ArticleClinical epigenetics2015
MethPed: a DNA methylation classifier tool for the identification of pediatric brain tumor subtypes.
Article in Clinical epigenetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 45 citations in OpenAlex.
- The impact of deep learning and omics data in transforming precision therapy for brain cancer.Frontiers in bioinformatics · 2026Review
- Enhancing the accuracy of molecular classification of pediatric CNS tumors: a dual-classifier approach using DNA methylation profiling.Frontiers in oncology · 2025Article
- Comparison of DNA methylation based classification models for precision diagnostics of central nervous system tumors.NPJ precision oncology · 2024Article
- Long-read sequencing for brain tumors.Frontiers in oncology · 2024Review
- Sex differences in methylation profiles are apparent in medulloblastoma, particularly among SHH tumors.Frontiers in oncology · 2023Article
- Review
- Machine Learning in the Classification of Pediatric Posterior Fossa Tumors: A Systematic Review.Cancers · 2022Review
- Spatial heterogeneity in DNA methylation and chromosomal alterations in diffuse gliomas and meningiomas.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022Article
- DNA methylation profiling improves routine diagnosis of paediatric central nervous system tumours: A prospective population-based study.Neuropathology and applied neurobiology · 2022Article
- Recent Advances in Pediatric Cancer Research.Cancer research · 2021Review
- DNA 5-hydroxymethylcytosine in pediatric central nervous system tumors may impact tumor classification and is a positive prognostic marker.Clinical epigenetics · 2021Article
- MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks.NPJ systems biology and applications · 2021Article
- DNA methylation profiling for molecular classification of adult diffuse lower-grade gliomas.Clinical epigenetics · 2021Article
- Epigenomics and immunotherapeutic advances in pediatric brain tumors.NPJ precision oncology · 2021Review
- Article
- Brain tumour diagnostics using a DNA methylation-based classifier as a diagnostic support tool.Neuropathology and applied neurobiology · 2020Article
- Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genes.Bioinformatics (Oxford, England) · 2019Article
- Intratumor DNA methylation heterogeneity in glioblastoma: implications for DNA methylation-based classification.Neuro-oncology · 2019Article
- Cell line-based xenograft mouse model of paediatric glioma stem cells mirrors the clinical course of the patient.Carcinogenesis · 2018Article
- Stem cell cultures derived from pediatric brain tumors accurately model the originating tumors.Oncotarget · 2017Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClassification of pediatric tumors into biologically defined subtypes is challenging, and multifaceted approaches are needed. For this aim, we developed a diagnostic classifier based on DNA methylation profiles.
resultsMethylation data generated by the Illumina Infinium HumanMethylation 450 BeadChip arrays were downloaded from the Gene Expression Omnibus (n = 472). Using the data, we built MethPed, which is a multiclass random forest algorithm, based on DNA methylation profiles from nine subgroups of pediatric brain tumors. DNA from 18 regional samples was used to validate MethPed. MethPed was additionally applied to a set of 28 publically available tumors with the heterogeneous diagnosis PNET. MethPed could successfully separate individual histology tumor types at a very high accuracy (κ = 0.98). Analysis of a regional cohort demonstrated the clinical benefit of MethPed, as confirmation of diagnosis of tumors with clear histology but also identified possible differential diagnoses in tumors with complicated and mixed type morphology.
conclusionsWe demonstrate the utility of methylation profiling of pediatric brain tumors and offer MethPed as an easy-to-use toolbox that allows researchers and clinical diagnosticians to test single samples as well as large cohorts for subclass prediction of pediatric brain tumors. This will immediately aid clinical practice and importantly increase our molecular knowledge of these tumors for further therapeutic development.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.