ArticleFrontiers in oncology2022
Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Article
- Prognostic model construction and immune microenvironment analysis of pyroptosis-related genes in hepatocellular carcinoma based on single-cell RNA sequencing.Frontiers in immunology · 2025Article
- Characteristics of Oxidative Phosphorylation-Related Subtypes and Construction of a Prognostic Signature in Ovarian Cancer.Current gene therapy · 2025Article
- Prognostic Prediction and Immune Microenvironment Characterization in Uveal Melanoma: A Novel Mitochondrial Metabolism-Related Gene Signature.ACS omega · 2024Article
- Article
- Overview of the immunological mechanisms in hepatitis B virus reactivation: Implications for disease progression and management strategies.World journal of gastroenterology · 2024Review
- Re-Shaping the Pancreatic Cancer Tumor Microenvironment: A New Role for the Metastasis Suppressor NDRG1.Cancers · 2023Review
- An immune and epigenetics-related scoring model and drug candidate prediction for hepatic carcinogenesis via dynamic network biomarker analysis and connectivity mapping.Computational and structural biotechnology journal · 2023Article
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: An increasing number of innovations have been discovered for treating hepatocellular carcinoma (HCC or commonly called HCC) therapy, Ferroptosis and mitochondrial metabolism are essential mechanisms of cell death. These pathways may act as functional molecular biomarkers that could have important clinical significance for determining individual differences and the prognosis of HCC. The aim of this study was to construct a stable and reliable comprehensive model of genetic features and clinical factors associated with HCC prognosis. Methods: In this study, we used RNA-sequencing (fragments per kilobase of exon model per million reads mapped value) data from the Cancer Genome Atlas (TCGA) database to establish a prognostic model. We enrolled 104 patients for further validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses (KEGG) analysis were used for the functional study of differentially expressed genes. Pan-cancer analysis was performed to evaluate the function of the Differentially Expressed Genes (DEGs). Thirteen genes were identified by univariate and least absolute contraction and selection operation (LASSO) Cox regression analysis. The prognostic model was visualized using a nomogram. Results: We found that eight genes, namely EZH2, GRPEL2, PIGU, PPM1G, SF3B4, TUBG1, TXNRD1 and NDRG1, were hub genes for HCC and differentially expressed in most types of cancer. EZH2, GRPEL2 and NDRG1 may indicate a poor prognosis of HCC as verified by tissue samples. Furthermore, a gene set variation analysis algorithm was created to analyze the relationship between these eight genes and oxidative phosphorylation, mitophagy, and FeS-containing proteins, and it showed that ferroptosis might affect inflammatory-related pathways in HCC. Conclusion: EZH2, GRPEL2, NDRG1, and the clinical factor of tumor size, were included in a nomogram for visualizing a prognostic model of HCC. This nomogram based on a functional study and verification by clinical samples, shows a reliable performance of patients with HCC.
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