Identification Of Key Genes In Hepatocellular Carcinoma By Bioinformatics

Objective: Identification the key genes related to the clinical phenotype of hepatocellular carcinoma,and explore its relationship with hepatocellular carcinoma by bioinformatics methods.Methods: Use the data set in the TCGA database for difference analysis.Use Weighted Gene Co-expression Network Analysis(WGCNA)to analyze differential genes,construct gene co-expression network and determine the key modules related to clinical phenotype.GO analysis and KEGG pathway analysis were performed on key module genes,LASSO regression was performed,and a prognostic risk score formula was established to identify genes related to prognosis.Results:Difference analysis yielded 2548 differential genes.The gene co-expression network includes 4 modules,each of which has similar gene expression.Among them,turquoise module is positively correlated with pathological grading,GO enrichment analysis results are involved in organelle fission,etc.KEGG enrichment analysis results are cell cycle,etc.LASSO regression and prognostic risk scoring formula screened out 4key genes including ANGPT2,CDCA8,SLC7A11 and CYBB.The modular genes and key genes identified in this study are expected to become candidate targets for the prognosis of hepatocellular carcinoma.Conclusion: A total of 1 module and 4 key genes were identified.These key genes may open up new possibilities for the detection and treatment of hepatocellular carcinoma,but the mechanism of the occurrence and development of hepatocellular carcinoma needs further study.