ArticleFrontiers in immunology2024
Signature of immune-related metabolic genes predicts the prognosis of hepatocellular carcinoma.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A GIMAP family signature for prognostic prediction and immune characterization in hepatocellular carcinoma patients.Discover oncology · 2026Article
- IMP metabolic mechanisms and IMPDH targeting strategies in tumor metabolic reprogramming and therapy (Review).International journal of molecular medicine · 2026Review
- Cross-Species Upregulation ofCurrent issues in molecular biology · 2026Article
- Comparison of stereotactic body radiotherapy following transcatheter arterial chemoembolizationWorld journal of gastrointestinal surgery · 2025Article
- Dissecting the multi-omics landscape of TEAD1 in hepatocellular carcinoma: cycle regulation and metastatic potential.Frontiers in immunology · 2025Article
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6 authors.
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Abstract
Introduction: The majority of liver cancer cases (90%) are attributed to hepatocellular carcinoma (HCC), which exhibits significant heterogeneity and an unfavorable prognosis. Modulating the immune response and metabolic processes play a crucial role in both the prevention and treatment of HCC. However, there is still a lack of comprehensive understanding regarding the immune-related metabolic genes that can accurately reflect the prognosis of HCC. Methods: In order to address this issue, we developed a prognostic prediction model based on immune and metabolic genes. To evaluate the accuracy of our model, we performed survival analyses including Kaplan-Meier (K-M) curve and time-dependent receiver operating characteristic (ROC) curve. Furthermore, we compared the predictive performance of our risk model with existing models. Finally, we validated the accuracy of our risk model using mouse models with Results: By conducting lasso regression analysis, we identified four independent prognostic genes: fatty acid binding protein 6 (FABP6), phosphoribosyl pyrophosphate amidotransferase (PPAT), spermine synthase (SMS), and dihydrodiol dehydrogenase (DHDH). Based on these findings, we constructed a prognostic model. Survival analysis revealed that the high-risk group had significantly lower overall survival (OS) rates. Besides that, the ROC curve demonstrated the effective prognostic capability of our risk model for hepatocellular carcinoma (HCC) patients. Furthermore, through animal experiments, we validated the accuracy of our model by showing a correlation between high-risk scores and poor prognosis in tumor development. Discussion: In conclusion, our prognostic model surpasses those solely based on immune genes or metabolic genes in terms of accuracy. We observed variations in prognosis among different risk groups, accompanied by distinct immune and metabolic characteristics. Therefore, our model provides an original evaluation index for personalized clinical treatment strategies targeting HCC patients.
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