ArticleFrontiers in immunology2022
Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Biomarker-Based Precision Prediction of Immunotherapy Response in Hepatocellular Carcinoma.Diagnostics (Basel, Switzerland) · 2025Article
- Molecular biomarkers of sintilimab plus lenvatinib in hepatitis-B-virus-associated hepatocellular carcinoma.World journal of hepatology · 2025Article
- Long non-coding RNA-based single and combination independent prognostic biomarkers for hepatocellular carcinoma.Discover oncology · 2025Review
- Liver-specific lncRNAs associated with liver cancers.FEBS open bio · 2025Review
- A new paradigm for cancer immunotherapy: targeting immunogenic cell death-related noncoding RNA.Frontiers in immunology · 2024Review
- A novel prognostic signature based on immunogenic cell death score predicts outcomes and response to transcatheter arterial chemoembolization and immunotherapy in hepatocellular carcinoma.Journal of cancer research and clinical oncology · 2023Article
- Immune cell death-related lncRNA signature as a predictive factor of clinical outcomes and immune checkpoints in gastric cancer.Frontiers in pharmacology · 2023Article
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6 authors.
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Abstract
Background: Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes. Methods: Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups. Result: A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, Conclusion: Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.
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