Peer-reviewedCC BYNature
A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity
22 affiliations
- 1Wellcome Sanger Institute, Cambridge, UK
- 2Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- 3European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- 4Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- 5Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge, UK
- 6Department of Neurosurgery, Cedars-Sinai Guerin Children's, Los Angeles, CA, USA
- 7Department of Paediatrics, University of Cambridge, Cambridge, UK
- 8Department of Pediatrics, Cedars-Sinai Guerin Children's, Los Angeles, CA, USA
- 9The Francis Crick Institute, London, UK
- 10Faculty of Medicine, Heidelberg University, Heidelberg, Germany
- 11Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
- 12International School of Medicine, Istanbul Medipol University, Istanbul, Turkey
- 13Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
- 14Cell Fate Engineering and Disease Modeling Group, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany
- 15Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- 16HITBR Hector Institute for Translational Brain Research gGmbH, Heidelberg, Germany
- 17Division of AI in Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- 18Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
- 19Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- 20European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
- 21Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. [email protected]
- 22Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge, UK. [email protected]
Abstract
. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here we generated a deep single-cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across many regions. We identify that glioblastoma heterogeneity is driven by spatially patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalizes tumours into distinct tissue microenvironments and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Consistently, using a new deep-learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue microenvironments. We validate this cellular trajectory by using somatic mutation-based hierarchies in vivo and an experimental patient-derived organoid model ex vivo. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalized myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.
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BibTeX
@article{jong2026spatiotemporal,
title = {{A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity}},
author = {Grant de Jong and Fani Memi and Tannia Gracia and Olga Lazareva and Oliver Gould and Georgios Solomou and Alexander Aivazidis and Manàs Dave and Qianqian Zhang and Melanie Jensen and Ahmet Süreyya Rifaioğlu and João Diogo Barros-Silva and Sabine Eckert and Di Zhou and Yvette Wood and Elizabeth J. Tuck and Sezgin Er and Koen Rademaker and Robert Petryszak and Henry Marshall and Kenny Roberts and Andrew L. Trinh and Shreya Rai and Tyler Shaw and Ágnes Oszlánczi and Hayden Powell and Pavel Mazin and Stanislaw Makarchuk and Yinshui Chang and Katarzyna Kania and Liying Jin and Catherine L. Tudor and Hon Man Chan and Harriet F. Johnson and Benjamin Rumney and Holly E. Anderson and Jasmine Ellis and Vanessa Brito Pereira and Zoi Katsirea and Irfan Mamun and Ilaria Mulas and Annelies Quaegebeur and Mayen Briggs and Jessica Cox and Jimmy Tsz Hang Lee and Laura Rueda-Gensini and Manu Saraswat and Zaira Seferbevoka and Adam Young and Minal Patel and Tarryn Porter and Moritz Gerstung and Martin Prete and Elena Prigmore and Moritz Mall and Harry Bulstrode and Julio Sáez-Rodríguez and James Briscoe and David H. Rowitch and Richard James Mair},
journal = {Nature},
year = {2026},
month = nov,
doi = {10.1038/s41586-026-11234-8},
url = {https://doi.org/10.1038/s41586-026-11234-8},
note = {CC BY},
}
RIS
TY - JOUR
TI - A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity
AU - Grant de Jong
AU - Fani Memi
AU - Tannia Gracia
AU - Olga Lazareva
AU - Oliver Gould
AU - Georgios Solomou
AU - Alexander Aivazidis
AU - Manàs Dave
AU - Qianqian Zhang
AU - Melanie Jensen
AU - Ahmet Süreyya Rifaioğlu
AU - João Diogo Barros-Silva
AU - Sabine Eckert
AU - Di Zhou
AU - Yvette Wood
AU - Elizabeth J. Tuck
AU - Sezgin Er
AU - Koen Rademaker
AU - Robert Petryszak
AU - Henry Marshall
AU - Kenny Roberts
AU - Andrew L. Trinh
AU - Shreya Rai
AU - Tyler Shaw
AU - Ágnes Oszlánczi
AU - Hayden Powell
AU - Pavel Mazin
AU - Stanislaw Makarchuk
AU - Yinshui Chang
AU - Katarzyna Kania
AU - Liying Jin
AU - Catherine L. Tudor
AU - Hon Man Chan
AU - Harriet F. Johnson
AU - Benjamin Rumney
AU - Holly E. Anderson
AU - Jasmine Ellis
AU - Vanessa Brito Pereira
AU - Zoi Katsirea
AU - Irfan Mamun
AU - Ilaria Mulas
AU - Annelies Quaegebeur
AU - Mayen Briggs
AU - Jessica Cox
AU - Jimmy Tsz Hang Lee
AU - Laura Rueda-Gensini
AU - Manu Saraswat
AU - Zaira Seferbevoka
AU - Adam Young
AU - Minal Patel
AU - Tarryn Porter
AU - Moritz Gerstung
AU - Martin Prete
AU - Elena Prigmore
AU - Moritz Mall
AU - Harry Bulstrode
AU - Julio Sáez-Rodríguez
AU - James Briscoe
AU - David H. Rowitch
AU - Richard James Mair
PY - 2026
DA - 2026/11/04
JO - Nature
DO - 10.1038/s41586-026-11234-8
UR - https://doi.org/10.1038/s41586-026-11234-8
AB - . However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here we generated a deep single-cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across many regions. We identify that glioblastoma heterogeneity is driven by spatially patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalizes tumours into distinct tissue microenvironments and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Consistently, using a new deep-learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue microenvironments. We validate this cellular trajectory by using somatic mutation-based hierarchies in vivo and an experimental patient-derived organoid model ex vivo. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalized myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.
SN - 0028-0836
SN - 1476-4687
ER -