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Exome sequencing identifies secondary mutations of SETBP1 and JAK3 in juvenile myelomonocytic leukemia

Abstract

Juvenile myelomonocytic leukemia (JMML) is an intractable pediatric leukemia with poor prognosis1 whose molecular pathogenesis is poorly understood, except for somatic or germline mutations of RAS pathway genes, including PTPN11, NF1, NRAS, KRAS and CBL, in the majority of cases2,3,4. To obtain a complete registry of gene mutations in JMML, whole-exome sequencing was performed for paired tumor-normal DNA from 13 individuals with JMML (cases), which was followed by deep sequencing of 8 target genes in 92 tumor samples. JMML was characterized by a paucity of gene mutations (0.85 non-silent mutations per sample) with somatic or germline RAS pathway involvement in 82 cases (89%). The SETBP1 and JAK3 genes were among common targets for secondary mutations. Mutations in the latter were often subclonal and may be involved in the progression rather than the initiation of leukemia, and these mutations associated with poor clinical outcome. Our findings provide new insights into the pathogenesis and progression of JMML.

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Figure 1: Mutation profiles of 92 JMML cases.
Figure 2: Clinical features of JMML cases with or without secondary mutations.

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References

  1. Pinkel, D. et al. Differentiating juvenile myelomonocytic leukemia from infectious disease. Blood 91, 365–367 (1998).

    CAS  PubMed  Google Scholar 

  2. Loh, M.L. et al. Mutations in CBL occur frequently in juvenile myelomonocytic leukemia. Blood 114, 1859–1863 (2009).

    Article  CAS  Google Scholar 

  3. Muramatsu, H. et al. Mutations of an E3 ubiquitin ligase c-Cbl but not TET2 mutations are pathogenic in juvenile myelomonocytic leukemia. Blood 115, 1969–1975 (2010).

    Article  CAS  Google Scholar 

  4. Pérez, B. et al. Genetic typing of CBL, ASXL1, RUNX1, TET2 and JAK2 in juvenile myelomonocytic leukaemia reveals a genetic profile distinct from chronic myelomonocytic leukaemia. Br. J. Haematol. 151, 460–468 (2010).

    Article  Google Scholar 

  5. Ng, S.B. et al. Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nat. Genet. 42, 790–793 (2010).

    Article  CAS  Google Scholar 

  6. Minakuchi, M. et al. Identification and characterization of SEB, a novel protein that binds to the acute undifferentiated leukemia–associated protein SET. Eur. J. Biochem. 268, 1340–1351 (2001).

    Article  CAS  Google Scholar 

  7. Damm, F. et al. SETBP1 mutations in 658 patients with myelodysplastic syndromes, chronic myelomonocytic leukemia and secondary acute myeloid leukemias. Leukemia 27, 401–403 (2013).

    Article  Google Scholar 

  8. Laborde, R.R. et al. SETBP1 mutations in 415 patients with primary myelofibrosis or chronic myelomonocytic leukemia: independent prognostic impact in CMML. Leukemia published online; doi:10.1038/leu.2013.97 (5 April 2013).10.1038/leu.2013.97

    Article  CAS  Google Scholar 

  9. Meggendorfer, M. et al. SETBP1 mutations occur in 9% of MDS/MPN and in 4% of MPN cases and are strongly associated with atypical CML, monosomy 7, isochromosome i(17)(q10), ASXL1 and CBL mutations. Leukemia published online; doi:10.1038/leu.2013.133 (30 April 2013).10.1038/leu.2013.133

    Article  CAS  Google Scholar 

  10. Piazza, R. et al. Recurrent SETBP1 mutations in atypical chronic myeloid leukemia. Nat. Genet. 45, 18–24 (2013).

    Article  CAS  Google Scholar 

  11. Thol, F. et al. SETBP1 mutation analysis in 944 patients with MDS and AML. Leukemia published online; doi:10.1038/leu.2013.145 (7 May 2013).10.1038/leu.2013.145

    Article  CAS  Google Scholar 

  12. Panagopoulos, I. et al. Fusion of NUP98 and the SET binding protein 1 (SETBP1) gene in a paediatric acute T cell lymphoblastic leukaemia with t(11;18)(p15;q12). Br. J. Haematol. 136, 294–296 (2007).

    Article  CAS  Google Scholar 

  13. Cristóbal, I. et al. SETBP1 overexpression is a novel leukemogenic mechanism that predicts adverse outcome in elderly patients with acute myeloid leukemia. Blood 115, 615–625 (2010).

    Article  Google Scholar 

  14. Goyama, S. et al. Evi-1 is a critical regulator for hematopoietic stem cells and transformed leukemic cells. Cell Stem Cell 3, 207–220 (2008).

    Article  CAS  Google Scholar 

  15. Ott, M.G. et al. Correction of X-linked chronic granulomatous disease by gene therapy, augmented by insertional activation of MDS1-EVI1, PRDM16 or SETBP1. Nat. Med. 12, 401–409 (2006).

    Article  CAS  Google Scholar 

  16. Hoischen, A. et al. De novo mutations of SETBP1 cause Schinzel-Giedion syndrome. Nat. Genet. 42, 483–485 (2010).

    Article  CAS  Google Scholar 

  17. Yoshida, K. et al. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature 478, 64–69 (2011).

    Article  CAS  Google Scholar 

  18. Flotho, C. et al. Genome-wide single-nucleotide polymorphism analysis in juvenile myelomonocytic leukemia identifies uniparental disomy surrounding the NF1 locus in cases associated with neurofibromatosis but not in cases with mutant RAS or PTPN11. Oncogene 26, 5816–5821 (2007).

