ArticleScientific data2025
Updating TCGA glioma classification through integration of molecular data following the latest WHO guidelines.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic value of LPAR1 expression and methylation in low-grade gliomas: a meta-analysis of TCGA and CGGA datasets and functional validation.BMC cancer · 2025Pooled it
- Plasma histone monomers as novel diagnostic markers in adult glioblastoma.The journal of liquid biopsy · 2026Article
- Integrated bulk and single-cell transcriptomic analyses identify transcriptome-defined groups and EGFR-associated microenvironmental programs in glioma.Discover oncology · 2026Article
- HISTAI: a valuable dataset with a valuable lesson.The journal of pathology. Clinical research · 2026Article
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- Artificial Intelligence in Transcriptomics: From Human-in-the-Loop to Agentic AI.Journal of personalized medicine · 2026Review
- Multimodal fusion of pathology and radiology foundation models for WHO 2021 glioma subtyping.NPJ precision oncology · 2026Article
- Impact of an evolving classification system on diffuse glioma repositories: experience from the Sydney brain tumour bank.Journal of neuro-oncology · 2026Article
- From Data to Decision: Integrating Bioinformatics into Glioma Patient Stratification and Immunotherapy Selection.International journal of molecular sciences · 2026Review
- G-protein coupled estrogen receptor 1Frontiers in endocrinology · 2026Article
- Deep learning model outperforms traditional models in clinical data-based prognostic prediction for adult-type diffuse glioma.Discover oncology · 2025Article
- Enhancing Prognostic Signatures in Glioblastoma with Feature Selection and Regularised Cox Regression.Genes · 2025Article
- EIF3M as a pan-cancer biomarker: prognostic significance and immune infiltration association.Frontiers in molecular biosciences · 2025Article
- Priority-Elastic net for binary disease outcome prediction based on multi-omics data.BioData mining · 2024Article
- Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers.Bioinformatics and biology insights · 2024Article
- Inferring Diagnostic and Prognostic Gene Expression Signatures Across WHO Glioma Classifications: A Network-Based Approach.Bioinformatics and biology insights · 2024Article
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7 authors.
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Abstract
The understanding of glioma disease has significantly advanced through the application of genetic and molecular profiling techniques on brain tumour tissue. Molecular biomarkers have gained a crucial role in glioma diagnosis, driving groundbreaking changes in the disease classification as standardised by the 2016 and 2021 World Health Organisation (WHO) Classification of Tumours of the Central Nervous System. Recent insights from large-scale multi-omics databases, such as The Cancer Genome Atlas (TCGA), have enriched our comprehension of this cancer type. However, given the evolution of glioma classification, retrospective databases may contain outdated annotations, suboptimal for research. To address this issue, we propose two methods for updating the tumor classification of TCGA glioma samples according to the 2016 and 2021 WHO guidelines, through the integration of open-access curated molecular profiling data. Respectively, our Method-2016 and Method-2021 allowed for the diagnostic update of 98% and 87% of cases. The proposed reclassification pipelines, provided in R scripts, enable straightforward reproduction or customisation upon new WHO guideline releases.
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