ArticleJournal of clinical and translational hepatology2021
Development of an Eight-gene Prognostic Model for Overall Survival Prediction in Patients with Hepatocellular Carcinoma.
Article in Journal of clinical and translational hepatology, 2021. 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.
- SORBS2: A Molecular Nexus in Multisystem Diseases Through Scaffold-Mediated Regulation.Journal of cellular and molecular medicine · 2026Review
- CoxKAN: Kolmogorov-Arnold networks for interpretable, high-performance survival analysis.Bioinformatics (Oxford, England) · 2025Article
- Prognostic prediction signature and molecular subtype for liver cancer: A CTC/CTM‑related gene prediction model and independent external validation.Oncology letters · 2024Article
- Deep dissection of stemness-related hierarchies in hepatocellular carcinoma.Journal of translational medicine · 2023Article
- Construction of a risk model and prediction of prognosis and immunotherapy based on cuproptosis-related LncRNAs in the urinary system pan-cancer.European journal of medical research · 2023Article
- Genes Modulating Butyrate Metabolism for Assessing Clinical Prognosis and Responses to Systematic Therapies in Hepatocellular Carcinoma.Biomolecules · 2022Article
- Exploring potential targets of Actinidia chinensis Planch root against hepatocellular carcinoma based on network pharmacology and molecular docking and development and verification of immune-associated prognosis features for hepatocellular carcinoma.Journal of gastrointestinal oncology · 2022Article
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7 authors.
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Abstract
BACKGROUND AND
aimsThe overall survival (OS) of hepatocellular carcinoma (HCC) remains dismal. Bioinformatic analysis of transcriptome data could identify patients with poor OS and may facilitate clinical decision. This study aimed to develop a prognostic gene model for HCC.
methodsGSE14520 was retrieved as a training set to identify differential expressed genes (DEGs) between tumor and adjacent liver tissues in HCC patients with different OS. A DEG-based prognostic model was then constructed and the TCGA-LIHC and ICGC-LIRI datasets were used to validate the model. The area under the receiver operating characteristic curve (AUC) and hazard ratio (HR) of the model for OS were calculated. A model-based nomogram was established and verified.
resultsIn the training set, differential expression analysis identified 80 genes dysregulated in oxidation-reduction and metabolism regulation. After univariate Cox and LASSO regression, eight genes (LPCAT1, DHRS1, SORBS2, ALDH5A1, SULT1C2, SPP1, HEY1 and GOLM1) were selected to build the prognostic model. The AUC for 1-, 3- and 5-year OS were 0.779, 0.736, 0.754 in training set and 0.693, 0.689, 0.693 in the TCGA-LIHC validation set, respectively. The AUC for 1- and 3-year OS were 0.767 and 0.705 in the ICGC-LIRI validation set. Multivariate analysis confirmed the model was an independent prognostic factor (training set: HR=4.422,
conclusionsOur eight-gene prognostic model and the related nomogram represent as reliable prognostic tools for OS prediction in HCC patients.
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