ReviewJournal of Korean medical science2023
Brain Tumor Classification by Methylation Profile.
Review in Journal of Korean medical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Multi-Omics and Machine Learning Analyses Reveal PIK3CG, PRKCD, and TRIM22 as Potential Markers of Poor Prognosis and Immune Activation in Glioblastoma.Journal of Korean medical science · 2026Article
- The contribution of methylation profiling in neuropathological diagnosis of central nervous system tumors in children, adolescent and young adults.Pathologica · 2025Article
- Conserved methylation signature accurately predicts heavily irradiated CNS tumour with perplexing histopathology: A case report.Biomedical reports · 2025Article
- Multi-Layered Analysis of TGF-β Signaling and Regulation via DNA Methylation and microRNAs in Astrocytic Tumors.International journal of molecular sciences · 2025Article
- Analysis of the Expression Patterns of Tumor Necrosis Factor Alpha Signaling Pathways and Regulatory MicroRNAs in Astrocytic Tumors.International journal of molecular sciences · 2025Article
- Rare glioblastoma subtype masquerading as a poorly differentiated carcinoma: illustrative case.Journal of neurosurgery. Case lessons · 2025Article
- Methylation profiling in neuropathological tumors diagnosis: a comprehensive review.Frontiers in oncology · 2025Review
- Neuroepithelial tumors of the central nervous system withFrontiers in oncology · 2025Article
- Multi-omics profiling of TGF-β isoforms and regulatory miRNAs in astrocytic tumors reveals TGF-β-3 as a prognostic biomarker.Frontiers in oncology · 2025Article
- Variances in the Expression Profile of Circadian Clock-Related Genes in Astrocytic Brain Tumors.Cancers · 2024Article
- cIMPACT-NOW update 9: Recommendations on utilization of genome-wide DNA methylation profiling for central nervous system tumor diagnostics.Neuro-oncology advancesReview
- Revisiting pediatric HGGs and PNETs according to the WHO CNS5 criteria: A clinical and genomic retrospective analysis.Neuro-oncology advancesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients. The methylation classifier can be used to perform classification on tumor samples with diagnostic difficulties due to ambiguous histology or mismatch between histopathology and molecular signatures, i.e., not otherwise specified (NOS) cases or not elsewhere classified (NEC) cases, aiding in pathological decision-making. Here, the authors elucidate upon the application of a methylation classifier as a tool to mitigate the inherent complexities associated with the pathological evaluation of brain tumors, even when pathologists are experts in histopathological diagnosis and have access to enough molecular genetic information. Also, it should be emphasized that methylome cannot classify all types of brain tumors, and it often produces erroneous matches even with high matching scores, so, excessive trust is prohibited. The primary issue is the considerable difficulty in obtaining reference data regarding the methylation profile of each type of brain tumor. This challenge is further amplified when dealing with recently identified novel types or subtypes of brain tumors, as such data are not readily accessible through open databases or authors of publications. An additional obstacle arises from the fact that methylation classifiers are primarily research-based, leading to the unavailability of charging patients. It is important to note that the application of methylation classifiers may require specialized laboratory techniques and expertise in DNA methylation analysis.
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Registered trials
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