Background: Hepatocellular Carcinoma (HCC) is one of the most common liver malignancies in the world.With highly invasive biological characteristics and lack of obvious clinical manifestations, hepatocellular Carcinoma usually has a poor prognosis and ranks fourth in cancer mortality. The aetiology and exact molecular mechanism of primary hepatocellular carcinoma are still unclear. This work aims to help identify biomarkers of early HCC diagnosis or prognosis.Results: In this study, Expression data and clinical information of HTSEQ-Counts were downloaded from The Cancer Genome Atlas (TCGA) database, and Gene Expression map GSE121248 was downloaded from Gene Expression Omnibus (GEO). By differentially expressed genes (DEGs) and Weighted Gene coexpression Network Analysis WGCNA searched for modules in the two databases that had the same effect on the biological characteristics of HCC, and extracted the module genes with the highest positive correlation with HCC from two databases, and nally obtained overlapping genes. Then, we performed functional enrichment analysis on the overlapping genes to understand their potential biological functions. The top ten hub genes were screened according to MCC through the String database and Cytoscape software. By survival analysis, high expression of CDK1, CCNA2, CDC20, KIF11, DLGAP5, KIF20A, ASPM, CEP55, TPX2 was associated with poorer overall survival (OS) of HCC patients. The DFS curve was plotted using the online website GEPIA2. Finally, based on the enrichment of these genes in the KEGG pathway, real hub genes were screened out, which were CDK1, CCNA2 and CDC20 respectively.Conclusions: High expression of these three genes was negatively correlated with survival time in HCC, and the expression of CDK1, CCNA2 and CDC20 were signi cantly higher in tumour tissues of HCC patients than in normal liver tissues as veri ed again by the HPA database. All in all, this provides a new feasible target for early and accurate diagnosis of HCC, clinical diagnosis, treatment and prognosis.