Genetic heterogeneity contributes to clinical outcome and progression of most tumors, but little is known about allelic diversity for epigenetic compartments, and almost no data exist for acute myeloid leukemia (AML). We examined epigenetic heterogeneity as assessed by cytosine methylation within defined genomic loci with four CpGs (epialleles), somatic mutations, and transcriptomes of AML patient samples at serial time points. We observed that epigenetic allele burden is linked to inferior outcome and varies considerably during disease progression. Epigenetic and genetic allelic burden and patterning followed different patterns and kinetics during disease progression. We observed a subset of AMLs with high epiallele and low somatic mutation burden at diagnosis, a subset with high somatic mutation and lower epiallele burdens at diagnosis, and a subset with a mixed profile, suggesting distinct modes of tumor heterogeneity. Genes linked to promoter-associated epiallele shifts during tumor progression showed increased single-cell transcriptional variance and differential expression, suggesting functional impact on gene regulation. Thus, genetic and epigenetic heterogeneity can occur with distinct kinetics likely to affect the biological and clinical features of tumors.

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We thank J. Phillips, J. Ishii, L. Wang, J. Busuttil, T. Lee, P. Zumbo, J. Gandara, and A. Zeilemaker for technical support; C. Sheridan for technical support, assistance with organization, and maintenance of sample database and banking; M. Perugini, D. Iarossi, and I.S. Tiong for assistance with clinical database management; and Y. Neelamraju, Z. Li, J. Glass, and M.R. De Massy for data annotation and management. Next-generation sequencing protocols and sequencing were performed by the Weill Cornell Medicine Epigenomics Core and the New York Genome Center. We thank A. Viale from the Integrated Genomics Operation and N. Socci from the bioinformatics core at Memorial Sloan Kettering Cancer Center for sequencing services. We thank the South Australian Cancer Research Biobank for access to clinical samples. We thank F. Michor for recommendations regarding data analyses. This work was supported by Starr Cancer Consortium grant I4-A442 (A.M.M., R.L., and C.E.M.), STARR Cancer Consortium grant I7-A765 and I9-A9-071 (C.E.M.), the Irma T. Hirschl and Monique Weill-Caulier Charitable Trusts, Bert L. and N. Kuggie Vallee Foundation and the WorldQuant Foundation, Pershing Square Sohn Cancer Research Alliance, and NASA (NNX14AH50G) (C.E.M.); LLS SCOR 7006-13 (A.M.M.); NCI K08CA169055 (F.E.G.-B.); an American Society of Hematology (ASHAMFDP-20121) award under the ASH-AMFDP partnership with the Robert Wood Johnson Foundation and ASH/EHA TRTH (F.E.G.-B.); a Doris Duke Medical Foundation, Leukemia and Lymphoma Society Translational Research Program, and Geoffrey Beene Cancer Center (C.Y.P.); a Leukaemia and Lymphoma Research award (D.G. and R. Dillon); German Research Foundation (DFG) grant SFB 1074 (project B3; K.D. and L.B.); DFG Heisenberg-Stipendium BU 1339/3-1 (L.B.); an Australian National Health and Medical Research Council and the Royal Adelaide Hospital Contributing Haematologists Fund financial support (R.J.D., A.L.B., and I.D.L.); US National Institutes of Health R01CA102031 (G.J.R. and M.L.G.) and R01NS076465 (C.E.M. and A.M.M.); and Leukemia Fighters funding (G.J.R., M.L.G., and D.C.H.).

Author information

Author notes

    • Sheng Li

    Present address: Department of Neurosurgery, Weill Cornell Medicine, New York, New York, USA.

    • Sheng Li
    •  & Francine E Garrett-Bakelman

    These authors contributed equally to this work.


  1. Department of Physiology and Biophysics and the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York, USA.

    • Sheng Li
    •  & Christopher E Mason
  2. Division of Hematology–Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, New York, USA.

    • Francine E Garrett-Bakelman
    • , Monica L Guzman
    • , Duane C Hassane
    • , Gail J Roboz
    •  & Ari M Melnick
  3. Leukemia Service, Department of Medicine, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Stephen S Chung
    • , Todd Hricik
    • , Franck Rapaport
    • , Jay Patel
    •  & Ross Levine
  4. Erasmus University Medical Center, Department of Hematology, Rotterdam, the Netherlands.

