ArticleCancer gene therapy2020
Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns.
Article in Cancer gene therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Glioblastoma at the crossroads: current understanding and future therapeutic horizons.Signal transduction and targeted therapy · 2025Review
- Discovery of a Therapeutic Agent for Glioblastoma Using a Systems Biology-Based Drug Repositioning Approach.International journal of molecular sciences · 2024Article
- Comprehensive understanding of glioblastoma molecular phenotypes: classification, characteristics, and transition.Cancer biology & medicine · 2024Review
- DNA methylation-based subtypes of acute myeloid leukemia with distinct prognosis and clinical features.Clinical and experimental medicine · 2023Article
- Article
- Deep multi-omics integration by learning correlation-maximizing representation identifies prognostically stratified cancer subtypes.Bioinformatics advances · 2023Article
- I kappa B kinase interacting protein as a promising biomarker in pan-cancer: A multi-omics analysis.Frontiers in genetics · 2023Article
- Current Opportunities for Targeting Dysregulated Neurodevelopmental Signaling Pathways in Glioblastoma.Cells · 2022Review
- Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma.BMC cancer · 2022Article
- Bisulfite profiling of the MGMT promoter and comparison with routine testing in glioblastoma diagnostics.Clinical epigenetics · 2022Article
- Construction of Molecular Subtypes and Related Prognostic and Immune Response Models Based on M2 Macrophages in Glioblastoma.International journal of general medicine · 2022Article
- Genome-wide profiling of alternative splicing in glioblastoma and their clinical value.BMC cancer · 2021Article
- Review
- Perspective of mesenchymal transformation in glioblastoma.Acta neuropathologica communications · 2021Review
- Current Advances in Immunotherapy for Glioblastoma.Current oncology reports · 2021Review
- DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival.International journal of molecular sciences · 2021Article
- A Signature of Nine lncRNA Methylated Genes Predicts Survival in Patients With Glioma.Frontiers in oncology · 2021Article
- Current Opinion on Molecular Characterization for GBM Classification in Guiding Clinical Diagnosis, Prognosis, and Therapy.Frontiers in molecular biosciences · 2020Review
- Adhesion G protein-coupled receptors in glioblastoma.Neuro-oncology advancesReview
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.
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