Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

Chronic myeloproliferative neoplasms

Ongoing clonal evolution in chronic myelomonocytic leukemia on hypomethylating agents: a computational perspective

Leukemia volume 32, pages 2049–2054 (2018)Cite this article

Subjects

To the Editor:

Chronic myelomonocytic leukemia (CMML) is a clinically heterogeneous myeloid neoplasm that combines myelodysplastic and myeloproliferative features, and carries a poor prognosis due to progression to acute myeloid leukemia or complications of cytopenias. TET2, SRSF2, and ASXL1 are the most commonly mutated genes in CMML, but somatic variants in additional genes have been identified [1,2,3]. Allogeneic stem cell transplantation is potentially curative, but most patients are ineligible due to advanced age and/or co-morbidities. Hypomethylating agents (HMAs), such as 5-azacitidine (5-Aza) induce responses in ~40% of CMML patients, but their impact on survival remains debatable [4]. While TET2 mutations have been reported to predict HMA response in myelodysplastic syndromes, data from patients treated with decitabine suggest that epigenetic profiles rather than somatic mutations govern response to HMAs in CMML [5, 6]. Previous work described unchanged mutant allele burden in CMML in patients responding to HMAs [1], but detailed analyses of clonal evolution in relation to HMA response have not been reported. We applied SubcloneSeeker computational analysis algorithm to whole-exome sequencing (WES) and single-nucleotide polymorphism (SNP) array data to uncover clonal architecture and evolution in CMML patients treated with 5-Aza on a prospective trial [7]. Compared to targeted sequencing, this approach allows reconstruction of clonal architecture using all somatic mutation calls, including driver and passenger mutations, in an unbiased fashion.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2

References

  1. Merlevede J, Droin N, Qin T, Meldi K, Yoshida K, Morabito M, et al. Mutation allele burden remains unchanged in chronic myelomonocytic leukaemia responding to hypomethylating agents. Nat Commun. 2016;7:10767.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Mason CC, Khorashad JS, Tantravahi SK, Kelley TW, Zabriskie MS, Yan D, et al. Age-related mutations and chronic myelomonocytic leukemia. Leukemia. 2016;30:906–13.

    Article  PubMed  CAS  Google Scholar 

  3. Yoshida K, Sanada M, Shiraishi Y, Nowak D, Nagata Y, Yamamoto R, et al. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature. 2011;478:64–9.

    Article  PubMed  CAS  Google Scholar 

  4. Fenaux P, Mufti GJ, Hellstrom-Lindberg E, Santini V, Finelli C, Giagounidis A, et al. Efficacy of azacitidine compared with that of conventional care regimens in the treatment of higher-risk myelodysplastic syndromes: a randomised, open-label, phase III study. Lancet Oncol. 2009;10:223–32.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Meldi K, Qin T, Buchi F, Droin N, Sotzen J, Micol JB, et al. Specific molecular signatures predict decitabine response in chronic myelomonocytic leukemia. J Clin Invest. 2015;125:1857–72.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Bejar R, Lord A, Stevenson K, Bar-Natan M, Perez-Ladaga A, Zaneveld J, et al. TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients. Blood. 2014;124:2705–12.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Tantravahi SK, Szankasi P, Khorashad JS, Dao K-H, Kovacsovics T, Kelley TW, et al. A phase II study of the efficacy, safety, and determinants of response to 5-azacitidine (Vidaza®) in patients with chronic myelomonocytic leukemia. Leuk Lymphoma. 2016;57:2441–4. 2016/10/02

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kandoth C, McLellan MD, Vandin F, Ye K, Niu B, Lu C, et al. Mutational landscape and significance across 12 major cancer types. Nature. 2013;502:333–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Schuetz JM, Johnson NA, Morin RD, Scott DW, Tan K, Ben-Nierah S, et al. BCL2 mutations in diffuse large B-cell lymphoma. Leukemia. 2012;26:1383–90.

    Article  PubMed  CAS  Google Scholar 

  10. Qiao Y, Quinlan AR, Jazaeri AA, Verhaak RG, Wheeler DA, Marth GT. SubcloneSeeker: a computational framework for reconstructing tumor clone structure for cancer variant interpretation and prioritization. Genome Biol. 2014;15:443.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Patel BJ, Przychodzen B, Thota S, Radivoyevitch T, Visconte V, Kuzmanovic T, et al. Genomic determinants of chronic myelomonocytic leukemia. Leukemia. 2017;31:2815–23.

