ArticleFrontiers in oncology2020
A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer.
Article in Frontiers in oncology, 2020. 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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Who cites it
5 citing papers in PubMed.
- Plasma-based digital PCR assay for early detection of gastric cancer using multiple methylation biomarkers.Scientific reports · 2025Article
- Article
- A SERPINE1-Based Immune Gene Signature Predicts Prognosis and Immunotherapy Response in Gastric Cancer.Pharmaceuticals (Basel, Switzerland) · 2022Article
- DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer.Journal of oncology · 2022Article
- Contrast-Enhanced Computed Tomography-Based Radiogenomics Analysis for Predicting Prognosis in Gastric Cancer.Frontiers in oncology · 2022Article
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Authors and funding
5 authors.
Funding
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Abstract
purposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model
methodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.
results5 DNA methylation-driven genes (
conclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.
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