ArticleAnnals of translational medicine2022
Development and validation of an eight-gene signature based predictive model to evaluate the prognosis of hepatocellular carcinoma patients: a bioinformatic study.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 5 citations in OpenAlex.
- Bioinformatics combined with network pharmacology and experimental validation to identify key biomarkers of hepatocellular carcinoma and corresponding compounds in Radix Astragali and Pueraria Mirifica.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- TAF1D Functions as a Novel Biomarker in Osteosarcoma.Journal of Cancer · 2023Article
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Authors and funding
7 authors at 5 institutions in 2 countries.
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Abstract
Background: Hepatocellular carcinoma (HCC) is a malignant tumor with a poor prognosis, however, biomarkers for the prognostic assessment of HCC remain suboptimal. Consequently, we aimed to develop a reliable tool for prognostic estimation of HCC. Methods: Differentially expressed genes (DEGs) between HCC and adjacent normal tissues in 3 Gene Expression Omnibus (GEO) datasets were identified, followed by hub gene selection and least absolute shrinkage and selection operator (LASSO) Cox regression to develop a prognostic gene signature. Kaplan-Meier survival analysis, univariate and multivariate Cox regression, time-dependent area under the curve (AUC), and integrated value of time-dependent AUC (iAUC) were used to assess the relationship between predictors and clinical outcomes in the training and validation datasets. Then we built nomograms including gene signature and clinicopathological factors to forecast the probability of death. Moreover, we performed quantitative real-time PCR (qPCR) to compare the expression of prognostic genes between HCC and adjacent normal tissues. Finally, the relationship between prognostic genes and tumor microenvironment (TME) was investigated using immune cell infiltration algorithms and single cell transcriptomic database. Results: Eight prognostic genes ( Conclusions: We have established and validated an eight-gene based prognostic model, which could be an effective tool for the prognostic evaluation of HCC patients.
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