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Stem cell gene expression programs influence clinical outcome in human leukemia

Nature Medicine volume 17, pages 1086–1093 (2011)Cite this article

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Abstract

Xenograft studies indicate that some solid tumors and leukemias are organized as cellular hierarchies sustained by cancer stem cells (CSCs). Despite the promise of the CSC model, its relevance in humans remains uncertain. Here we show that acute myeloid leukemia (AML) follows a CSC model on the basis of sorting multiple populations from each of 16 primary human AML samples and identifying which contain leukemia stem cells (LSCs) using a sensitive xenograft assay. Analysis of gene expression from all functionally validated populations yielded an LSC-specific signature. Similarly, a hematopoietic stem cell (HSC) gene signature was established. Bioinformatic analysis identified a core transcriptional program shared by LSCs and HSCs, revealing the molecular machinery underlying 'stemness' properties. Both stem cell programs were highly significant independent predictors of patient survival and were found in existing prognostic signatures. Thus, determinants of stemness influence the clinical outcome of AML, establishing that LSCs are clinically relevant and not artifacts of xenotransplantation.

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Figure 1: Strategy of transcriptional profiling of stem cell fractions identified by function.
Figure 2: Correlation between LSC-R and HSC-R.
Figure 3: LSC-R and HSC-R gene signatures are correlated with disease outcome.
Figure 4: Correlation of LSC and HSC gene expression signatures and molecular risk status with overall survival in a cohort of cytogenetically normal AML samples.

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Acknowledgements

This work was in part supported by grants from the German Ministry of Education and Research (BMBF; C.B. and S.K.B., 01GS0448 and 01GS0876); the Deutsche Forschungsgemeinschaft (C.B., BU-1177/3-1); Ontario Research Fund (I.J., GL2-01-030); a fellowship (K.E.) and grants (J.E.D.) from the Leukemia and Lymphoma Society; the Stem Cell Network of Canadian National Centres of Excellence (J.E.D.); the Canadian Cancer Society Research Institute (J.E.D.); Ministry of Education, Culture, Sports, Science and Technology in Japan (20591134, K.T.); the Terry Fox Foundation (J.E.D.); Genome Canada through the Ontario Genomics Institute (J.E.D.); Ontario Institute for Cancer Research with funds from the province of Ontario (J.E.D.); the Canadian Institutes for Health Research (J.E.D.); and a Canada Research Chair (J.E.D. and I.J.). Computational resources were supported in part by Canada Foundation for Innovation (12301 and 203383) and IBM (I.J.). This research was funded in part by the Ontario Ministry of Health and Long-Term Care (OMOHLTC). The views expressed do not necessarily reflect those of OMOHLTC.

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Author notes

  1. Katsuto Takenaka, Eric R Lechman, Levi Waldron and Björn Nilsson: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Stem Cell and Developmental Biology, University Health Network and Department of Molecular Genetics, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University of Toronto, Toronto, Ontario, Canada

    Kolja Eppert, Eric R Lechman, Peter van Galen, Armando Poeppl & John E Dick

  2. Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan

    Katsuto Takenaka

  3. University Health Network and Department of Medical Biophysics, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University of Toronto, Toronto, Ontario, Canada

    Levi Waldron & Igor Jurisica

  4. Brigham and Women's Hospital, Boston, Massachusetts, USA

    Björn Nilsson & Benjamin L Ebert

  5. Department of Internal Medicine III, Ludwig-Maximilians-Universität, Munich, Germany

    Klaus H Metzeler & Stefan K Bohlander

  6. Population Health Sciences, Research Institute, Hospital for Sick Children, Toronto, Ontario, Canada

    Vicki Ling & Joseph Beyene

  7. Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada

    Angelo J Canty

  8. Hospital for Sick Children and Department of Immunology and Department of Medical Biophysics, Program in Genetics and Genome Biology, University of Toronto, Toronto, Ontario, Canada

    Jayne S Danska

  9. Institute of Experimental Cancer Research, Comprehensive Cancer Center, University Hospital of Ulm, Ulm, Germany

    Christian Buske

  10. Department of Medicine, University Health Network, Toronto, Ontario, Canada

    Mark D Minden

  11. Broad Institute, Cambridge, Massachusetts, USA

    Todd R Golub

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  1. Kolja Eppert
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Contributions

K.E., E.R.L., K.T., B.L.E. and J.E.D. designed the study. K.E., E.R.L., P.v.G., K.T. and A.P. carried out experiments. K.E., K.T., L.W., B.N., E.R.L., P.v.G., V.L. and I.J. analyzed and interpreted data. K.E., J.B., A.J.C., J.S.D., S.K.B., K.H.M., C.B., M.D.M., T.R.G., I.J., B.L.E. and J.E.D. provided research support and conceptual advice. M.D.M. provided samples. K.E. and J.E.D. wrote the paper. E.R.L., K.T., K.H.M., J.S.D., S.K.B., C.B., M.D.M., I.J. and B.L.E. revised the paper.

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Correspondence to John E Dick.

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Eppert, K., Takenaka, K., Lechman, E. et al. Stem cell gene expression programs influence clinical outcome in human leukemia. Nat Med 17, 1086–1093 (2011). https://doi.org/10.1038/nm.2415

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