ArticleEuropean journal of medical research2026
A telomere-based prognostic model incorporating E2F1, MYCN, VPS72, CFAP53, OR8A1, and TXNRD1 for hepatocellular carcinoma.
Article in European journal of medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundHepatocellular carcinoma (HCC) is an aggressive malignancy associated with an unfavorable prognosis. Telomeres and telomere-related genes are central to tumorigenesis, but their systematic integration into prognostic modeling for HCC remains insufficiently explored. This study presents a telomere-based prognostic model aimed at improving risk stratification and informing therapeutic decision-making in HCC.
methodsTranscriptomic profiles and clinical data were collected from The Cancer Genome Atlas (369 HCC and 50 normal samples) and Hepatocellular Carcinoma Gene Expression Database (203 cases). A curated panel of 2,093 telomere-related genes was retrieved from TelNet. Hub genes were identified using an integrated strategy combining ssGSEA, WGCNA, and differential expression analysis. A prognostic risk model was established using univariate Cox, LASSO, and multivariate Cox regression analyses, followed by external validation.
resultsWe developed a robust telomere-based prognostic model featuring six key genes: E2F1, MYCN, VPS72, CFAP53, OR8A1, and TXNRD1. This six-gene signature stratified patients with HCC into high- and low-risk subgroups with significantly different overall survival (P < 0.05) across training and validation cohorts. Multivariate analyses confirmed the risk score as an independent prognostic factor. Functional analysis revealed significant enrichment of DNA replication and cell cycle pathways in high-risk patients. Immune profiling showed distinct infiltration patterns and elevated immune evasion potential in the high-risk group. Drug sensitivity analyses highlighted potential therapeutic vulnerabilities to specific inhibitors.
conclusionThis study established a telomere-based prognostic model for HCC. This model provides reliable survival prediction, captures key tumor microenvironment features, and yields insights to support personalized therapeutic strategies, offering a valuable tool for clinical decision-making in HCC.
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