Construction of a five-gene prognostic model involving T cell exhaustion and metabolic reprogramming for predicting hepatocellular carcinoma risk using LASSO: insights into immune infiltration and drug sensitivity

Hepatocellular carcinoma (HCC) ranks as one of the most common and deadly malignancies in the world. Its pathogenesis is closely correlated with T cell exhaustion and metabolic reprogramming, these two critical yet underexplored mechanisms can profoundly shape the tumor immune microenvironment (TIME) and drive disease progression. This study was designed for constructing a prognosis risk model for HCC and elucidating its correlations with immune infiltration and drug sensitivity by integrating these two biological processes. An integrated bioinformatics analysis was performed by using data from two datasets such as Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) and Gene Expression Omnibus (GEO, including GSE76427 and GSE10186). Fifty seven overlapping genes associated with both T cell exhaustion and metabolic reprogramming were screened. Thereafter, the protein–protein interaction (PPI) network analyses and Cox regression model analyses were conducted to identify the following five core genes: EZH2, FOXO1, SMARCA2, KPNA2, and SLC2A1. According to the calculated risk scores, HCC patients in the TCGA-LIHC training set were stratified into high- and low-risk groups, which indicated an obvious difference in overall survival (OS) ( P < 0.0001). This model demonstrated good performance in predicting one- and three-year OS, with an area under the curve (AUC) exceeding 0.7, this finding was further confirmed by external validation. Furthermore, the risk scores were correlated with distinct immune cell infiltration patterns and varied sensitivities to anticancer drugs, and the low-risk group exhibited enhanced immune activity and greater drug sensitivity. In summary, this study has constructed a five-gene model that provides computational evidence for prognostic stratification of HCC from the perspective of the intersection between cell exhaustion and metabolic reprogramming. However, its clinical application still requires experimental validation in independent clinical cohorts. These findings offer novel and deeper insights into synergistic effects of metabolic alterations and immune escape on HCC progression.