ArticleCurrent medical science2024
Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients.
Article in Current medical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- TAZ WW Domain-Mediated Regulation of Gluconeogenesis and Tumorigenesis in Hepatocellular Carcinoma through Interaction with the Glucocorticoid Receptor.Endocrinology and metabolism (Seoul, Korea) · 2026Article
- Article
- Identifying metabolism-related genes in liver cancer through weighted gene co-expression network analysis and machine learning.Frontiers in genetics · 2025Article
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12 authors.
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Abstract
objectiveThe activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear.
methodsThe cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored.
resultsA total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes.
conclusionThrough bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.
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