ArticleCurrent genomics2023
Mitochondrial Lipid Metabolism Genes as Diagnostic and Prognostic Indicators in Hepatocellular Carcinoma.
Article in Current genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- KIF20A suppresses ferroptosis in HCC through HMOX1/SLC7A11/GPX4 signaling pathway.Discover oncology · 2026Article
- Pan-Cancer Landscape of the Novel Oxygen Sensor ADO and Its Potential Role in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- Multimodal analysis reveals potential association of CDH13 with endothelial cells and its overexpression in hepatocellular carcinoma.European journal of medical research · 2025Article
- Glycolysis-related MiRNA signature predicts prognosis, recurrence risk, and therapeutic responses in hepatocellular carcinoma.Scientific reports · 2025Article
- Acid phosphatase type 6 promotes endometrial cancer progression via activating PI3K/AKT pathway.Molecular biology reports · 2025Article
- Emerging roles of metabolic biomarkers in renal cell carcinoma: from molecular mechanisms to clinical implications.Frontiers in cell and developmental biology · 2025Review
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Authors and funding
7 authors.
Funding
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Abstract
Background: Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects the occurrence and progression of HCC. Objective: This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM) genes as diagnostic and independent prognostic biomarkers for HCC. Methods: MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University (GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate the prognostic significance, immune infiltration, and copy number alterations. The validity of the prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC), and GXMU cohorts. Results: The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust predictive value was constructed using the lasso regression algorithm based on TCGA data. The results of the Stepwise regression model showed that the combination of signature and routine clinical parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram was constructed to predict the survival probability of HCC, and the calibration curves demonstrated a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation statuses between the two different risk groups. Conclusion: MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular pathogenesis and providing potential therapeutic strategies for HCC.
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