ArticleJournal of hepatocellular carcinoma2024
Construction of a Prognostic Model for Hepatocellular Carcinoma Based on Macrophage Polarization-Related Genes.
Article in Journal of hepatocellular carcinoma, 2024. 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.
- Spatiotemporal heterogeneity of neutrophil extracellular traps in hepatocellular carcinoma microenvironment and targeted therapy progress.Journal of translational medicine · 2026Review
- ZG16B: A key regulator of tumor progression and immune microenvironment modulation in cancer (Review).International journal of molecular medicine · 2026Review
- Construction of a macrophage-related prognostic signature and assessment of immune checkpoint inhibitor efficacy of HCC.Scientific reports · 2025Article
- Pilot study using a discrete mathematical approach for topological analysis and ssGSEA of gene expression in autosomal recessive polycystic kidney disease.Scientific reports · 2025Article
- Machine learning approach identifies inflammatory gene signature for predicting survival outcomes in hepatocellular carcinoma.Scientific reports · 2024Article
- Macrophage Polarization in the Tumor Microenvironment of Hepatocellular Carcinoma: From Mechanistic Insights to Translational Therapies.Cancer control : journal of the Moffitt Cancer CenterReview
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Authors and funding
4 authors.
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Abstract
Background: The progression of hepatocellular carcinoma (HCC) is related to macrophage polarization (MP). Our aim was to identify genes associated with MP in HCC patients and develop a prognostic model based on these genes. Results: We successfully developed a prognostic model consisting of six MP-related genes (SCN4A, EBF3, ADGRB2, HOXD9, CLEC1B, and MSC) to calculate the risk score for each patient. Patients were then classified into high- and low-risk groups based on their median risk score. The performance of the MP-related prognostic model was evaluated using Kaplan-Meier and ROC curves, which yielded favorable results. Additionally, the nomogram demonstrated good clinical effectiveness and displayed consistent survival predictions with actual observations. Gene Set Enrichment Analysis (GSEA) revealed enrichment of pathways related to KRAS signaling downregulation, the G2M checkpoint, and E2F targets in the high-risk group. Conversely, pathways associated with fatty acid metabolism, xenobiotic metabolism, bile acid metabolism, and adipogenesis were enriched in the low-risk group. The risk score positively correlated with the number of invasion-related genes. Immune checkpoint expression differed significantly between the two groups. Patients in the high-risk group exhibited increased sensitivity to mitomycin C, cisplatin, gemcitabine, rapamycin, and paclitaxel, while those in the low-risk group showed heightened sensitivity to doxorubicin. These findings suggest that the high-risk group may have more invasive HCC with greater susceptibility to specific drugs. IHC staining revealed higher expression levels of SCN4A in HCC tissues. Furthermore, experiments conducted on HepG2 cells demonstrated that supernatants from cells with reduced SCN4A expression promoted M2 macrophage polarization marker, CD163 in THP-1 cells. Reduced SCN4A expression induced HCC-related genes, while increased SCN4A expression reduced their expression in HepG2 cells. Conclusion: The MP-related prognostic model comprising six MPRGs can effectively predict HCC prognosis, infer invasiveness, and guide drug therapy. SCN4A is identified as a suppressor gene in HCC.
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