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Dynamics of clonal evolution in myelodysplastic syndromes

Nature Genetics volume 49, pages 204–212 (2017)Cite this article

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Abstract

To elucidate differential roles of mutations in myelodysplastic syndromes (MDS), we investigated clonal dynamics using whole-exome and/or targeted sequencing of 699 patients, of whom 122 were analyzed longitudinally. Including the results from previous reports, we assessed a total of 2,250 patients for mutational enrichment patterns. During progression, the number of mutations, their diversity and clone sizes increased, with alterations frequently present in dominant clones with or without their sweeping previous clones. Enriched in secondary acute myeloid leukemia (sAML; in comparison to high-risk MDS), FLT3, PTPN11, WT1, IDH1, NPM1, IDH2 and NRAS mutations (type 1) tended to be newly acquired, and were associated with faster sAML progression and a shorter overall survival time. Significantly enriched in high-risk MDS (in comparison to low-risk MDS), TP53, GATA2, KRAS, RUNX1, STAG2, ASXL1, ZRSR2 and TET2 mutations (type 2) had a weaker impact on sAML progression and overall survival than type-1 mutations. The distinct roles of type-1 and type-2 mutations suggest their potential utility in disease monitoring.

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Figure 1: Numbers, allele frequency and diversity of somatic nonsynonymous mutations.
Figure 2: Clonal evolution from MDS to sAML analyzed by WES.
Figure 3: Dynamics of major driver mutations revealed by targeted sequencing.
Figure 4: Distinct sets of driver mutations in MDS and their impact on clinical outcomes.
Figure 5: Effects of clone size of driver mutations on prognosis.
Figure 6: Combination of type-1 and type-2 mutations in MDS.

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Acknowledgements

This work was supported by US National Institutes of Health (NIH) grants RO1HL-082983 (J.P.M.), U54 RR019391 (J.P.M.) and K24 HL-077522 (J.P.M.), a grant from the AA & MDS International Foundation (J.P.M., M.A.S. and H.M.), the Robert Duggan Charitable Fund (J.P.M.), a grant from Edward P. Evans Foundation (J.P.M. and M.A.S.), Scott Hamilton CARES grant (H.M.), Grant-in-Aids from the Ministry of Health, Labor and Welfare of Japan, the Japanese Agency for Medical Research and Development (Health and Labour Sciences Research Expenses for Commission and Applied Research for Innovative Treatment of Cancer) and KAKENHI (26221308, 23249052, 22134006, 15H05909, hp160219 and 21790907; S.O.), (15km0305018h0101, 16H05338; H.M.), (26890016; K.Y.), project for development of innovative research on cancer therapies (FIRST, p-direct; S.O.), the Japan Society for the Promotion of Science (JSPS) through the 'Funding Program for World-Leading Innovative R&D on Science and Technology', initiated by the Council for Science and Technology Policy (CSTP) (S.O.), NHRI-EX100-10003NI Taiwan (L.-Y.S.), National Aeronautics and Space Administration grant NNJ13ZSA001N (T.R.), and a grant from the American Cancer Society (Research Scholar Grant 123436-RSG-12-159-01-DMC, to T.L.). Supercomputing resources were also provided by the Human Genome Center, the Institute of Medical Science, The University of Tokyo.

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Author notes

  1. Hideki Makishima, Tetsuichi Yoshizato and Kenichi Yoshida: These authors contributed equally to this work.

  2. Seishi Ogawa and Jaroslaw P Maciejewski: These authors jointly directed this work.

Authors and Affiliations

  1. Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA

    Hideki Makishima, Mikkael A Sekeres, Tomas Radivoyevitch, Bartlomiej Przychodzen, Cassandra Hirsch, Teodora Kuzmanovic, Naoko Hosono, Inés Gómez-Seguí, Holleh D Husseinzadeh, Swapna Thota, Kathryn M Guinta, Brittney Dienes, Yogen Saunthararajah & Jaroslaw P Maciejewski

  2. Department of Pathology and Tumor Biology, Kyoto University, Kyoto, and Cancer Genomics Project, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Hideki Makishima, Tetsuichi Yoshizato, Kenichi Yoshida, Hiromichi Suzuki, Yasunobu Nagata, Yusuke Okuno, Yusuke Sato, Aiko Sato-Otsubo, Yusuke Shiozawa & Seishi Ogawa

  3. Department of Hematology and Medical Oncology, Leukemia Program, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA

    Mikkael A Sekeres

  4. MLL Munich Leukemia Laboratory, Munich, Germany

    Manja Meggendorfer

  5. Clinical Research Center, Nagoya Medical Center, Nagoya, Japan

    Masashi Sanada, Claudia Haferlach, Wolfgang Kern & Torsten Haferlach

  6. Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, USA

    Thomas LaFramboise

  7. Laboratory of Sequence Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan

    Yuichi Shiraishi, Kenichi Chiba, Hiroko Tanaka & Satoru Miyano

  8. Division of Hematology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan

    Tsuyoshi Nakamaki

  9. Division of Hematology, Tokyo Metropolitan Ohtsuka Hospital, Tokyo, Japan

    Shuichi Miyawaki

  10. Department of Hematology, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan

    Shigeru Chiba

  11. Division of Hematology-Oncology, Chang Gung Memorial Hospital–Linkou, Chang Gung University, Taoyuan, Taiwan

    Lee-Yung Shih

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  1. Hideki Makishima
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Contributions

H.M.: project leader, analysis coordination, variant validation production and manuscript preparation. T.Y.: project leader, sequence analysis, microarray data analysis and manuscript preparation. K.Y.: data analysis team and variant validation production. M.A.S.: clinical data and specimen acquisition and manuscript preparation. T.R.: data analysis, manuscript preparation. H.S.: data analysis team and variant validation production. B.P.: supervisor data analysis team and variant validation production. Y.N.: hybridization-based capture next-generation platform development. M.M.: clinical data and specimen acquisition, data analysis. M.S.: sequence analysis. Y.O.: auto-analysis and manuscript preparation. C. Hirsch: clinical data and specimen acquisition, data analysis. T.K.: clinical data and specimen acquisition, data analysis. Y. Sato: microarray data analysis. A.S.-O.: data management, data analysis. T.L.: data analysis and manuscript preparation. N.H.: variant validation production. Y. Shiraishi: data management, data analysis. K.C.: data management, data analysis. C. Haferlach: clinical data and specimen acquisition, data analysis. W.K.: clinical data and specimen acquisition, data analysis. H.T.: data management, data analysis. Y. Shiozawa: data analysis. I.G.-S.: clinical data management. H.D.H.: clinical data management. S.T.: clinical data management. K.M.G.: specimen acquisition. B.D.: specimen acquisition. T.N.: clinical data management and specimen acquisition. S. Miyawaki: clinical data management and specimen acquisition. Y. Saunthararajah: clinical data management and specimen acquisition. S.C.: clinical data management and specimen acquisition. S. Miyano: data management, data analysis automation leader. L.-Y.S.: clinical data and specimen acquisition, study design. T.H.: clinical data and specimen acquisition, study design. S.O. and J.P.M.: project leaders, study design, execution and analysis, manuscript preparation.

Corresponding authors

Correspondence to Seishi Ogawa or Jaroslaw P Maciejewski.

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Makishima, H., Yoshizato, T., Yoshida, K. et al. Dynamics of clonal evolution in myelodysplastic syndromes. Nat Genet 49, 204–212 (2017). https://doi.org/10.1038/ng.3742

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