Abstract

Human glioblastomas harbour a subpopulation of glioblastoma stem cells that drive tumorigenesis. However, the origin of intratumoural functional heterogeneity between glioblastoma cells remains poorly understood. Here we study the clonal evolution of barcoded glioblastoma cells in an unbiased way following serial xenotransplantation to define their individual fate behaviours. Independent of an evolving mutational signature, we show that the growth of glioblastoma clones in vivo is consistent with a remarkably neutral process involving a conserved proliferative hierarchy rooted in glioblastoma stem cells. In this model, slow-cycling stem-like cells give rise to a more rapidly cycling progenitor population with extensive self-maintenance capacity, which in turn generates non-proliferative cells. We also identify rare ‘outlier’ clones that deviate from these dynamics, and further show that chemotherapy facilitates the expansion of pre-existing drug-resistant glioblastoma stem cells. Finally, we show that functionally distinct glioblastoma stem cells can be separately targeted using epigenetic compounds, suggesting new avenues for glioblastoma-targeted therapy.

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Acknowledgements

We thank R. D. Corbett, P. Plettner, N. Khuu and G. Edin for technical advice, the SickKids-UHN Flow Cytometry Facility for assistance with fluorescence-activated cell sorting, SickKids Laboratory Animal Services for animal housing and veterinary support, and The Centre for Applied Genomics, Princess Margaret Genomics Centre, and Canada’s Michael Smith Genome Sciences Centre for sequencing and bioinformatics support. This study was supported by the Canadian Institutes of Health Research (funding reference number 142434), the Ontario Institute for Cancer Research through funding provided by the Government of Ontario, and Stand Up To Cancer (SU2C) Canada. P.B.D. is also supported by the Terry Fox Research Institute, the Canadian Cancer Society, the Hospital for Sick Children Foundation, Jessica’s Footprint Foundation, the Hopeful Minds Foundation, the Bresler family, and B.R.A.I.N. Child. P.B.D. holds a Garron Family Chair in Childhood Cancer Research at The Hospital for Sick Children. B.D.S. acknowledges the support of the Wellcome Trust (grant number 098357/Z/12/Z). C.J.E. acknowledges grant support from the Canadian Cancer Society and the Terry Fox Run. Research was supported by SU2C Canada Cancer Stem Cell Dream Team Research Funding (SU2C-AACR-DT-19-15) provided by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, with supplementary support from the Ontario Institute for Cancer Research through funding provided by the Government of Ontario. Stand Up To Cancer Canada is a program of the Entertainment Industry Foundation Canada. Research funding is administered by the American Association for Cancer Research International – Canada, the scientific partner of SU2C Canada. The Structural Genomics Consortium is funded by AbbVie, Bayer, Boehringer Ingelheim, GSK, Genome Canada, Ontario Genomics Institute, Janssen, Lilly, Merck, Novartis, the government of Ontario, Pfizer, Takeda, and the Wellcome Trust.

Author information

Author notes

    • Benjamin D. Simons
    •  & Peter B. Dirks

    These authors jointly supervised this work.

Affiliations

  1. Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada

    • Xiaoyang Lan
    • , Florence M. G. Cavalli
    • , Robert J. Vanner
    • , Lilian Lee
    • , Michelle M. Kushida
    • , Nicole I. Park
    • , Fiona J. Coutinho
    • , Heather Whetstone
    • , Hayden J. Selvadurai
    • , Clare Che
    • , Betty Luu
    • , Naghmeh Rastegar
    • , Renee Head
    • , Sonam Dolma
    • , Michael D. Taylor
    •  & Peter B. Dirks
  2. The Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada

    • Xiaoyang Lan
    • , Florence M. G. Cavalli
    • , Robert J. Vanner
    • , Lilian Lee
    • , Michelle M. Kushida
    • , Nicole I. Park
    • , Fiona J. Coutinho
    • , Heather Whetstone
    • , Hayden J. Selvadurai
    • , Clare Che
    • , Betty Luu
    • , Naghmeh Rastegar
    • , Renee Head
    • , Sonam Dolma
    • , Michael D. Taylor
    •  & Peter B. Dirks
  3. Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada

    • Xiaoyang Lan
    • , Robert J. Vanner
    • , Nicole I. Park
    • , Fiona J. Coutinho
    •  & Peter B. Dirks
  4. Cavendish Laboratory, Department of Physics, J. J. Thomson Avenue, Cambridge CB3 0HE, UK

    • David J. Jörg
    •  & Benjamin D. Simons
  5. The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge CB2 1QN, UK

    • David J. Jörg
    •  & Benjamin D. Simons
  6. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2M9, Canada

    • Laura M. Richards
    • , Paul Guilhamon
    • , Mathieu Lupien
    •  & Trevor J. Pugh
  7. Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada

    • Laura M. Richards
    • , Paul Guilhamon
    • , Panagiotis Prinos
    • , Cheryl H. Arrowsmith
    • , Mathieu Lupien
    •  & Trevor J. Pugh
  8. Terry Fox Laboratory, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada

    • Long V. Nguyen
    • , Davide Pellacani
    •  & Connie J. Eaves
  9. Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada

    • Paul Guilhamon
    •  & Mathieu Lupien
  10. Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6T 2B5, Canada

