A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification.
Abstract: Classification of tumors in neuro-oncology today relies on molecular patterns (mostly DNA methylation) and their machine learning-supported interpretation. Understanding the process of algorithmic interpretation is essential for safe application in clinical routine. This is paradigmatically true for the most common primary intracranial tumor in adults, meningioma. Here, by applying multiomic profiling and multiple lines of orthogonal computational evaluation in multiple independent datasets, we found that not only tumor cell characteristics but also incremental changes in the tumor microenvironment (TME) have impact on epigenetic meningioma classification and clinical outcome. Besides revealing the decisive role of non-neoplastic cells in the CNS methylation classifier, this challenges the model of distinct meningioma subgroups toward a TME-determined risk continuum. This refines current controversies in molecular meningioma subtyping. In addition, we apply these learnings to devise and validate a simple diagnostic approach for increased clinical prediction accuracy based on immunohistochemistry, which is also applicable in resource-limited settings.
Authors: Sybren L N Maas, Yiheng Tang, Eric Stutheit-Zhao, Ramin Rahmanzade, Christina Blume, Thomas Hielscher, Ferdinand Zettl, Salvatore Benfatto, Domenico Calafato, Martin Sill, Jasim Kada Benotmane, Yahaya A Yabo, Felix Behling, Abigail Suwala, Helin Kardo, Michael Ritter, Matthieu Peyre, Roman Sankowski, Konstantin Okonechnikov, Philipp Sievers, Areeba Patel, David Reuss, Mirco J Friedrich, Damian Stichel, Daniel Schrimpf, Thierry P P Van den Bosch, Katja Beck, Hans-Georg Wirsching, Gerhard Jungwirth, C Oliver Hanemann, Katrin Lamszus, Nima Etminan, Andreas Unterberg, Christian Mawrin, Marc Remke, Olivier Ayrault, Peter Lichter, Guido Reifenberger, Michael Platten, Tim Kacprowski, Markus List, Josch K Pauling, Jan Baumbach, Till Milde, Rachel Grossmann, Zvi Ram, Miriam Ratliff, Jan-Philipp Mallm, Marian C Neidert, Eelke M Bos, Marco Prinz, Michael Weller, Till Acker, Felix J Hartmann, Matthias Preusser, Ghazaleh Tabatabai, Christel Herold-Mende, Sandro M Krieg, David T W Jones, Stefan M Pfister, Wolfgang Wick, Michel Kalamarides, Andreas von Deimling, Dieter Henrik Heiland, Volker Hovestadt, Moritz Gerstung, Matthias Schlesner, , Felix Sahm
Published: Feb 2026 / Journal: Nature genetics
Multiomic integration reveals tumoral heterogeneity of lipid dependence within lethal group 3 medulloblastoma.
Abstract: Medulloblastoma, the most common malignant brain tumor of childhood, exhibits significant biological complexity that demands deeper exploration. Here, we present a large multiomics dataset integrating data from 384 primary medulloblastoma patient samples across five omic layers: CpG methylome, transcriptome, proteome, phosphoproteome, and metabolome, paired with associated clinical metadata. Data integration revealed intertumoral heterogeneity of lipid metabolism across proteomic subtypes. Notably, while the MYC-FASN-SCD axis drives lipid biosynthesis, pathway inhibition elicits a compensatory escape mechanism in vivo through exogenous fatty acid uptake. Unexpectedly, we demonstrated that MYC triggers lipid storage, creating a unique dependency on lipid droplet-mitochondria communications to sustain tumor maintenance in vivo. Together, this comprehensive analysis reveals a targetable vulnerability downstream of MYC that constitutes a promising therapeutic approach to treat currently untreatable medulloblastoma subtypes.
