ArticleClinical and experimental medicine2023
Predicting the prognosis of hepatocellular carcinoma based on the interaction between pyroptosis, apoptosis, and necroptosis.
Article in Clinical and experimental medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Exploring the role of PANoptosis related genes in the prognosis of oral squamous cell carcinoma subtypes based on multi-omics analysis.Discover oncology · 2025Article
- Biological and clinical role of TREM2 in liver diseases.Hepatology communications · 2024Review
- TREM2, a critical activator of pyroptosis, mediates the anti‑tumor effects of piceatannol in uveal melanoma cells via caspase 3/GSDME pathwayInternational journal of molecular medicine · 2024Article
- Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.Journal of cellular and molecular medicine · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Multiple programmed cell death pathways (pyroptosis, apoptosis, and necroptosis) are closely related to the progression of hepatocellular carcinoma (HCC). Furthermore, molecular interactions among pyroptotic, apoptotic, and necroptotic components may be new targets for cancer therapy. However, the signature of the genes involved in the interaction between pyroptosis, apoptosis, and necroptosis (PANRGs), and their prognostic value, is still unclear in HCC. In this study, we used HCC clinical and expression data from TCGA and GEO to explore the relationship between PANRGs and HCC. First, we determined the copy number variation incidence of 41 PANRGs genes and explored the prognostic correlation of these genes in HCC. Based on PANRGs, two molecular subgroups of HCC associated with prognosis were identified. We also found significant differences in the overall survival time and the immune infiltration of HCC patients between the two subgroups. Finally, based on the nine PANRGs (CDC25B, EZH2, HMOX1, PLK1, SQSTM1, WEE1, TREM2, MYCN, and FLT3), we constructed a prognostic model using LASSO-Cox regression analysis. The prognostic model could predict OS of HCC patients in TCGA and GEO cohorts with high accuracy. Significant correlations were found between prognosis-related PANRGs and the tumor immune microenvironment (TIME), tumor mutational burden (TMB), and drug sensitivity. In conclusion, we explored the role of PANRGs in HCC and the association of these genes with TIME, TMB, and drug sensitivity.
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Registered trials
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