Abstract

Refractoriness to induction chemotherapy and relapse after achievement of remission are the main obstacles to cure in acute myeloid leukaemia (AML)1. After standard induction chemotherapy, patients are assigned to different post-remission strategies on the basis of cytogenetic and molecular abnormalities that broadly define adverse, intermediate and favourable risk categories2,3. However, some patients do not respond to induction therapy and another subset will eventually relapse despite the lack of adverse risk factors4. There is an urgent need for better biomarkers to identify these high-risk patients before starting induction chemotherapy, to enable testing of alternative induction strategies in clinical trials5. The high rate of relapse in AML has been attributed to the persistence of leukaemia stem cells (LSCs), which possess a number of stem cell properties, including quiescence, that are linked to therapy resistance6,7,8,9,10. Here, to develop predictive and/or prognostic biomarkers related to stemness, we generated a list of genes that are differentially expressed between 138 LSC+ and 89 LSC cell fractions from 78 AML patients validated by xenotransplantation. To extract the core transcriptional components of stemness relevant to clinical outcomes, we performed sparse regression analysis of LSC gene expression against survival in a large training cohort, generating a 17-gene LSC score (LSC17). The LSC17 score was highly prognostic in five independent cohorts comprising patients of diverse AML subtypes (n = 908) and contributed greatly to accurate prediction of initial therapy resistance. Patients with high LSC17 scores had poor outcomes with current treatments including allogeneic stem cell transplantation. The LSC17 score provides clinicians with a rapid and powerful tool to identify AML patients who do not benefit from standard therapy and who should be enrolled in trials evaluating novel upfront or post-remission strategies.

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Acknowledgements

This work was supported by grants from the Ontario Institute for Cancer Research with funds from the province of Ontario, the Cancer Stem Cell Consortium with funding from the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-047), and the Canadian Institutes of Health Research (CSC-105367), Canadian Cancer Society, Terry Fox Foundation, a Canada Research Chair to J.E.D., the Philip S. Orsino Chair in Leukemia Research to M.D.M., and a Collaborative Translational Cancer Research Grant from the Princess Margaret Cancer Centre (formerly Ontario Cancer Institute). This research was funded in part by the Leukemia & Lymphoma Society of Canada (493946) and the Stem Cell Network (492019), Ontario Graduate Scholarships, and the Ontario Ministry of Health and Long Term Care (OMOHLTC). The views expressed do not necessarily reflect those of the OMOHLTC. L.B. was supported in part by the Deutsche Forschungsgemeinschaft (Heisenberg-Professur BU 1339/8-1). T.H. was supported by the Wilhelm-Sander-Stiftung (grant 2013.086.1). K.M. and W.H. received grant support from Deutsche Forschungsgemeinschaft (DFG SFB 1243). We thank The Centre for Applied Genomics (Hospital for Sick Children) and the Princess Margaret Genomics Centre for the generation of GE data for the PM sorted cell fractions and validation cohort. We thank M. Pintilie for discussions regarding time-dependent covariates in survival analysis. We thank S. Geffroy for technical support and running the microarrays for the ALFA-0701 trial cohort.

Author information

Author notes

    • Stanley W. K. Ng
    • , Amanda Mitchell
    •  & James A. Kennedy

    These authors contributed equally to this work.

    • Thomas Büchner

    Deceased.

    • Mark D. Minden
    • , John E. Dick
    •  & Jean C. Y. Wang

    These authors jointly supervised this work.

