Abstract: OBJECTIVE To use the bioinformatics method based on data of GEO chip to analyze the development of the molecular markers and prognosis in liver cancer. METHODS Liver cancer chip data was obtained in CEO database. The differentially expressed genes in liver cancer tissues and normal liver tissues were identified by GEO2R; the pathway enrichment of differentially expressed genes were performed by using KEGG and GO. The protein-protein interaction(PPI) network of differentially expressed genes was constructed by STRING database and visualized by Cytoscape. The perform survival analysis of these key genes were analyzed by online tool Kaplan Meier-Plotter. The immunohistochemistry analysis of these key genes were analyzed by The Human Protein Atlas Database. RESULTS A total of 338 differentially expressed genes were identified, including 97 up-regulated genes and 241 down-regulated genes. These up-regulated differentially expressed genes were significantly enriched in mitotic nuclear division, cell division, mitotic sister chromatid segregation, sister chromatid cohesion. These down-regulated differentially expressed genes were significantly enriched in epoxygenase P450 pathway, oxidation-reduction process, exogenous drug catabolic process. The PPI network was constructed a key module by 24 key genes. These key genes were found to be associated with poor survival in patients with liver cancer. Representative images of key differentially expressed genes immunostained were taken. CONCLUSION These key genes are found by this study which contributed to understanding the molecular mechanism of liver cancer, and can be used as a biomarker for the prognosis of liver cancer and a molecular target for the treatment of liver cancer.