Identification of Molecular Subtypes for Hepatocellular Carcinoma Based on Ubiquitin‐Conjugating Enzyme E2 (UBE2)‐Related Genes to Assess Prognosis and Immune Landscape

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent and highly aggressive cancer, characterized by elevated morbidity and mortality. Ubiquitin-conjugating enzyme E2 (UBE2) plays a crucial role in regulating HCC development, although the underlying mechanisms remain poorly understood. METHODS: HCC patient transcriptomic and clinical datasets were sourced from The Cancer Genome Atlas database. Patients were classified into two distinct subtypes using the K-means clustering method. Prognostic genes were identified through univariate and multivariate Cox regression, as well as least absolute shrinkage and selection operator regression. A nomogram was developed to predict patient prognosis, which was subsequently validated using the independent GEO dataset, GSE14520. Extensive model validation was performed to assess its prognostic significance. Immune landscape characterization was conducted using Single Sample Gene Set Enrichment Analysis (ssGSEA), ESTIMATE, and CIBERSORT algorithms. Drug sensitivity was also evaluated to identify potential therapeutic options. RESULTS: Based on the expression profiles of 12 UBE2-associated genes, we classified patients into two subtypes and identified six UBE2-related genes as prognostic biomarkers. The risk score effectively predicted patient outcomes, with high-risk individuals showing reduced survival and the low-risk group characterized by elevated immune cell infiltration and unique immune checkpoint expression patterns. Additionally, potential drugs were identified, and drug sensitivity for HCC was evaluated. CONCLUSION: In this study, we established a prognostic risk model for HCC with strong predictive performance. Risk-based stratification revealed its associations with immune infiltration, immunotherapy response, and drug sensitivity. These findings offer new insights into survival prediction and clinical features in patients with HCC.