    Article  PubMed  CAS  Google Scholar 

  12. Dunbar AJ, Gondek LP, O’Keefe CL, Makishima H, Rataul MS, Szpurka H, et al. 250K single nucleotide polymorphism array karyotyping identifies acquired uniparental disomy and homozygous mutations, including novel missense substitutions of c-Cbl, in myeloid malignancies. Cancer Res. 2008;68:10349–57.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Grand FH, Hidalgo-Curtis CE, Ernst T, Zoi K, Zoi C, McGuire C, et al. Frequent CBL mutations associated with 11q acquired uniparental disomy in myeloproliferative neoplasms. Blood. 2009;113:6182–92.

    Article  PubMed  CAS  Google Scholar 

  14. Grun D, van Oudenaarden A. Design and analysis of single-cell sequencing experiments. Cell. 2015;163:799–810.

    Article  PubMed  CAS  Google Scholar 

  15. Brady SW, McQuerry JA, Qiao Y, Piccolo SR, Shrestha G, Jenkins DF, et al. Combating subclonal evolution of resistant cancer phenotypes. Nat Commun. 2017;8:1231.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by a Leukemia and Lymphoma Society (LLS) Translational Research Program Award (6086-12) (M.W.D.) and an LLS Specialized Center of Research Program Award (GCNCR0314A-UTAH) (M.W.D.). This work was also supported by the National Institutes of Health (NIH) National Cancer Institute grant R01CA178397 (M.W.D. and T.O.), the V Foundation for Cancer Research grant (M.W.D. and T.O.) and by U01HG006513 (G.T.M.). J.S.K. was a special fellow of the LLS and was supported by a Translational Research Training in Hematology Award from the American Society of Hematology (ASH). H.T. was a visiting scholar from Singapore, and was supported by the Research Training Fellowship from National Medical Research Council of Singapore. We thank Brian K. Dalley, director of High-Throughput Genomics Core Facility, and James Marvin, director of Flow Cytometry Core Facility, at the University of Utah for their assistance with the experiments. The University of Utah Flow Cytometry Facility was supported by the National Cancer Institute through award 5P30CA042014-24 and the National Center for Research Resources of the National Institutes of Health under award 1S10RR026802-01. The University of Utah High-Throughput Genomics Core Facility was supported by Award Number P30CA042014 from the National Cancer Institute.

Author contributions

H.T., Y.Q., and M.W.D. conceived the project and analyzed data. H.T., T.O., and M.W.D. wrote the manuscript. Y.Q., X.H., and G.T.M. designed the software and analyzed data. H.T., D.Y., and J.S.K. prepared the samples and performed experiments. M.W.D. and T.J.K. provided clinical information and research materials. A.D.P. and T.O. critically reviewed the manuscript.

Author information

Authors and Affiliations

  1. Huntsman Cancer Institute, The University of Utah, Salt Lake City, UT, USA

    Hein Than, Dongqing Yan, Jamshid S. Khorashad, Anthony D. Pomicter, Thomas O’Hare & Michael W. Deininger

  2. Department of Hematology, Singapore General Hospital, Singapore, Singapore

    Hein Than

  3. Eccles Institute of Human Genetics, The University of Utah, Salt Lake City, UT, USA

    Yi Qiao, Xiaomeng Huang & Gabor T. Marth

  4. Centre for Hematology, Department of Medicine, Imperial College, London, UK

    Jamshid S. Khorashad & Tibor J. Kovacsovics

  5. Division of Hematology and Hematologic Malignancies, The University of Utah, Salt Lake City, UT, USA

    Thomas O’Hare & Michael W. Deininger

Authors
  1. Hein Than
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaomeng Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dongqing Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jamshid S. Khorashad
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Anthony D. Pomicter
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Tibor J. Kovacsovics
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Gabor T. Marth
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Thomas O’Hare
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Michael W. Deininger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael W. Deininger.

Ethics declarations

Conflict of interest

M.W.D. is on the advisory board and is a consultant for Incyte, Novartis and Pfizer, and serves on the advisory board for Ariad, Blueprint, and Galena BioPharma. His laboratory receives research funding from Novartis and Pfizer.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Than, H., Qiao, Y., Huang, X. et al. Ongoing clonal evolution in chronic myelomonocytic leukemia on hypomethylating agents: a computational perspective. Leukemia 32, 2049–2054 (2018). https://doi.org/10.1038/s41375-018-0050-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-018-0050-z

Search

Advanced search

Quick links