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Peer-reviewedCC BYNature

Decoding the regulatory programs governing glioblastoma plasticity

  • Manu Saraswat1,2,3,4,5,6
  • Laura Rueda-Gensini1,2,5,6
  • Elisa Heinzelmann1,7,2,5,6
  • Tannia Gracia7
  • Fani Memi7
  • Grant de Jong7
  • Jannes Straub1,2,6
  • Cedar Schloo1,2,5,6
  • Dirk C. Hoffmann8,9
  • Erik Jung8,9
  • Tim Kindinger1,2,6
  • Louis Masclef1,2,6
13 more authors
  • Bettina Weigel1,2,5,6
  • Bryce Lim1,2,5,6
  • Faustus Tuschmann1,2,6
  • Sophie Heuer8,9
  • Oliver Gould7
  • Richard James Mair10,11
  • Katharina Mikulik3,5
  • Martin Rohbeck3,4
  • Wolfgang Wick8,9
  • Frank Winkler8,9
  • Omer Ali Bayraktar12,13
  • Oliver Stegle14,15
  • Moritz Mall16,17,18
18 affiliations
  1. 1Cell Fate Engineering and Disease Modeling Division, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany
  2. 2Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
  3. 3Computational Genomics and Systems Genetics Division, German Cancer Research Center (DKFZ), Heidelberg, Germany
  4. 4European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
  5. 5Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
  6. 6HITBR Hector Institute for Translational Brain Research, Heidelberg, Germany
  7. 7Cellular Genetics Programme, Wellcome Sanger Institute, Cambridge, UK
  8. 8Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), DKFZ, Heidelberg, Germany
  9. 9Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
  10. 10Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
  11. 11Department of Clinical Neurosciences, Cambridge University, Cambridge, UK
  12. 12Cellular Genetics Programme, Wellcome Sanger Institute, Cambridge, UK. [email protected]
  13. 13UCL Cancer Institute, University College London, London, UK. [email protected]
  14. 14Computational Genomics and Systems Genetics Division, German Cancer Research Center (DKFZ), Heidelberg, Germany. [email protected]
  15. 15European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany. [email protected]
  16. 16Cell Fate Engineering and Disease Modeling Division, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany. [email protected]
  17. 17Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. [email protected]
  18. 18HITBR Hector Institute for Translational Brain Research, Heidelberg, Germany. [email protected]
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Abstract

. Here we introduce scDORI (single-cell deep multi-omic regulatory inference)-a deep-learning framework that infers enhancer-driven gene-regulatory networks at single-cell resolution-and apply it to single-nucleus multiome profiles of more than one million cells from primary glioblastomas. Integrating computational inference with systematic perturbation screens across patient-derived models, we show that a structured regulatory program with an asymmetric interplay of activators and repressors governs cellular plasticity in glioblastoma. The resulting transition landscape is hierarchical and predictable, but permits cross-lineage trajectories that are absent from normal neurodevelopment. Within this landscape, low-plasticity states such as the neuronal-like state are not stable differentiation end points but actively maintained configurations, stabilized by a network of safeguard repressors that silence alternative fates. We identify MYT1L as the dominant member of this network, and show that it binds to and represses master regulators of every alternative state to consolidate neuronal-like identity. MYT1L restricted plasticity even under standard-of-care therapy and suppressed tumour growth and invasion in vivo. Conversely, loss of MYT1L reactivated plasticity and accelerated malignant features, indicating that low-plasticity identity requires continuous repression. These findings reframe malignant cell state stability as a balance between activation and continuous repression, and nominate safeguard repressors as candidate therapeutic targets that are distinct from differentiation-inducing activators, with potential relevance across cancers in which phenotypic switching drives therapy resistance.

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Cite

BibTeXRIS
BibTeX
@article{saraswat2026decoding,
  title = {{Decoding the regulatory programs governing glioblastoma plasticity}},
  author = {Manu Saraswat and Laura Rueda-Gensini and Elisa Heinzelmann and Tannia Gracia and Fani Memi and Grant de Jong and Jannes Straub and Cedar Schloo and Dirk C. Hoffmann and Erik Jung and Tim Kindinger and Louis Masclef and Bettina Weigel and Bryce Lim and Faustus Tuschmann and Sophie Heuer and Oliver Gould and Richard James Mair and Katharina Mikulik and Martin Rohbeck and Wolfgang Wick and Frank Winkler and Omer Ali Bayraktar and Oliver Stegle and Moritz Mall},
  journal = {Nature},
  year = {2026},
  month = nov,
  doi = {10.1038/s41586-026-11177-0},
  url = {https://doi.org/10.1038/s41586-026-11177-0},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Decoding the regulatory programs governing glioblastoma plasticity
AU  - Manu Saraswat
AU  - Laura Rueda-Gensini
AU  - Elisa Heinzelmann
AU  - Tannia Gracia
AU  - Fani Memi
AU  - Grant de Jong
AU  - Jannes Straub
AU  - Cedar Schloo
AU  - Dirk C. Hoffmann
AU  - Erik Jung
AU  - Tim Kindinger
AU  - Louis Masclef
AU  - Bettina Weigel
AU  - Bryce Lim
AU  - Faustus Tuschmann
AU  - Sophie Heuer
AU  - Oliver Gould
AU  - Richard James Mair
AU  - Katharina Mikulik
AU  - Martin Rohbeck
AU  - Wolfgang Wick
AU  - Frank Winkler
AU  - Omer Ali Bayraktar
AU  - Oliver Stegle
AU  - Moritz Mall
PY  - 2026
DA  - 2026/11/04
JO  - Nature
DO  - 10.1038/s41586-026-11177-0
UR  - https://doi.org/10.1038/s41586-026-11177-0
AB  - . Here we introduce scDORI (single-cell deep multi-omic regulatory inference)-a deep-learning framework that infers enhancer-driven gene-regulatory networks at single-cell resolution-and apply it to single-nucleus multiome profiles of more than one million cells from primary glioblastomas. Integrating computational inference with systematic perturbation screens across patient-derived models, we show that a structured regulatory program with an asymmetric interplay of activators and repressors governs cellular plasticity in glioblastoma. The resulting transition landscape is hierarchical and predictable, but permits cross-lineage trajectories that are absent from normal neurodevelopment. Within this landscape, low-plasticity states such as the neuronal-like state are not stable differentiation end points but actively maintained configurations, stabilized by a network of safeguard repressors that silence alternative fates. We identify MYT1L as the dominant member of this network, and show that it binds to and represses master regulators of every alternative state to consolidate neuronal-like identity. MYT1L restricted plasticity even under standard-of-care therapy and suppressed tumour growth and invasion in vivo. Conversely, loss of MYT1L reactivated plasticity and accelerated malignant features, indicating that low-plasticity identity requires continuous repression. These findings reframe malignant cell state stability as a balance between activation and continuous repression, and nominate safeguard repressors as candidate therapeutic targets that are distinct from differentiation-inducing activators, with potential relevance across cancers in which phenotypic switching drives therapy resistance.
SN  - 0028-0836
SN  - 1476-4687
ER  -