ArticleBMC cancer2019
An analysis about heterogeneity among cancers based on the DNA methylation patterns.
Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- C-Reactive Protein and C-Reactive Protein-Based Scores to Predict Survival in Esophageal and Junctional Adenocarcinoma: Systematic Review and Meta-Analysis.Annals of surgical oncology · 2022Pooled it
- Comparison of Histone H3K4me3 between IVF and ICSI Technologies and between Boy and Girl Offspring.International journal of molecular sciences · 2021Trial
- Predictive significance of anterior and posterior minimal extrathyroidal extension for central lymph node metastasis in cN0 papillary thyroid carcinoma.Clinical & experimental metastasis · 2026Article
- Advances in the Molecular Imaging of Sarcoma: An Emphasis on Metabolic Imaging.Molecular imaging and biology · 2025Review
- DNA methylation expression patterns predict outcome of clear cell renal cell carcinoma.Discover oncology · 2025Article
- MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model.Nature communications · 2025Article
- Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas.Nature communications · 2023Article
- The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma.BMC bioinformatics · 2021Article
- Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.BMC cancer · 2021Article
- Clinicopathological impacts of DNA methylation alterations on pancreatic ductal adenocarcinoma: prediction of early recurrence based on genome-wide DNA methylation profiling.Journal of cancer research and clinical oncology · 2021Article
- Identification of Prognostic Biomarkers for Bladder Cancer Based on DNA Methylation Profile.Frontiers in cell and developmental biology · 2021Article
- Molecular subtypes based on DNA promoter methylation predict prognosis in lung adenocarcinoma patients.Aging · 2020Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundIt is generally believed that DNA methylation, as one of the most important epigenetic modifications, participates in the regulation of gene expression and plays an important role in the development of cancer, and there exits epigenetic heterogeneity among cancers. Therefore, this study tried to screen for reliable prognostic markers for different cancers, providing further explanation for the heterogeneity of cancers, and more targets for clinical transformation studies of cancer from epigenetic perspective.
methodsThis article discusses the epigenetic heterogeneity of cancer in detail. Firstly, DNA methylation data of seven cancer types were obtained from Illumina Infinium HumanMethylation 450 K platform of TCGA database. Then, differential methylation analysis was performed in the promotor region. Secondly, pivotal gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes obtained from two networks were integrated as candidate markers for the prognosis model. Finally, we used the univariate and multivariate COX regression models to select specific independent prognostic markers for each cancer, and studied the risk factor of these genes by doing survival analysis.
resultsFirst, the cancer type-specific gene markers were obtained by differential methylation analysis and they were found to be involved in different biological functions by enrichment analysis. Moreover, specific and common diagnostic markers for each type of cancer was sorted out and Kaplan-Meier survival analysis showed that there was significant difference in survival between the two risk groups.
conclusionsThis study screened out reliable prognostic markers for different cancers, providing a further explanation for the heterogeneity of cancer at the DNA methylation level and more targets for clinical conversion studies of cancer.
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