ArticleAnnals of translational medicine2020
An aberrant DNA methylation signature for predicting hepatocellular carcinoma.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Exploration of signature-related FAM genes and correlation between FAM50A expression and the pathogenesis and prognosis of hepatocellular carcinoma.Translational cancer research · 2025Article
- Integrative multi-omics analysis and experimental validation identify molecular subtypes, prognostic signature, and CA9 as a therapeutic target in oral squamous cell carcinoma.Frontiers in cell and developmental biology · 2025Article
- Mitoepigenetics pathways and natural compounds: a dual approach to combatting hepatocellular carcinoma.Medical oncology (Northwood, London, England) · 2024Review
- Article
- Integrated Bioinformatic Analysis IdentifiesDisease markers · 2022Article
- Spectrum of BRAF Aberrations and Its Potential Clinical Implications: Insights From Integrative Pan-Cancer Analysis.Frontiers in bioengineering and biotechnology · 2022Article
- Alantolactone: A Natural Plant Extract as a Potential Therapeutic Agent for Cancer.Frontiers in pharmacology · 2021Review
- Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBy the time they are clinically diagnosed, patients with hepatocellular carcinoma (HCC) are often at the advanced stage. DNA methylation has become a useful predictor of prognosis for cancer patients. Research on DNA methylation as a biomarker for assessing the risk of occurrence in HCC patients is limited. The purpose of this study was to develop an efficient methylation site model for predicting survival in patients with HCC.
methodsDNA methylation and gene expression profile data were extracted from The Cancer Genome Atlas (TCGA) database. Markers of DNA-methylated site in two subsets (the training subset and the test subset) were identified using a random survival forest algorithm and Cox proportional hazards regression. Then, Gene Ontology annotations were applied to investigate the functions of DNA methylation signatures.
resultsA total of 37 hub genes containing 713 methylated sites were identified among the differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Finally, seven methylation sites (cg12824782, cg24871714, cg18683774, cg22796509, cg19450025, cg10474350, and cg06511917) were identified. In the training group and the test group, the area under the curve predicting the survival of patients with HCC was 0.750 and 0.742, respectively. The seven methylation sites signature could be used to divide the patients in the training group into high- and low-risk subgroups [overall survival (OS): 2.81
conclusionsThe results of this study showed that the signature is useful for predicting the survival of HCC patients and thus, can facilitate treatment-related decision-making.
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