Observational studyMedicine2020
Identification of MTHFD2 as a novel prognosis biomarker in esophageal carcinoma patients based on transcriptomic data and methylation profiling.
Observational study in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The trial behind it
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- TAF15-mediated m5C modification of MTHFD2 RNA reveals a novel therapeutic target for IDH mutant gliomas.Biomarker research · 2026Article
- Comprehensive in silico CpG methylation analysis in hepatocellular carcinoma identifies tissue- and tumor-type specific marks disconnected from gene expression.Journal of physiology and biochemistry · 2024Article
- MTHFD2 in healthy and cancer cells: Canonical and non-canonical functions.npj metabolic health and disease · 2024Review
- Metabolic subtypes and immune landscapes in esophageal squamous cell carcinoma: prognostic implications and potential for personalized therapies.BMC cancer · 2024Article
- Delineating the glioblastoma stemness by genes involved in cytoskeletal rearrangements and metabolic alterations.World journal of stem cells · 2023Review
- Biology of Pellino1: a potential therapeutic target for inflammation in diseases and cancers.Frontiers in immunology · 2023Review
- Identification of a metabolic reprogramming-related signature associated with prognosis and immune microenvironment of head and neck squamous cell carcinoma by in silico analysis.Cancer medicine · 2022Article
- ATF4/MYC Regulates MTHFD2 to Promote NSCLC Progression by Mediating Redox Homeostasis.Disease markers · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA methylation is an important epigenetic regulatory mechanism in esophageal carcinoma (EC) and is associated with genomic instability and carcinogenesis. In the present study, we aimed to identify tumor biomarkers for predicting prognosis of EC patients.We downloaded mRNA expression profiles and DNA methylation profiles associated with EC from the Gene Expression Omnibus database. Differentially expressed and differentially methylated genes between tumor tissues and adjacent normal tissue samples were identified. Functional enrichment analyses were performed, followed by the construction of protein-protein interaction networks. Data were validated based on methylation profiles from The Cancer Genome Atlas. Candidate genes were further verified according to survival analysis and Cox regression analysis.We uncovered multiple genes with differential expression or methylation in tumor samples compared with normal samples. After taking the intersection of 3 differential gene sets, we obtained a total of 232 overlapping genes. Functional enrichment analysis revealed that these genes are related to pathways such as "glutathione metabolism," "p53 signaling pathway," and "focal adhesion." Furthermore, 8 hub genes with inversed expression and methylation correlation were identified as candidate genes. The abnormal expression levels of MSN, PELI1, and MTHFD2 were correlated with overall survival times in EC patients (P < .05). Only MTHFD2 was significantly associated with a pathologic stage according to univariate analysis (P = .037) and multivariate analysis (P = .043).Our study identified several novel EC biomarkers with prognostic value by integrated analysis of transcriptomic data and methylation profiles. MTHFD2 could serve as an independent biomarker for predicting prognosis and pathological stages of EC.
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