    • Davide Pellacani
    •  & Connie J. Eaves
  11. Centre for High-Throughput Biology, Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada

    • Annaick Carles
    • , Michelle Moksa
    •  & Martin Hirst
  12. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario M5G 0A4, Canada

    • Sonam Dolma
    • , Michael D. Taylor
    •  & Peter B. Dirks
  13. Structural Genomics Consortium, University of Toronto, Toronto, Ontario M5G 1L7, Canada

    • Panagiotis Prinos
    •  & Cheryl H. Arrowsmith
  14. Division of Neurosurgery, St. Michael’s Hospital, Toronto, Ontario M5B 1W8, Canada

    • Michael D. Cusimano
    •  & Sunit Das
  15. Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario M5S 1A8, Canada

    • Michael D. Cusimano
    • , Sunit Das
    • , Mark Bernstein
    • , Michael D. Taylor
    •  & Peter B. Dirks
  16. Division of Neurosurgery, Toronto Western Hospital, Toronto, Ontario M5T 2S8, Canada

    • Mark Bernstein
  17. Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada

    • Andrew J. Mungall
    • , Richard A. Moore
    • , Yussanne Ma
    •  & Martin Hirst
  18. Departments of Physiology and Pharmacology, Biochemistry and Molecular Biology, Alberta Children’s Hospital Research Institute, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta T2N 4N1, Canada

    • Marco Gallo
  19. Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario M5S 3E1, Canada

    • Michael D. Taylor
    •  & Peter B. Dirks
  20. The Wellcome Trust/Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK

    • Benjamin D. Simons

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Contributions

X.L. and P.B.D. conceptualized the study and were assisted by L.V.N., R.J.V., N.I.P., F.J.C., H.J.S., M.G. and C.J.E. in experimental design. P.B.D. and B.D.S. supervised the study. X.L. performed in vivo and in vitro barcoding experiments and drug validation studies. D.J.J., B.D.S., X.L., D.P., A.C. and P.B.D. analysed and interpreted barcoding results. D.J.J. and B.D.S. developed the theoretical model of tumour growth, performed simulations and wrote the supplemental theory section. F.M.G.C., L.M.R., M.D.T. and T.J.P. analysed whole-exome sequencing and RNA sequencing results. P.G. and M.L. performed ATAC–seq and analysed results. R.J.V., L.L., M.M.K., N.I.P., F.J.C., H.W., C.C., B.L., N.R., R.H. and S. Do assisted in performing the experiments. M.M., A.J.M., R.A.M., Y.M. and M.H. oversaw the generation of sequencing data. L.V.N. and C.J.E. designed, generated, and validated the barcode library. P.P. and C.H.A. assisted with in vitro drug assays. M.D.C., S. Da and M.B. contributed all GBM tumour samples used in the study. X.L., D.J.J., C.J.E., B.D.S. and P.B.D. wrote the manuscript, and all authors contributed to data interpretation and approved the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Benjamin D. Simons or Peter B. Dirks.

Reviewer Information Nature thanks T. Graham, J. Seoane, M. Suva and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Theory

    This file contains the Supplementary Theory section, which details the quantitative analysis of barcoding data that led to our minimal model of GBM growth, and the stochastic simulation strategy used to test the model predictions. It further describes how the clone survival and cross-correlation values obtained from simulation results are compared with experimental findings. Building upon the minimal model, a potential explanation for the existence of Group B clones (resistance to apoptosis) is also presented. Lastly, the use of exome sequencing analysis of xenografts as an additional consistency check for the model is described.

  2. 2.

    Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    This file contains the normalized clone size quantification of barcoded xenografts for the GBM-719, -729, -735, -742, -743, and -754 series. The data is related to Figure 2 and Extended Data Figures 4-6.

  2. 2.

    Supplementary Table 2

    This file contains clone growth trajectories derived from an instance of the stochastic simulation algorithm, as well as the change in mean clone size over time. The data is represented graphically in Figure 2d and Figure S1 in the Supplementary Theory.

  3. 3.

    Supplementary Table 3

    This file contains the experimental and simulated clone survival probability values for the GBM-719, -742, and -754 series. The data is related to Figure 2g and Figure S2 in the Supplementary Theory.

  4. 4.

    Supplementary Table 4

    This file contains the experimental and simulated clone size cross correlation values for the GBM-719, -742, and -754 series. The data is related to Figure 2f and Figure S3 in the Supplementary Theory.

  5. 5.

    Supplementary Table 5

    This file contains the first incomplete moment distribution obtained from the stochastic simulation algorithm with random induction times. The data is related to Figure S4 in the Supplementary Theory.

  6. 6.

    Supplementary Table 6

    This file contains the normalized clone size quantification for the proliferation assay from (1)754 culture. The data is related to Extended Data Figure 7d-f.

  7. 7.

    Supplementary Table 7

    This file contains the normalized clone size quantification for the additional xenograft-derived cultures. The data is related to Extended Data Figure 8.

  8. 8.

    Supplementary Table 8

    This file contains the normalized clone size quantification for the drug screen using (1)754 culture. The data is related to Figure 3g, Extended Data Figure 9c-d and Extended Data Figure 10.

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DOI

https://doi.org/10.1038/nature23666

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