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Life sciences · Journal article
Discover Oncology · September 20, 2026
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Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer and poses significant challenges due to its aggressive nature and poor prognosis. Mitochondrial metabolism is closely related to the onset and progression of tumors, but its value in constructing prognostic models for HCC remains unclear. RNA‑sequencing and clinical data of HCC patients were obtained from TCGA database. Mitochondrial metabolism–related genes (MMRGs) were collected from GeneCards database. Weighted gene co‑expression network analysis (WGCNA) and differential expression analysis were used to identify mitochondrial metabolism-related differentially expressed genes (MRDEGs), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Consensus clustering based on MRDEGs was used to define molecular subtypes. Least absolute shrinkage and selection operator (LASSO) regression was applied to screen key genes and build a prognostic risk model, which was evaluated by Kaplan–Meier analysis and time‑dependent receiver operating characteristic (ROC) curves. A nomogram combining the risk score with clinical variables was constructed and assessed by calibration and decision curve analysis. In vitro experiments were conducted to investigate the role of KPNA2 in Huh7 cells. A total of 40 MRDEGs were identified, which were mainly enriched in pathways involved in cellular respiration, cell cycle regulation and cellular senescence. Based on these genes, HCC patients were divided into two molecular subtypes with significantly distinct overall survival (OS) outcomes. LASSO regression yielded a four‑gene prognostic signature (PPARGC1A, CBX2, KPNA2, ACADS) that effectively stratified patients into high‑ and low‑risk groups, with good predictive accuracy for 1‑, 3‑, and 5‑year OS. The risk score was confirmed as an independent prognostic factor, and a nomogram integrating the signature with age, gender, stage and T stage further improved prognostic prediction with good discrimination and calibration. In vitro, KPNA2 was upregulated in Huh7 cells, and knockdown of KPNA2 markedly suppressed the proliferation and migration of HCC cells. We developed a concise mitochondrial metabolism–related four‑gene prognostic signature and a combined nomogram that provide reliable survival prediction for HCC. These genes, particularly KPNA2, may serve as potential prognostic biomarkers and therapeutic targets, and help guide individualized adjuvant therapy decisions for HCC.