关键词: 肝细胞癌, 加权基因共表达网络分析, 基因集富集分析, 癌发生机制

Abstract: Objective This study was conducted to explore the functional enrichment pathways and key genes in hepatocarcinogenesis. Methods We downloaded liver transcriptome data from the Gene Expression Database (GEO) at different stages of hepatitis B infection to hepatocellular carcinoma occurrence. Genes were categorized into different modules by weighted gene co-expression network analysis (WGCNA), and genes in different modules were enriched and analyzed. Important gene levels were further validated by GEO dataset. Results A total of 6145 differential genes were involved in the construction of WGCNA, which categorized genes into nine modules. The evolutionary trajectory from early liver lesions to tumorigenesis was further analyzed, e.g., a linear activation of pathways related to cell proliferation, DNA damage repair, and cellular senescence during the process from normal tissues to oncogenesis; a gradual suppression of pathways related to liver function, such as lipid metabolism and coagulation was found with disease progression; and activation of immune-related pathways was also revealed during the period of chronic inflammation prior to tumors, with a gradual convergence to an inhibitory state in the later stage; Three important senescence-related genes, e.g., CCNA2, UBE2C and ANAPC1, were identified, and the levels of the 3 genes were validated in an external dataset. Our further analysis demonstrated that the levels of the 3 genes were strongly associated with poor prognosis of patients with hepatocellular carcinoma. Conclusion By through bioinformatics analysis, we identify potential pathways and important genes involved in hepatocarcinogenesis, which might provide potential targets for diagnosis and therapeutic intervention in the future.

Key words: Hepatoma, Weighted gene co-expression network analysis, Gene set enrichment analysis, Tumorigenesis