Synergistic Interactions of Molecular and Clinical Advances for Characterizing the Myelodysplastic Syndromes

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Peter L. Greenberg, MD, is Professor of Medicine in the Division of Hematology and Director of the Myelodysplastic Syndromes (MDS) Center at Stanford University Cancer Institute. He is Chair of the NCCN MDS Guidelines Panel, serves as a member of the Leukemia Core Committee of ECOG, and is a member of the Board of Directors of the MDS Foundation. He is coordinator of the International Working Group for Prognosis in MDS (IWG-PM).The ideas and viewpoints expressed in this editorial are those of the author and do not necessarily represent any policy, position, or program of NCCN.
  • 1.

    GreenbergPLStoneRMBejarR. NCCN Clinical Practice Guidelines in Oncology: Myelodysplastic Syndromes Version 1.2015. Available at: NCCN.org. Accessed June 15 2015.

    • Search Google Scholar
    • Export Citation
  • 2.

    GreenbergPTuechlerHSchanzJ. Revised International Prognostic Scoring System for myelodysplastic syndromes. Blood2012;120:24542465.

  • 3.

    VosoMTFenuSLatagliataR. Revised International Prognostic Scoring System predicts survival and leukemic evolution of myelodysplastic syndromes significantly better than IPSS and WHO Prognostic Scoring System: validation by the Gruppo Romano Mielodisplasie Italian Regional Database. J Clin Oncol2013;31:26712677.

    • Search Google Scholar
    • Export Citation
  • 4.

    OkCYHasserjianRPFoxPS. Application of the International Prognostic Scoring System-Revised in therapy-related myelodysplastic syndromes and oligoblastic acute myeloid leukemia. Leukemia2014;28:185189.

    • Search Google Scholar
    • Export Citation
  • 5.

    ZeidanAMLeeJWPrebetT. Comparison of the prognostic utility of the Revised International Prognostic Scoring System and the French Prognostic Scoring System in azacitidine-treated patients with myelodysplastic syndromes. Brit J Haematol2014;166:352359.

    • Search Google Scholar
    • Export Citation
  • 6.

    Della PortaMGAlessandrinoEPBacigalupoA. Predictive factors for the outcome of allogeneic transplantation in patients with MDS stratified according to the revised IPSS-R. Blood2014;123:23332342.

    • Search Google Scholar
    • Export Citation
  • 7.

    Della PortaMGTuechlerHMalcovatiL. Validation of WHO classification-based Prognostic Scoring System (WPSS) for myelodysplastic syndromes and comparison with the revised International Prognostic Scoring System (IPSS-R). A study of the International Working Group for Prognosis in Myelodysplasia (IWG-PM)[published online ahead of print February 27 2015]. Leukemiadoi: 10.1038/leu.2015.55.

    • Search Google Scholar
    • Export Citation
  • 8.

    BejarRStevensonKAbdel-WahabO. Clinical effect of point mutations in myelodysplastic syndromes. N Engl J Med2011;364:24962506.

  • 9.

    PapaemmanuilEGerstungMMalcovatiL. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood2013;122:36163627.

    • Search Google Scholar
    • Export Citation
  • 10.

    HaferlachTNagataYGrossmannV. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia2014;28:241247.

  • 11.

    YoshidaKSanadaMShiraishiY. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature2011;478:6469.

  • 12.

    WalterMJShenDDingL. Clonal architecture of secondary acute myeloid leukemia. N Engl J Med2012;366:10901098.

  • 13.

    KulasekararajAGSmithAEMianSA. TP53 mutations in myelodysplastic syndrome are strongly correlated with aberrations of chromosome 5, and correlate with adverse prognosis. Br J Haematol2013;160:660672.

    • Search Google Scholar
    • Export Citation
  • 14.

    JäderstenMSaftLSmithA. TP53 mutations in low-risk myelodysplastic syndromes with del(5q) predict disease progression. J Clin Oncol2011;29:19711979.

    • Search Google Scholar
    • Export Citation
  • 15.

    BejarRPapaemmanuilEHaferlachT. TP53 mutation status divides MDS patients with complex karyotypes into distinct prognostic risk groups: analysis of combined datasets from the International Working Group for MDS-Molecular Prognosis Committee (IWG-PM) [abstract]. Blood2014;124(Suppl 21):Abstract 532.

    • Search Google Scholar
    • Export Citation
  • 16.

    MalcovatiLKarimiMPapaemmanuilE. SF3B1 mutation identifies a distinct subset of myelodysplastic syndrome with ring sideroblasts[published online ahead of print May 8 2015]. Bloodpii: blood-2015-03-633537.

    • Search Google Scholar
    • Export Citation
  • 17.

    MeggendorferMRollerAHaferlachT. SRSF2 mutations in 275 cases with chronic myelomonocytic leukemia (CMML). Blood2012;120:30803088.

  • 18.

    Abu KarSJankowskaAMakishimaH. Spliceosomal gene mutations are frequent events in the diverse mutational spectrum of chronic myelomonocytic leukemia but largely absent in juvenile myelomonocytic leukemia. Haematologica2013;98:107113.

    • Search Google Scholar
    • Export Citation
  • 19.

    JaiswalSFontanillasPFlannickJ. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med2014;371:24882498.

  • 20.

    GenoveseGJaiswalSEbertBLMcCarrollSA. Clonal hematopoiesis and blood-cancer risk. N Engl J Med2015;372:10711072.

  • 21.

    SteensmaDPBejarRJaiswalS. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes[published online ahead of print April 30 2015]. Bloodpii: blood-2015-03-631747.

    • Search Google Scholar
    • Export Citation
  • 22.

    WestAHGodleyLAChurpekJE. Familial myelodysplastic syndrome/acute leukemia syndromes: a review and utility for translational investigations. Ann N Y Acad Sci2014;1310:111118.

    • Search Google Scholar
    • Export Citation
  • 23.

    PellagattiACazzolaMGiagounidisAA. Gene expression profiles of CD34+ cells in myelodysplastic syndromes: involvement of interferon-stimulated genes and correlation to FAB subtype and karyotype. Blood2006;108:337345.

    • Search Google Scholar
    • Export Citation
  • 24.

    SridharKRossDTibshiraniR. Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression. Blood2009;114:48474858.

    • Search Google Scholar
    • Export Citation
  • 25.

    PellagattiABennerAMillsKI. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J Clin Oncol2013;31:35573564.

    • Search Google Scholar
    • Export Citation
  • 26.

    ImHRaoVSridharK. Transcriptomic evaluation of CD34+ marrow cells from myelodysplastic syndrome patients [abstract]. Blood2014;124(Suppl 21):Abstract 1894.

    • Search Google Scholar
    • Export Citation
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