Open AccessAn 8-gene DNA methylation signature predicts the recurrence risk of cervical cancer
Author(s) -
Jinghang Ma,
Yu Huang,
Luyao Liu,
Zhen Feng
Publication year - 2021
Publication title -
journal of international medical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 57
eISSN - 1473-2300
pISSN - 0300-0605
DOI - 10.1177/03000605211018443
Subject(s) - dna methylation , cervical cancer , medicine , methylation , kegg , gene , proportional hazards model , oncology , receiver operating characteristic , cancer , hazard ratio , bioinformatics , gene expression , confidence interval , genetics , biology , gene ontology
Objective This study examined the predictive utility of DNA methylation for cervical cancer recurrence.Methods DNA methylation and RNA expression data for patients with cervical cancer were downloaded from The Cancer Genome Atlas. Differentially methylated genes (DMGs) and differentially expressed genes were screened and extracted via correlation analysis. A support vector machine (SVM)-based recurrence prediction model was established using the selected DMGs. Cox regression analysis and receiver operating characteristic curve analysis were used for self-evaluation. The Gene Expression Omnibus (GEO) database was applied for external validation. Functional enrichment was determined using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses.Results An eight-gene DNA methylation signature identified patients with a high risk of recurrence (area under the curve = 0.833). The SVM score was an independent risk factor for recurrence (hazard ratio [HR] = 0.418; 95% confidence interval [CI] = 0.26–0.67). The independent GEO database analysis further supported the result.Conclusion An eight-gene DNA methylation signature predictive of cervical cancer recurrence was identified in this study, and this signature may help identify patients at high risk of recurrence and improve clinical treatment.