopy were used to observe cell immunofluorescence experiments to verify that RFC4 and FEN1 were significantly overexpressed in liver cancer cells.Therefore,the expression of RFC4 and FEN1 genes and proteins in liver cancer cells were significantly higher than that in normal cells.(4)Design of TCGA-LIHC data online analysis platform based on R-Shiny: The functions of the analysis platform mainly included differential expression analysis of genes,survival analysis,ROC curve plotting,correlation analysis of clinical factors,as well as differential expression analysis of mi RNA,prognosis analysis,correlation analysis of mi RNA expression and gene expression.The use of an analysis platform to replicate previous studies showed consistent results,indicating that the analysis results of platform were accurate.