Affiliations

  1. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 1A1, Canada

    • Stanley W. K. Ng
    •  & Peter W. Zandstra
  2. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2M9, Canada

    • Amanda Mitchell
    • , James A. Kennedy
    • , Weihsu C. Chen
    • , Jessica McLeod
    • , Narmin Ibrahimova
    • , Andrea Arruda
    • , Andreea Popescu
    • , Vikas Gupta
    • , Aaron D. Schimmer
    • , Andre C. Schuh
    • , Karen W. Yee
    • , Mark D. Minden
    • , John E. Dick
    •  & Jean C. Y. Wang
  3. Division of Medical Oncology and Hematology, Department of Medicine, University Health Network, Toronto, Ontario M5G 2M9, Canada

    • James A. Kennedy
    • , Vikas Gupta
    • , Aaron D. Schimmer
    • , Andre C. Schuh
    • , Karen W. Yee
    • , Mark D. Minden
    •  & Jean C. Y. Wang
  4. Department of Medicine, University of Toronto, Toronto, Ontario M5G 1A1, Canada

    • James A. Kennedy
    • , Vikas Gupta
    • , Aaron D. Schimmer
    • , Andre C. Schuh
    • , Karen W. Yee
    • , Mark D. Minden
    •  & Jean C. Y. Wang
  5. Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1A1, Canada

    • Aaron D. Schimmer
    •  & Mark D. Minden
  6. Department of Internal Medicine III, University Hospital of Ulm, 89081 Ulm, Germany

    • Lars Bullinger
  7. Department of Internal Medicine III, University of Munich, 81377 Munich, Germany

    • Tobias Herold
    • , Wolfgang Hiddemann
    •  & Klaus Metzeler
  8. German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany

    • Tobias Herold
    • , Wolfgang Hiddemann
    •  & Klaus Metzeler
  9. Institute of Biostatistics and Clinical Research, University of Münster, 48149 Münster, Germany

    • Dennis Görlich
  10. Department of Medicine, Hematology and Oncology, University of Münster, 48149 Münster, Germany

    • Thomas Büchner
    •  & Wolfgang E. Berdel
  11. Department of Hematology, Oncology and Tumor Immunology, Charité University Medicine, Campus Virchow, 10117 Berlin, Germany

    • Bernhard Wörmann
  12. Jean-Pierre AUBERT Research Center UMR-S 1172, Institute for Cancer Research Lille, 59045 Lille, France

    • Meyling Cheok
  13. University Hospital of Lille, Center of Pathology, Laboratory of Hematology, 59037 Lille, France

    • Claude Preudhomme
  14. Saint-Louis Hospital, Department of Hematology, University of Paris Diderot, 75010 Paris, France

    • Hervé Dombret
  15. Comprehensive Cancer Center Ulm, Institute of Experimental Cancer Research, University Hospital of Ulm, 89081 Ulm, Germany

    • Christian Buske
  16. Department of Hematology, Erasmus University Medical Centre, 3015 CE Rotterdam, the Netherlands

    • Bob Löwenberg
    •  & Peter J. M. Valk
  17. Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A1, Canada

    • John E. Dick

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Contributions

S.W.K.N. developed the signature derivation workflow, identified, refined and validated prognostic and predictive signatures, designed the custom NanoString assay, processed and analysed GE data, and performed statistical analyses and bioinformatics. A.M., W.C.C., J.M. and A.P. carried out functional xenograft transplantation, RNA extraction for GE analysis, and provided technical support for experiments. J.A.K., N.I., A.A., V.G., A.D.S., A.C.S., K.W.Y. and M.D.M. provided clinical annotations for the PM AML cohort. M.D.M. provided PM AML samples. S.W.K.N., J.C.Y.W., J.E.D. and M.D.M. interpreted the data. W.H., W.E.B., B.W., T.B., D.G., L.B., K.M., T.H. and C.B. provided clinical annotations for the GSE15434 and GSE12417 data sets. M.C., C.P. and H.D. provided GE and clinical data for the ALFA-0701 trial cohort. P.J.M.V. and B.L. provided clinical annotations for the GSE6891 data set. J.C.Y.W. and J.E.D. supervised the study. S.W.K.N. and J.C.Y.W. wrote the paper. A.M., J.A.K., P.W.Z., J.E.D. and M.D.M. revised the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Jean C. Y. Wang.

Reviewer Information Nature thanks F. Holstege, G. Schuurhuis and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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    Supplementary Information

    This file contains a Supplementary Discussion of the 17 LSC signature genes.

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https://doi.org/10.1038/nature20598

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