Cytogenetics and molecular genetics

Genomic determinants of chronic myelomonocytic leukemia

Article metrics


The biology, clinical phenotype and progression rate of chronic myelomonocytic leukemia (CMML) are highly variable due to diverse initiating and secondary clonal genetic events. To determine the effects of molecular features including clonal hierarchy in CMML, we studied whole-exome and targeted next-generation sequencing data from 150 patients with robust clinical and molecular annotation assessed cross-sectionally and at serial time points of disease evolution. To identify molecular lesions unique to CMML, we compared it to the related myeloid neoplasms (N=586), including juvenile myelomonocytic leukemia, myelodysplastic syndromes (MDS) and primary monocytic acute myeloid leukemia and discerned distinct molecular profiles despite similar pathomorphological features. Within CMML, mutations in certain pathways correlated with clinical classification, for example, proliferative vs dysplastic features. While most CMML patients (59%) had ancestral (dominant/co-dominant) mutations involving TET2, SRSF2 or ASXL1 genes, secondary subclonal hierarchy correlated with clinical phenotypes or outcomes. For example, progression was associated with acquisition of new expanding clones carrying biallelic TET2 mutations or RAS family, or spliceosomal gene mutations. In contrast, dysplastic features correlated with mutations usually encountered in MDS (for example, SF3B1 and U2AF1). Classification of CMML based on hierarchies of ancestral and subclonal mutational events may correlate strongly with clinical features and prognosis.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6


  1. 1

    Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood 2016; 127: 2391–2405.

  2. 2

    Sakaguchi H, Okuno Y, Muramatsu H, Yoshida K, Shiraishi Y, Takahashi M et al. Exome sequencing identifies secondary mutations of SETBP1 and JAK3 in juvenile myelomonocytic leukemia. Nat Genet 2013; 45: 937–941.

  3. 3

    Campo E, Swerdlow SH, Harris NL, Pileri S, Stein H, Jaffe ES . The 2008 WHO classification of lymphoid neoplasms and beyond: evolving concepts and practical applications. Blood 2011; 117: 5019–5032.

  4. 4

    Haferlach T, Nagata Y, Grossmann V, Okuno Y, Bacher U, Nagae G et al. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia 2014; 28: 241–247.

  5. 5

    Malcovati L, Papaemmanuil E, Ambaglio I, Elena C, Gallì A, Della Porta MG et al. Driver somatic mutations identify distinct disease entities within myeloid neoplasms with myelodysplasia. Blood 2014; 124: 1513–1521.

  6. 6

    Makishima H, Yoshizato T, Yoshida K, Sekeres MA, Radivoyevitch T, Suzuki H et al. Dynamics of clonal evolution in myelodysplastic syndromes. Nat Genet 2017; 49: 204–212.

  7. 7

    Miller CA, Wilson RK, Ley TJ . Genomic landscapes and clonality of de novo AML. N Engl J Med 2013; 369: 1473.

  8. 8

    Walter MJ, Shen D, Ding L, Shao J, Koboldt DC, Chen K et al. Clonal architecture of secondary acute myeloid leukemia. N Eng J Med 2012; 366: 1090–1098.

  9. 9

    Jankowska AM, Makishima H, Tiu RV, Szpurka H, Huang Y, Traina F et al. Mutational spectrum analysis of chronic myelomonocytic leukemia includes genes associated with epigenetic regulation: UTX, EZH2, and DNMT3A. Blood 2011; 118: 3932–3941.

  10. 10

    Makishima H, Cazzolli H, Szpurka H, Dunbar A, Tiu R, Huh J et al. Mutations of e3 ubiquitin ligase cbl family members constitute a novel common pathogenic lesion in myeloid malignancies. J Clin Oncol 2009; 27: 6109–6116.

  11. 11

    Makishima H, Jankowska AM, McDevitt MA, O'Keefe C, Dujardin S, Cazzolli H et al. CBL, CBLB, TET2, ASXL1, and IDH1/2 mutations and additional chromosomal aberrations constitute molecular events in chronic myelogenous leukemia. Blood 2011; 117: e198–e206.

  12. 12

    Makishima H, Visconte V, Sakaguchi H, Jankowska AM, Abu Kar S, Jerez A et al. Mutations in the spliceosome machinery, a novel and ubiquitous pathway in leukemogenesis. Blood 2012; 119: 3203–3210.

  13. 13

    Meggendorfer M, Roller A, Haferlach T, Eder C, Dicker F, Grossmann V et al. SRSF2 mutations in 275 cases with chronic myelomonocytic leukemia (CMML). Blood 2012; 120: 3080–3088.

  14. 14

    Such E, Germing U, Malcovati L, Cervera J, Kuendgen A, Della Porta MG et al. Development and validation of a prognostic scoring system for patients with chronic myelomonocytic leukemia. Blood 2013; 121: 3005–3015.

  15. 15

    Elena C, Gallì A, Such E, Meggendorfer M, Germing U, Rizzo E et al. Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia. Blood 2016; 128: 1408–1417.

  16. 16

    Cheson BD, Greenberg PL, Bennett JM, Lowenberg B, Wijermans PW, Nimer SD et al. Clinical application and proposal for modification of the International Working Group (IWG) response criteria in myelodysplasia. Blood 2006; 108: 419–425.

  17. 17

    Savona MR, Malcovati L, Komrokji R, Tiu RV, Mughal TI, Orazi A et al. An international consortium proposal of uniform response criteria for myelodysplastic/myeloproliferative neoplasms (MDS/MPN) in adults. Blood 2015; 125: 1857–1865.

