A novel glutamine metabolism‑related risk model for prognostic prediction of liver hepatocellular carcinoma

Glutamine has emerged as a focus of cancer metabolism research, although its role in liver hepatocellular carcinoma (LIHC) has yet to be fully elucidated. To determine the role of glutamine metabolism in the development of LIHC, the gene expression profiles and the clinical data of patients with LIHC were obtained from The Cancer Genome Atlas database and the International Cancer Genome Consortium website. Consensus clustering was used to identify distinct molecular clusters. Functional en 10.3892/ol.2025.15149 richment analysis between clusters was performed using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, and gene set variation analysis was performed. Least absolute shrinkage and selection operator and multivariate Cox regression analyses were then performed to generate a novel prognostic model. The prognostic, immune, mutational and drug-sensitive characteristics of the model were subsequently evaluated. The clinical proteomic tumor analysis consortium and reverse transcription-quantitative PCR analysis were then used to assess the protein and mRNA expression levels of the modeled genes. In addition, western blot analysis and Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine, Transwell and wound healing assays were performed to further evaluate the role of glutamate-oxaloacetate transaminase 2 (GOT2) in the pathogenesis of LIHC. Data from multiple LIHC cohorts were utilized to identify two distinct clusters of LIHC, each characterized by unique clinical and immunological features associated with different levels of glutamine metabolism-related genes. Numerous functional pathway differences were identified between these clusters, and these were demonstrated to be crucial for the onset and progression of LIHC. For modeling of glutamine metabolism-related features, patients with LIHC were divided into two groups, namely a high- and a low-risk group. Different clusters of patients with LIHC exhibited distinct characteristics in terms of their clinicopathological features, drug-sensitivity and mutations. For example, the high-risk group had a higher mutational load and was associated with a poorer prognosis compared to the low-risk group. Finally, GOT2 protein and mRNA expression levels were significantly lower in LIHC tissues compared to paracancerous tissues, and GOT2 knockdown promoted the malignant phenotype of LIHC. In conclusion, the results of the present study indicate that glutamine metabolism exerts a crucial role in the tumorigenesis and progression of LIHC, and that this is positively associated with poor prognosis. The identified glutamine metabolism-related signature was revealed to have notable accuracy in predicting the prognosis and immune characteristics of patients with LIHC. Moreover, the expression level of GOT2 was downregulated in LIHC, and a low expression of GOT2 was indicative of a poor prognosis for patients with LIHC, suggesting that the expression of GOT2 may be used as a potential therapeutic target.