    • Mathijs A Sanders
    • , Ruud Delwel
    • , Bob Löwenberg
    •  & Peter J M Valk
  5. Department of Medical and Molecular Genetics, King's College London, Faculty of Life Sciences and Medicine, London, UK.

    • Richard Dillon
    •  & David Grimwade
  6. Tri-Institutional Training Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, New York, USA.

    • Priyanka Vijay
  7. Center for Cancer Biology, SA Pathology and University of South Australia, Adelaide, South Australia, Australia.

    • Anna L Brown
    • , Ian D Lewis
    •  & Richard J D'Andrea
  8. School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, South Australia, Australia.

    • Anna L Brown
    •  & Richard J D'Andrea
  9. Department of Hematology, SA Pathology and Royal Adelaide Hospital, Adelaide, South Australia, Australia.

    • Anna L Brown
    • , Ian D Lewis
    • , Luen Bik To
    •  & Richard J D'Andrea
  10. Division of Hematology and Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

    • Alexander E Perl
    • , Joy Cannon
    • , Selina Luger
    •  & Martin Carroll
  11. Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany.

    • Lars Bullinger
    • , Hartmut Döhner
    •  & Konstanze Döhner
  12. University of Rochester Medical Center, Rochester, New York, USA.

    • Michael Becker
  13. School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.

    • Ian D Lewis
    •  & Luen Bik To
  14. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Christopher Y Park
  15. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Christopher Y Park
  16. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Donna Neuberg
  17. The Feil Family Brain and Mind Research Institute, New York, New York, USA.

    • Christopher E Mason


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A.M.M. and C.E.M. conceived of the studies, designed analytical approaches, analyzed results, wrote the manuscript, and designed experiments with F.E.G.-B. S. Li conceived of computational analyses, wrote code and performed computational analysis, wrote the manuscript, and generated figures. F.E.G.-B. performed, coordinated and/or supervised all patient sample experimental procedures, performed computational and bench experimental data management and analyses, and wrote manuscript. S.S.C. and R. Dillon performed experiments (flow cytometry and sorting of subject samples) and associated data analysis. T.H., F.R., and J.P. performed computational analyses. M.A.S. and P.J.M.V. performed experiments (exome capture) and associated computational analysis. A.L.B., A.E.P., J.C., L.B., S. Luger, M.B., I.D.L., L.B.T., B.L., H.D., K.D., P.J.M.V., R.J.D., and M.C. coordinated patient sample collection and analyzed clinical data. D.N. assisted with statistical analyses. P.V. performed single-cell RNA-seq library preparation. R. Delwel, M.L.G., D.C.H., G.J.R., D.G., C.Y.P., and R.L. helped with sample collection, writing, analysis, and patient annotation. All authors read, edited, and approved the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ari M Melnick or Christopher E Mason.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Methods and Supplementary Figures 1–10

Excel files

  1. 1.

    Supplementary Table 1

    Summary of patient characteristics

  2. 2.

    Supplementary Table 2

    Detailed description of patient characteristics and genomics assays performed

  3. 3.

    Supplementary Table 3

    Sequencing statistics from ERRBS

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    Supplementary Table 4

    Sequencing statistics from genomic sequencing

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    Supplementary Table 5

    Patterns of EPM and genetic changes in epigenetic clusters 1 and 3

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    Supplementary Table 6

    Somatic mutations in recurrently affected AML genes

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    Supplementary Table 7

    Sequencing statistics from RNA-seq

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    Supplementary Table 8

    Differentially expressed genes between epigenetic clusters 3 and 1

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    Supplementary Table 9

    GO term enrichment analysis of differentially expressed genes between epigenetic clusters 1 and 3

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    Supplementary Table 10

    Somatic mutations gained in AML_130 at first relapse time point (T2)

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    Supplementary Table 11

    Somatic mutations detected in AML_130 at time points T1–T5

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    Supplementary Table 12

    Genes associated with eloci linked to clinical outcomes

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