Authors: Flavia Bernardi, Jacob Torrejon, Irene Basili, Randy Van Ommeren, Véronique Marsaud, Hua Yu, Julie Talbot, Judith Souphron, Emilie Indersie, Antoine Forget, Benjamin Bonneau, Alexane Massiot, Coralie Alcazar, Laurine Figeac, Emma Bonerandi, Gabriele Cancila, Olga Sirbu, Navneesh Yadav, Dinesh Mohanakrishnan, Bérangère Lombard, Damarys Loew, Patrick Poullet, Stephane Liva, Marta Lovino, I-Hsuan Lin, Takuma Nakashima, Tarek Gharsalli, Paul Antoine Nicolas, Naoji Yubuki, Roberto A Ribas, Benoit Colsch, Emeline Chu-Van, Florence Castelli, Julio Lopes Sampaio, Sophie Leboucher, Charlene Lasgi, Laetitia Besse, Marie-Noëlle Soler, Valentina Lo Re, Nathalie Planque, Namal Abeysundara, Polina Balin, Hao Wang, Haipeng Su, Xiaochong Wu, Florence M G Cavalli, Olivier Saulnier, Elisa Ficarra, Lucia Di Marcotullio, Kohei Kumegawa, Reo Maruyama, Daisuke Kawauchi, Daniel Picard, Marc Remke, Laurent Riffaud, Chloé Puiseux, Yassine Bouchoucha, Sophie Huybrechts, Marie Simbozel, Franck Bourdeaut, Pascale Varlet, Stéphanie Puget, Thomas Blauwblomme, Mamy Andrianteranagna, Julien Masliah Planchon, Aurelien Dugourd, Julio Saez-Rodriguez, Emmanuel Barillot, Nicolas Servant, Loredana Martignetti, Jeremy Rich, Marcel Kool, Stefan M Pfister, Sameer Agnihotri, Hiromichi Suzuki, Marjorie Fanjul, Won-Jing Wang, Jin-Wu Tsai, Ramon C Sun, Kévin Beccaria, Christelle Dufour, Jean-Emmanuel Sarry, Kulandaimanuvel Antony Michealraj, Michael D Taylor, Olivier Ayrault
Published: Feb 2026 / Journal: Cancer cell
Modelling EWS::FLI1 protein fluctuations reveal determinants of tumor plasticity in Ewing sarcoma.
Abstract: Tumor cell plasticity drives metastasis and therapy resistance, yet its regulation by oncoprotein dosage dynamics remains poorly understood. In Ewing sarcoma (EwS), variations in EWS::FLI1 (EF) fusion oncoprotein activity have been associated with epithelial-mesenchymal plasticity (EMP). Using degron technology, we precisely modulated endogenous EF in EwS cells and linked phenotypic states to distinct oncoprotein dosages. Strikingly, modest EF depletion promoted a pro-metastatic phenotype that diminished upon near-complete EF loss, revealing a paradoxical effect of submaximal EF inhibition. Nascent RNA-sequencing uncovered distinct gene clusters with heterogenous transcriptional responses to graded EF loss. Genes most sensitive to subtle EF depletion harbored GGAA microsatellites within EF-bound enhancers, while chromatin profiling uncovered candidate cofactors regulating EF-repressed EMP programs. Transient EF depletion followed by rapid restoration, modelling oncoprotein fluctuations, caused persistent dysregulation of genes functionally linked to enhanced extravasation and metastatic burden in preclinical models. This study highlights the therapeutic challenge of incomplete EF elimination, serving a paradigm in which oncoprotein dosage dynamics act as non-genetic drivers of disease progression and reveal novel vulnerabilities of advanced disease.
Authors: Veveeyan Suresh, Christoph Hafemeister, Andri Konstantinou, Sarah Grissenberger, Caterina Sturtzel, Martha M Zylka, Florencia Cidre-Aranaz, Andrea Wenninger-Weinzierl, Karla Queiroz, Dorota Kurek, Martin Distel, Anna Obenauf, Thomas G P Grünewald, Florian Halbritter, Heinrich Kovar, Valerie Fock
Published: Feb 2026 / Journal: EMBO molecular medicine
Loss of CTLH component MAEA impairs DNA repair and replication and leads to developmental delay.
Abstract: Ubiquitin E3 ligases play crucial roles in the DNA damage response (DDR) by modulating the turnover, localization, activation, and interactions of DDR and DNA replication proteins. We performed a CRISPR-Cas9 knockout screen focused on ubiquitin E3 ligases and related proteins with the DNA topoisomerase I inhibitor camptothecin. This led us to establish that MAEA, a core subunit of the CTLH E3 ligase complex, is a critical regulator of homologous recombination and the replication stress response. In tandem, we identified eight patients with variants in MAEA who present with a neurodevelopmental disorder that we term DIADEM (Developmental delay and Intellectual disability Associated with DEfects in MAEA). Analysis of patient-derived cell lines and mutation modeling reveal an underlying defect in HR-dependent DNA repair and replication fork restart and protection as a likely cause of disease. Mechanistically, we find that MAEA dysfunction hinders DNA repair by reducing the efficiency of RAD51 loading at sites of DNA damage, which we propose may contribute to the presentation of DIADEM by compromising genome integrity and cell division during development.
