Identification and Prognostic Evaluation of Biomarker Genes in Hepatocellular Carcinoma: Focus on EZH2 as a Potential Biomarker and Therapeutic Target

Hepatocellular carcinoma (HCC) ranks among the most prevalent and aggressive cancers globally, characterized by high rates of illness and death. Early diagnosis and effective treatment are hindered by a lack of reliable biomarkers and a comprehensive understanding of its molecular mechanisms. We carried out a bioinformatics analysis in this study, employing the TCGA and GEO databases to identify genes with varying expression levels between HCC and normal liver tissues. The TCGA dataset identified 395 genes that were upregulated and 631 that were downregulated, whereas the GSE45267 dataset found 2,452 upregulated genes and 446 downregulated ones. These DEGs were primarily involved in critical biological processes such as cell cycle regulation, DNA replication, and metabolism. Gene set enrichment analysis (GSEA) indicated that pathways associated with mitotic division and cell cycle progression were enriched with upregulated genes, whereas downregulated genes were linked to immune response and metabolic pathways. Further analysis of gene interaction networks revealed several key hub genes, including EZH2, MCM2, and ALDH2, which were associated with poor and favorable prognosis, respectively. Survival analysis identified EZH2, GINS1, and MCM2 as adverse prognostic markers and ALDH2, ADH4, and PON1 as favorable prognostic markers. A Lasso Cox regression model was developed, incorporating these genes to construct a prognostic risk score, which showed high predictive accuracy for patient survival. These findings offer insights into the molecular landscape of HCC, identify potential diagnostic and prognostic biomarkers, and propose novel therapeutic targets for personalized treatment strategies. Future studies should validate these biomarkers and assess their clinical utility in HCC management.