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
Year: 2026
Type: article
Abstract: Hepatocellular carcinomas (HCCs) ranks as the most commonly seen and deadly tumor in the world, whose pathogenesis has a close correlation with T cell exhaustion and metabolic reprogramming, which are two critical yet underexplored mechanisms and can profoundly shape the tumor immune microenvironment (TIME) to drive disease progression. This study was designed for constructing a prognosis risk model for HCCs and elucidating its correlations with immune infiltration and drug sensitivity via combined use of these two biological axes. An integrated bioinformatics analysis was performed by leveraging 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 out. Thereafter, the protein-protein interaction (PPI) network analyses and Cox regression model analyses were conducted for identifying five core genes as follows: EZH2, FOXO1, SMARCA2, KPNA2, and SLC2A1.According to the calculated risk scores, HCC patients in the TCGA-LIHC training set were assigned into two groups respectively with high and low risks, which indicated an obvious difference in overall survival (OS) (P<0.0001). This model demonstrated a good performance in predicting one-and three-year OS, with an area under the curve (AUC) of greater than 0.7, which was further confirmed by external validation.Furthermore, the risk scores had correlations with distinct immune cell infiltration patterns and different sensitivities to anticancer drugs, and the low-risk group displayed an enhanced immune activity and greater drug sensitivity.To sum up, the present study has constructed a creative five-gene prognostic model involving both T cell exhaustion and metabolic reprogramming, which can be used as a reliable prognosis biomarker, and guide personalized therapy. These findings offer new and deeper insights into synergistic effects of metabolic alterations and immune escape on HCC progression.
Source: Scientific Reports
Authors: Shaogang Wang, Ying Chen, Yu Mao, Zhijian Chen, Xueqin Zhang, Tao Zhang
Institution: Nantong University
Language: English
Subfield: Hepatology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7165114036