ArticleMolecular medicine reports2024
Combining a glycolysis‑related prognostic model based on scRNA‑Seq with experimental verification identifies ZFP41 as a potential prognostic biomarker for HCC.
Article in Molecular medicine reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 3 citations in OpenAlex.
- Article
- Downregulation of Signal Transducer and Activator of Transcription 4 Contributes to Impaired Osteogenic Differentiation of Human Bone Marrow Stem Cells during in vitro Expansion.Cells, tissues, organs · 2026Article
- The glycolytic characteristics of hepatocellular carcinoma and its interaction with the microenvironment: a comprehensive omics study.Journal of translational medicine · 2025Article
- Overexpression and clinicopathological significance of zinc finger protein 71 in hepatocellular carcinoma.World journal of hepatology · 2025Article
- Unraveling the Heterogeneity of Tumor Immune Microenvironment in Hepatocellular Carcinoma by SingleCell RNA Sequencing and its Implications for Prognosis and Therapeutic Response.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is a common malignancy with a poor prognosis, and its heterogeneity affects the response to clinical treatments. Glycolysis is highly associated with HCC therapy and prognosis. The present study aimed to identify a novel biomarker for HCC by exploring the heterogeneity of glycolysis in HCC. The intersection of both marker genes of glycolysis‑related cell clusters from single‑cell RNA sequencing analysis and mRNA data of liver HCC from The Cancer Genome Atlas were used to construct a prognostic model through Cox proportional hazard regression and the least absolute shrinkage and selection operator Cox regression. Data from the International Cancer Genome Consortium were used to validate the results of the analysis. Immune status analysis was then conducted. A significant gene in the prognostic model was identified as a potential biomarker and was verified through
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Registered trials
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