  18. 18

    Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G et al. Integrative genomics viewer. Nat Biotechnol 2011; 29: 24–26.

  19. 19

    Bolger AM, Lohse M, Usadel B . Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30: 2114–2120.

  20. 20

    Li H, Durbin R . Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 2010; 26: 589–595.

  21. 21

    McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research 2010; 20: 1297–1303.

  22. 22

    DePristo M, Banks E, Poplin R, Garimella K, Maguire J, Hartl C et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 2011; 43: 491–498.

  23. 23

    Wang K, Li M, Hakonarson H . ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acid Res 2010; 38: e164.

  24. 24

    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: 64–69.

  25. 25

    Tiu RV, Gondek L, O'Keefe CL, Huh J, Sekeres MA, Elson P et al. New lesions detected by single nucleotide polymorphism array-based chromosomal analysis have important clinical impact in acute myeloid leukemia. J Clin Oncol 2009; 27: 5219–5226.

  26. 26

    Huh J, Tiu RV, Gondek LP, O'Keefe CL, Jasek M, Makishima H et al. Characterization of chromosome arm 20q abnormalities in myeloid malignancies using genome-wide single nucleotide polymorphism array analysis. Genes Chromosomes Cancer 2010; 49: 390–399.

  27. 27

    Makishima H, Yoshida K, Nguyen N, Przychodzen B, Sanada M, Okuno Y et al. Somatic SETBP1 mutations in myeloid malignancies. Nat Genet 2013; 45: 942–946.

  28. 28

    Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, Golub TR et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 2014; 505: 495–501.

  29. 29

    Delhommeau F, Dupont S, Della Valle V, James C, Trannoy S, Massé A et al. Mutation in TET2 in myeloid cancers. N Eng J Med 2009; 360: 2289–2301.

  30. 30

    Kon A, Shin LY, Minamino M, Sanada M, Shiraishi Y, Nagata Y et al. Recurrent mutations in multiple components of the cohesin complex in myeloid neoplasms. Nat Genet 2013; 45: 1232–1237.

  31. 31

    Itzykson R, Kosimder O, Renneville A, Morabito M, Preudhomme C, Berthon C et al. Clonal architecture of chronic myelomonocytic leukemias. Blood 2013; 121: 2186–2198.

  32. 32

    Itzykson R, Solary E . An evolutionary perspective on chronic myelomonocytic leukemia. Leukemia 2013; 27: 1441–1450.

  33. 33

    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: 10349–10357.

  34. 34

    Kar SA, Jankowska A, Makishima H, Visconte V, Jerez A, Sugimoto Y et al. Spliceosomal gene mutations are frequent events in the diverse mutational spectrum of chronic myelomonocytic leukemia but largely absent in juvenile myelomonocytic leukemia. Haematologica 2013; 98: 107–113.

  35. 35

    Levine RL, Loriaux M, Huntly BJ, Loh ML, Beran M, Stoffregen E et al. The JAK2V617F activating mutation occurs in chronic myelomonocytic leukemia and acute myeloid leukemia, but not in acute lymphoblastic leukemia or chronic lymphocytic leukemia. Blood 2005; 106: 3377–3379.

  36. 36

    Tyner JW, Erickson H, Deininger MW, Willis SG, Eide CA, Levine RL et al. High-throughput sequencing screen reveals novel, transforming RAS mutations in myeloid leukemia patients. Blood 2009; 113: 1749–1755.

  37. 37

    Abdel-Wahab O, Pardanani A, Patel J, Wadleigh M, Lasho T, Heguy A et al. Concomitant analysis of EZH2 and ASXL1 mutations in myelofibrosis, chronic myelomonocytic leukemia and blast-phase myeloproliferative neoplasms. Leukemia 2011; 25: 1200–1202.

  38. 38

    Gelsi-Boyer V, Trouplin V, Roquain J, Adélaïde J, Carbuccia N, Esterni B et al. ASXL1 mutation is associated with poor prognosis and acute transformation in chronic myelomonocytic leukaemia. Br J Haematol 2010; 151: 365–375.

  39. 39

    Traina F, Visconte V, Elson P, Tabarroki A, Jankowska AM, Hasrouni E et al. Impact of molecular mutations on treatment response to DNMT inhibitors in myelodysplasia and related neoplasms. Leukemia 2014; 28: 78–87.

  40. 40

    Bejar R, Lord A, Stevenson K, Bar-Natan M, Pérez-Ladaga A, Zaneveld J et al. TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients. Blood 2014; 124: 2705–2712.

Download references


We thank the Edwards P Evans Foundation and Aplastic Anemia and MDS International Foundation, NIH-R01HL123904: NIH-R01HL118281, NIH-R01HL128425 for their contributions and support.

Author contributions

BJP designed the study, collected, analyzed and interpreted the data, and wrote the manuscript. BP analyzed and interpreted the sequencing data. ST collected the clinical data. VV helped with the data interpretation and manuscript preparation. MC collected samples. CH analyzed the data. TR performed statistical analysis and edited the manuscript. AM, RS, BD, AN, CS and TK collected the data. TLF performed bioinformatics analysis. HS and SK provided important insights to the manuscript. HEC edited the manuscript. MAS contributed to the data interpretation and manuscript preparation. SO and HM provided samples and the data analysis. JMP designed the study, analyzed and interpreted the data, and manuscript preparation.

Author information

Correspondence to J P Maciejewski.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on the Leukemia website

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Patel, B., Przychodzen, B., Thota, S. et al. Genomic determinants of chronic myelomonocytic leukemia. Leukemia 31, 2815–2823 (2017) doi:10.1038/leu.2017.164

Download citation

Further reading