Advancing CNS tumor diagnostics with expanded DNA methylation-based classification
DNA methylation-based classification is now central to contemporary neuro-oncology, as highlighted by the World Health Organization (WHO) classification of central nervous system (CNS) tumors. We present the Heidelberg CNS Tumor Methylation Classifier version 12.8 (v12.8), trained on 7,495 methylati...
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
9 February 2026
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| In: |
Cancer cell
Year: 2026, Jahrgang: 44, Heft: 2 |
| ISSN: | 1878-3686 |
| DOI: | 10.1016/j.ccell.2025.11.002 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.ccell.2025.11.002 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S1535610825004957 |
| Verfasserangaben: | Martin Sill, Daniel Schrimpf, Areeba Patel, Dominik Sturm, Natalie Jäger, Philipp Sievers, Rouzbeh Banan, David Reuss, Abigail Suwala, Damian Stichel, Annika K. Wefers, Jonas Ecker, Florian Selt, Nicola Dikow, Stefan Hamelmann, Barbara C. Jones, Chris Jones, Annekathrin Reinhardt, Peter Lichter, Till Milde, Kristian W. Pajtler, Karl H. Plate, Michael Platten, Marcel Kool, Nima Etminan, Olaf Witt, Christel Herold-Mende, Jürgen Debus, Sandro Krieg, Wolfgang Wick, Andreas von Deimling, Stefan M. Pfister, David T.W. Jones, Felix Sahm [und viele weitere] |
| Zusammenfassung: | DNA methylation-based classification is now central to contemporary neuro-oncology, as highlighted by the World Health Organization (WHO) classification of central nervous system (CNS) tumors. We present the Heidelberg CNS Tumor Methylation Classifier version 12.8 (v12.8), trained on 7,495 methylation profiles, which expands recognized entities from 91 classes in version 11 (v11) to 184 subclasses. This expansion is a result of newly identified tumor types discovered through our large online repository and global collaborations, underscoring CNS tumor heterogeneity. The random forest-based classifier achieves 95% subclass-level accuracy, with its well-calibrated probabilistic scores providing a reliable measure of confidence for each classification. Its hierarchical output structure enables interpretation across subclass, class, family, and superfamily levels, thereby supporting clinical decisions at multiple granularities. Comparative analyses demonstrate that v12.8 surpasses previous versions and conventional WHO-based approaches. These advances highlight the improved precision and practical utility of the updated classifier in personalized neuro-oncology. |
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| Beschreibung: | Online verfügbar 4 December 2025, Artikelversion 9 February 2026 Gesehen am 03.06.2026 |
| Beschreibung: | Online Resource |
| ISSN: | 1878-3686 |
| DOI: | 10.1016/j.ccell.2025.11.002 |