ArticleFrontiers in immunology2023
Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape.
Article in Frontiers in immunology, 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.
- The Molecular Network of Neutrophil Extracellular Traps in Hepatocellular Carcinoma: Biogenesis, Function, and Therapeutic Implications.Molecules (Basel, Switzerland) · 2026Review
- A prognostic lncRNA signature associated with ribonucleotide reductase predicts overall survival and immune landscape in hepatocellular carcinoma.Frontiers in cell and developmental biology · 2026Article
- LncRNAs as behind-the-scenes molecules in cancer progression through regulating tumor-associated innate immune system cells.Molecular biology reports · 2025Review
- Unraveling the oncogenic role of LINC00504 and its interaction with miR-545-3p and ARIHI in hepatocellular carcinoma: novel insights for molecular therapy.Discover oncology · 2025Article
- Neutrophil extracellular traps promote growth of lung adenocarcinoma by mediating the stability of m6A-mediated SLC2A3 mRNA-induced ferroptosis resistance and CD8(+) T cell inhibition.Clinical and translational medicine · 2025Article
- Neutrophil extracellular traps-related lncRNAs prognostic signature for gastric cancer and immune infiltration: potential biomarkers for predicting overall survival and clinical therapy.Discover oncology · 2024Article
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Authors and funding
6 authors.
Funding
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Abstract
Purpose: To investigate the impact of N6-methyladenosine- (m6A) and neutrophil extracellular traps- (NETs) related lncRNAs (MNlncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We collected m6A and NETs-related genes from published studies. We identified the MNlncRNAs by correlation analysis. Cox regression and the least absolute selection operator (LASSO) method were used to select predictive MNlncRNAs. The expressions of predictive MNlncRNAs were detected by cell and tissue experiments. Survival, medication sensitivity, and immunological microenvironment evaluations were used to assess the model's prognostic utility. Finally, we performed cellular experiments to further validate the model's prognostic reliability. Results: We obtained a total of 209 MNlncRNAs. 7 MNlncRNAs comprised the prognostic model, which successfully stratifies HCC patients, with the area under the curve (AUC) ranging from 0.7 to 0.8. Conclusion: The MNlncRNAs-related prognostic model aided in determining HCC prognosis, revealing novel therapeutic options, notably immunotherapy.
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