    Article  CAS  Google Scholar 

  19. Walters, D.K. et al. Activating alleles of JAK3 in acute megakaryoblastic leukemia. Cancer Cell 10, 65–75 (2006).

    Article  CAS  Google Scholar 

  20. Sato, T. et al. Functional analysis of JAK3 mutations in transient myeloproliferative disorder and acute megakaryoblastic leukaemia accompanying Down syndrome. Br. J. Haematol. 141, 681–688 (2008).

    Article  CAS  Google Scholar 

  21. De Vita, S. et al. Loss-of-function JAK3 mutations in TMD and AMKL of Down syndrome. Br. J. Haematol. 137, 337–341 (2007).

    Article  CAS  Google Scholar 

  22. Norton, A. et al. Analysis of JAK3, JAK2, and C-MPL mutations in transient myeloproliferative disorder and myeloid leukemia of Down syndrome blasts in children with Down syndrome. Blood 110, 1077–1079 (2007).

    Article  CAS  Google Scholar 

  23. Kiyoi, H., Yamaji, S., Kojima, S. & Naoe, T. JAK3 mutations occur in acute megakaryoblastic leukemia both in Down syndrome children and non–Down syndrome adults. Leukemia 21, 574–576 (2007).

    Article  CAS  Google Scholar 

  24. Elliott, N.E. et al. FERM domain mutations induce gain of function in JAK3 in adult T-cell leukemia/lymphoma. Blood 118, 3911–3921 (2011).

    Article  CAS  Google Scholar 

  25. Zhang, J. et al. The genetic basis of early T-cell precursor acute lymphoblastic leukaemia. Nature 481, 157–163 (2012).

    Article  CAS  Google Scholar 

  26. Koo, G.C. et al. Janus kinase 3–activating mutations identified in natural killer/T-cell Lymphoma. Cancer Discov. 2, 591–597 (2012).

    Article  CAS  Google Scholar 

  27. Zhang, J. et al. A novel retinoblastoma therapy from genomic and epigenetic analyses. Nature 481, 329–334 (2012).

    Article  CAS  Google Scholar 

  28. Makishima, H. et al. Somatic SETBP1 mutations in myeloid malignancies. Nat. Genet. published online; doi:10.1038/ng.2696 (7 July 2013).10.1038/ng.2696

    PubMed  PubMed Central  Google Scholar 

  29. Crozatier, M. & Meister, M. Drosophila haematopoiesis. Cell. Microbiol. 9, 1117–1126 (2007).

    Article  CAS  Google Scholar 

  30. Changelian, P.S. et al. Prevention of organ allograft rejection by a specific Janus kinase 3 inhibitor. Science 302, 875–878 (2003).

    Article  CAS  Google Scholar 

  31. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  32. Matthews, L. et al. Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res. 37, D619–D622 (2009).

    Article  CAS  Google Scholar 

  33. Thorvaldsdóttir, H., Robinson, J.T. & Mesirov, J.P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

    Article  Google Scholar 

  34. Kent, W.J. BLAT—the BLAST-like alignment tool. Genome Res. 12, 656–664 (2002).

    Article  CAS  Google Scholar 

  35. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  Google Scholar 

  36. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).

    Article  Google Scholar 

  37. Kumar, P., Henikoff, S. & Ng, P.C. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 4, 1073–1081 (2009).

    Article  CAS  Google Scholar 

  38. Adzhubei, I.A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    Article  CAS  Google Scholar 

  39. Schwarz, J.M., Rödelsperger, C., Schuelke, M. & Seelow, D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat. Methods 7, 575–576 (2010).

    Article  CAS  Google Scholar 

  40. Huang, X. & Madan, A. CAP3: A DNA sequence assembly program. Genome Res. 9, 868–877 (1999).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank the subjects and their parents for participating in this study. This work was supported by the Research on Measures for Intractable Diseases Project from the Ministry of Health, Labor and Welfare, by Grants-in-Aid from the Ministry of Health, Labor and Welfare of Japan and KAKENHI (23249052, 22134006 and 21790907), by the Project for the Development of Innovative Research on Cancer Therapeutics (P-DIRECT) and by the Japan Society for the Promotion of Science through the Funding Program for World-Leading Innovative R&D on Science and Technology.

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H.S., Y.O., H. Muramatsu, K.Y., M.T., A.K. and M.S. designed and performed the research, analyzed the data and wrote the manuscript. Y.S., K.C., H.T. and S.M. performed bioinformatics analyses of the resequencing data. X.W. and Y.X. performed Sanger sequencing. S.D., A.H., K.N., Y.T. and N.Y. collected specimens and performed the research. H. Makishima and J.P.M. designed the research and analyzed the data. S.O. and S.K. led the entire project and wrote the manuscript.

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Correspondence to Seishi Ogawa or Seiji Kojima.

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The authors declare no competing financial interests.

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Supplementary Figures 1–11 and Supplementary Tables 1–3 (PDF 1935 kb)

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Sakaguchi, H., Okuno, Y., Muramatsu, H. et al. Exome sequencing identifies secondary mutations of SETBP1 and JAK3 in juvenile myelomonocytic leukemia. Nat Genet 45, 937–941 (2013). https://doi.org/10.1038/ng.2698

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