ArticleTranslational cancer research2025
A gene signature associated with cellular senescence serves as an important prognostic indicator in hepatocellular carcinoma.
Article in Translational cancer research, 2025. 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.
- Environmental Carcinogenesis as a Stochastic Evolutionary Failure of Senescence-Control Systems.Cells · 2026Review
- A senescence-based machine learning model prognosticates and personalizes therapy in cervical cancer.Translational cancer research · 2026Article
- VDAC2: an emerging pivotal and multifaceted regulator in tumor biology.Apoptosis : an international journal on programmed cell death · 2026Review
- VDAC1 as prognostic marker and therapeutic target in lung adenocarcinoma: a study integrating bioinformatics and experimental validation.Discover oncology · 2025Article
- Prognostic value of a simplified score based on routine parameters in patients with hepatocellular carcinoma treated with systemic therapies: a retrospective cohort study.Journal of gastrointestinal oncology · 2025Article
- Identification of basement membrane-based prognostic signature and potential therapeutic drugs in hepatocellular carcinoma.Translational cancer research · 2025Article
- Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma.PloS one · 2025Article
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Abstract
Background: Hepatocellular carcinoma (HCC) is a lethal tumor. Predicting the prognosis of HCC remains challenging. Cellular senescence, which is one of the hallmarks of cancer, and its related prognostic-gene signature can provide critical information for clinical decision making. Our objective was to investigate the role of cellular senescence in HCC. Methods: The RNA sequencing data and clinical information of HCC patients from The Cancer Genome Atlas (TCGA) database were obtained. The HCC subtypes and a senescence score model were established to predict the prognosis of HCC. Results: In this study, patients from TCGA-HCC dataset were stratified into low- and high-risk groups based on cellular senescence-related genes. The analysis of the various subtypes revealed that the distribution of Cluster 1 (C1) was significantly correlated with numerous factors, including age, sex, pathological T stage, tumor node metastasis (TNM) classification, and grade staging. Further, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that the upregulated genes in the high-risk C1 group were primarily engaged in pathways related to the cell cycle, DNA replication, cellular senescence, extracellular matrix (ECM)-receptor interactions, and the mechanisms of mismatch repair. Conversely, the 90 downregulated genes were mainly associated with metabolic pathways, chemical carcinogenesis involving DNA adducts, complement and coagulation cascades, and the peroxisome proliferator-activated receptor (PPAR) signaling pathway. The resultant boxplots revealed significant differences in the populations of immune cells, such as B cells, endothelial cells, natural killer (NK) cells, macrophages, cluster of differentiation (CD)4+ T cells, and CD8+ T cells, in the C1 HCC samples compared to the C2 HCC samples. Additionally, the prognostic outcomes of the HCC patients were predicted using a cellular senescence-related gene model that included Conclusions: This study established a prognostic model of HCC based on cellular senescence-related gene expression. Our findings may provide insights that can be used to develop novel potential targeted therapies.
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