Authors: Søren H Hough, Satpal S Jhujh, Samah W Awwad, Oliver E Lewis, Simon Lam, John C Thomas, Thorsten Mosler, Aldo Bader, Lauren Bartik, Shane McKee, Shivarajan Amudhavalli, Estelle Colin, Nadirah Damseh, Emma Clement, Pilar Cacheiro, Anirban Majumdar, Damian Smedley, Joël Fluss, Rosalinda Giannini, Isabelle Thiffault, Guido Zagnoli Vieira, Rimma Belotserkovskaya, Stephen J Smerdon, Petra Beli, Yaron Galanty, Christopher J Carnie, Grant S Stewart, Stephen P Jackson
Published: Feb 2026 / Journal: EMBO molecular medicine
Advancing CNS tumor diagnostics with expanded DNA methylation-based classification.
Abstract: 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.
Authors: Martin Sill, Daniel Schrimpf, Areeba Patel, Dominik Sturm, Natalie Jäger, Philipp Sievers, Leonille Schweizer, Rouzbeh Banan, David Reuss, Abigail Suwala, Andrey Korshunov, Damian Stichel, Annika K Wefers, Ann-Christin Hau, Henning Boldt, Patrick N Harter, Zied Abdullaev, Jamal Benhamida, Daniel Teichmann, Arend Koch, Jürgen Hench, Stephan Frank, Martin Hasselblatt, Sheila Mansouri, Theresita Díaz de Ståhl, Jonathan Serrano, Jonas Ecker, Florian Selt, Michael Taylor, Vijay Ramaswamy, Florence Cavalli, Anna S Berghoff, Brigitte Bison, Mirjam Blattner-Johnson, Ivo Buchhalter, Rolf Buslei, Gabriele Calaminus, Nicola Dikow, Hildegard Dohmen, Philipp Euskirchen, Gudrun Fleischhack, Amar Gajjar, Nicolas U Gerber, Marco Gessi, Gerrit H Gielen, Astrid Gnekow, Nicholas G Gottardo, Christine Haberler, Stefan Hamelmann, Volkmar Hans, Jordan R Hansford, Christian Hartmann, Frank L Heppner, Pablo Hernaiz Driever, Katja von Hoff, Ulrich W Thomale, Stephan Tippelt, Michael C Frühwald, Christof M Kramm, Ulrich Schüller, Jens Schittenhelm, Martin U Schuhmann, Marco Stein, Petra Ketteler, Marc Ladanyi, Nada Jabado, Barbara C Jones, Chris Jones, Matthias A Karajannis, Ralf Ketter, Patricia Kohlhof, Uwe Kordes, Annekathrin Reinhardt, Christian Kölsche, Katrin Lamszus, Peter Lichter, Sybren L N Maas, Christian Mawrin, Till Milde, Michel Mittelbronn, Camelia-Maria Monoranu, Wolf Mueller, Martin Mynarek, Paul A Northcott, Kristian W Pajtler, Werner Paulus, Arie Perry, Ingmar Blümcke, Karl H Plate, Michael Platten, Matthias Preusser, Torsten Pietsch, Marco Prinz, Guido Reifenberger, Bjarne W Kristensen, Marcel Kool, Volker Hovestadt, David W Ellison, Thomas S Jacques, Pascale Varlet, Nima Etminan, Till Acker, Michael Weller, Christine L White, Olaf Witt, Christel Herold-Mende, Jürgen Debus, Sandro Krieg, Wolfgang Wick, Matija Snuderl, Ken Aldape, Sebastian Brandner, Cynthia Hawkins, Craig Horbinski, Christian Thomas, Pieter Wesseling, Andreas von Deimling, David Capper, Stefan M Pfister, David T W Jones, Felix Sahm
Published: Feb 2026 / Journal: Cancer cell