Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny1. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures. We infer that most cancer cells are differentiated along two specialized glial programs, whereas a rare subpopulation of cells is undifferentiated and associated with a neural stem cell expression program. Cells with expression signatures for proliferation are highly enriched in this rare subpopulation, consistent with a model in which CSCs are primarily responsible for fuelling the growth of oligodendroglioma in humans. Analysis of copy number variation (CNV) shows that distinct CNV sub-clones within tumours display similar cellular hierarchies, suggesting that the architecture of oligodendroglioma is primarily dictated by developmental programs. Subclonal point mutation analysis supports a similar model, although a full phylogenetic tree would be required to definitively determine the effect of genetic evolution on the inferred hierarchies. Our single-cell analyses provide insight into the cellular architecture of oligodendrogliomas at single-cell resolution and support the cancer stem cell model, with substantial implications for disease management.

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  1. 1.

    & Evolution of the cancer stem cell model. Cell Stem Cell 14, 275–291 (2014)

  2. 2.

    , , , & Cancer stem cells in glioblastoma. Genes Dev . 29, 1203–1217 (2015)

  3. 3.

    et al. Dedifferentiation of neurons and astrocytes by oncogenes can induce gliomas in mice. Science 338, 1080–1084 (2012)

  4. 4.

    , , & WHO Classification of Tumors of the Central Nervous System 4th edn (IARC, 2016)

  5. 5.

    et al. Full-length RNA-seq from single cells using Smart-seq2. Nature Protocols 9, 171–181 (2014)

  6. 6.

    et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396–1401 (2014)

  7. 7.

    et al. Identification of a unique TGF-β-dependent molecular and functional signature in microglia. Nature Neurosci . 17, 131–143 (2014)

  8. 8.

    et al. Expression of oligodendroglial and astrocytic lineage markers in diffuse gliomas: use of YKL-40, ApoE, ASCL1, and NKX2-2. J. Neuropathol. Exp. Neurol. 65, 1149–1156 (2006)

  9. 9.

    et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34, 11929–11947 (2014)

  10. 10.

    et al. The chromatin remodeler CHD7 regulates adult neurogenesis via activation of SoxC transcription factors. Cell Stem Cell 13, 62–72 (2013)

  11. 11.

    et al. Autocrine TGF-β signaling maintains tumorigenicity of glioma-initiating cells through Sry-related HMG-box factors. Cell Stem Cell 5, 504–514 (2009)

  12. 12.

    et al. Reconstructing and reprogramming the tumor-propagating potential of glioblastoma stem-like cells. Cell 157, 580–594 (2014)

  13. 13.

    et al. An aberrant transcription factor network essential for Wnt signaling and stem cell maintenance in glioblastoma. Cell Reports 3, 1567–1579 (2013)

  14. 14.

    , & Epigenetic reprogramming in cancer. Science 339, 1567–1570 (2013)

  15. 15.

    et al. Transcriptional landscape of the prenatal human brain. Nature 508, 199–206 (2014)

  16. 16.

    et al. A survey of human brain transcriptome diversity at the single cell level. Proc. Natl Acad. Sci. USA 112, 7285–7290 (2015)

  17. 17.

    et al. Asymmetry-defective oligodendrocyte progenitors are glioma precursors. Cancer Cell 20, 328–340 (2011)

  18. 18.

    et al. Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron 89, 37–53 (2016)

  19. 19.

    et al. Single-cell RNA-seq with waterfall reveals molecular cascades underlying adult neurogenesis. Cell Stem Cell 17, 360–372 (2015)

  20. 20.

    et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015)

  21. 21.

    et al. Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells. Genome Res . 25, 1860–1872 (2015)

  22. 22.

    The Cancer Genome Atlas Research Network Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N. Engl. J. Med. 372, 2481–2498 (2015)

  23. 23.

    & Cdks and cyclins link G1 length and differentiation of embryonic, neural and hematopoietic stem cells. Cell Cycle 9, 1893–1900 (2010)

  24. 24.

    et al. The critical role of cyclin D2 in cell cycle progression and tumorigenicity of glioblastoma stem cells. Oncogene 32, 3840–3845 (2013)

  25. 25.

    et al. Absolute quantification of somatic DNA alterations in human cancer. Nature Biotechnol . 30, 413–421 (2012)

  26. 26.

    et al. Mutations in CIC and FUBP1 contribute to human oligodendroglioma. Science 333, 1453–1455 (2011)

  27. 27.

    , , , & ETV/Pea3 family transcription factor-encoding genes are overexpressed in CIC-mutant oligodendrogliomas. Genes Chromosom. Cancer 54, 725–733 (2015)

  28. 28.

    et al. Mosaic analysis with double markers reveals tumor cell of origin in glioma. Cell 146, 209–221 (2011)

  29. 29.

    , , , & Spatial reconstruction of single-cell gene expression data. Nature Biotechnol . 33, 495–502 (2015)

  30. 30.

    et al. Glioma test array for use with formalin-fixed, paraffin-embedded tissue: array comparative genomic hybridization correlates with loss of heterozygosity and fluorescence in situ hybridization. J. Mol. Diagn. 8, 268–276 (2006)

  31. 31.

    & RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011)

  32. 32.

    et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510, 363–369 (2014)

  33. 33.

    et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol. Biol. Cell 13, 1977–2000 (2002)

  34. 34.

    & Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

  35. 35.

    et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res . 20, 1297–1303 (2010)

  36. 36.

    et al. ContEst: estimating cross-contamination of human samples in next-generation sequencing data. Bioinformatics 27, 2601–2602 (2011)

  37. 37.

    et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nature Biotechnol . 31, 213–219 (2013)

  38. 38.

    et al. Discovery and characterization of artifactual mutations in deep coverage targeted capture sequencing data due to oxidative DNA damage during sample preparation. Nucleic Acids Res . 41, e67 (2013)

  39. 39.

    et al. Oncotator: cancer variant annotation tool. Hum. Mutat. 36, E2423–E2429 (2015)

  40. 40.

    et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

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We thank L. Gaffney for graphic support. This work was supported by grants from the National Brain Tumor Society (to M.L.S. and D.N.L.), the Smith Family Foundation (to M.L.S.), NIH-NCI SPORE on brain cancer Career Enhancement Project and Developmental Research Project (to M.L.S.), the Broad Institute Broadnext10 program (to M.L.S. and O.R.R.), the American Cancer Society (to M.L.S.) and start-up funds from the MGH department of Pathology. A.S.V. was supported by the NIH R25 fellowship (NS065743) and research grants from the American Brain Tumor Association and Neurosurgery Research and Education Foundation. I.T. was supported by a Human Frontier Science Program fellowship and a Rothschild fellowship. A.R. was supported by funds from the Howard Hughes Medicine Institute, the Klarman Cell Observatory, STARR cancer consortium, NCI grant 1U24CA180922, by the Koch Institute Support (core) grant P30-CA14051 from the National Cancer Institute, the Ludwig Center and the Broad Institute. A.R. is a scientific advisory board member for ThermoFisher Scientific and Syros Pharmaceuticals and a consultant for Driver Group. Flow cytometry and sorting services were supported by shared instrumentation grant 1S10RR023440-01A1. M.M. was supported by the California Institute of Regenerative Medicine (CIRM) grants RB4-06093 and RN3-06510 and the Virginia and D.K. Ludwig Fund for Cancer Research.

Author information

Author notes

    • Itay Tirosh
    •  & Andrew S. Venteicher

    These authors contributed equally to this work.

    • Aviv Regev
    •  & Mario L. Suvà

    These authors jointly supervised this work.


  1. Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA

    • Itay Tirosh
    • , Andrew S. Venteicher
    • , Christine Hebert
    • , Leah E. Escalante
    • , Keren Yizhak
    • , Jonathan M. Fisher
    • , Christopher Rodman
    • , Mariella G. Filbin
    • , Cyril Neftel
    • , Jackson Nyman
    • , Benjamin Izar
    • , Joshua M. Francis
    • , Kenneth J. Livak
    • , Dave Gennert
    • , Rahul Satija
    • , Todd R. Golub
    • , Miguel N. Rivera
    • , Gad Getz
    • , Orit Rozenblatt-Rosen
    • , Bradley E. Bernstein
    • , Aviv Regev
    •  & Mario L. Suvà
  2. Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA

    • Andrew S. Venteicher
    • , Christine Hebert
    • , Leah E. Escalante
    • , Keren Yizhak
    • , Mariella G. Filbin
    • , Cyril Neftel
    • , Niyati Desai
    • , Christina C. Luo
    • , Aanand A. Patel
    • , Maristela L. Onozato
    • , Nicolo Riggi
    • , Ravindra Mylvaganam
    • , A. John Iafrate
    • , Matthew P. Frosch
    • , Miguel N. Rivera
    • , Gad Getz
    • , Bradley E. Bernstein
    • , David N. Louis
    •  & Mario L. Suvà
  3. Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA

    • Andrew S. Venteicher
    • , Anoop P. Patel
    • , Brian V. Nahed
    • , William T. Curry
    • , Robert L. Martuza
    •  & Daniel P. Cahill
  4. Departments of Neurology, Neurosurgery, Pediatrics and Pathology, Stanford University School of Medicine, Stanford, California 94305, USA

    • Christopher Mount
    •  & Michelle Monje
  5. Department of Pediatric Oncology, Dana-Farber Cancer Institute and Children’s Hospital Cancer Center, Boston, Massachusetts 02215, USA

    • Mariella G. Filbin
    •  & Todd R. Golub
  6. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA

    • Joshua M. Francis
  7. Howard Hughes Medical Institute, Koch Institute, Department of Biology, MIT, Cambridge, Massachusetts 02139, USA

    • Todd R. Golub
    •  & Aviv Regev


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I.T., A.S.V., A.R. and M.L.S. conceived the project, designed the study, and interpreted results. A.S.V., C.H., L.E.E. and C.N. collected single cells and generated single-cell sequencing data. I.T. performed computational analyses. J.M.Fra, K.Y. and G.G. provided support for genomic and genetic analyses. J.M.Fis, C.R. and K.J.L. designed and performed qPCR experiments. C.C.L. and R.M. provided flow cytometry expertise. C.M. and M.M. developed normal human cell cultures used in the study. N.D., N.R., M.N.R., M.L.O. and A.J.I. performed in situ hybridization and FISH experiments. A.P.P., A.A.P., D.G., B.I., J.N., R.S., M.G.F., B.V.N., D.P.C., W.T.C., R.L.M., M.P.F., O.R.R., T. R.G., B.E.B. and D.N.L. provided experimental and analytical support. I.T., A.R. and M.L.S. wrote the manuscript with feedback from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Aviv Regev or Mario L. Suvà.

Reviewer Information Nature thanks P. Dirks, J. Rich and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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