The Multifaceted Nature of Myelodysplastic Syndromes: Clinical, Molecular, and Biological Prognostic Features

Author: Peter L. Greenberg MD1
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  • 1 From the Hematology Division, Stanford University Cancer Center, Stanford, California.

The myelodysplastic syndromes (MDS) consist of a heterogeneous spectrum of myeloid clonal hemopathies. The Revised International Prognostic Scoring System (IPSS-R) provides a recently refined method for clinically evaluating the prognosis of patients with MDS. Molecular profiling has recently generated extensive data describing critical hematopoietic molecular and biologic derangements contributing to clinical phenotypes. Current molecular insights have demonstrated roles of specific somatic gene mutations in the development and clinical outcomes of MDS, including their propensity to progress to more aggressive stages, such as acute myeloid leukemia. This article focuses on these recently reported clinical and underlying pathogenetic findings. The discussion provides a synthesis of the prognostic clinical, molecular, and biologic abnormalities intrinsic to the aberrant marrow hematopoietic and microenvironmental influences in MDS.

NCCN: Continuing Education

Accreditation Statement

This activity has been designated to meet the educational needs of physicians and nurses involved in the management of patients with cancer. There is no fee for this article. No commercial support was received for this article. The National Comprehensive Cancer Network (NCCN) is accredited by the ACCME to provide continuing medical education for physicians.

NCCN designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

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This activity is accredited for 1.0 contact hour. Accreditation as a provider refers to recognition of educational activities only; accredited status does not imply endorsement by NCCN or ANCC of any commercial products discussed/displayed in conjunction with the educational activity. Kristina M. Gregory, RN, MSN, OCN, is our nurse planner for this educational activity.

All clinicians completing this activity will be issued a certificate of participation. To participate in this journal CE activity: 1) review the learning objectives and author disclosures; 2) study the education content; 3) take the posttest with a 70% minimum passing score and complete the evaluation at http://education.nccn.org/node/23880; and 4) view/print certificate.

Release date: July 12, 2013; Expiration date: July 12, 2014

Learning Objectives

Upon completion of this activity, participants will be able to:

  • Describe the clinical, molecular, and biological prognostic features of MDS

  • Apply the Revised International Prognostic Scoring System (IPSS-R) for clinically evaluating patients with MDS

The myelodysplastic syndromes (MDS) consist of a heterogeneous spectrum of myeloid clonal hemopathies. Factors associated with the clinical and biologic nature of MDS must incorporate the 2 major features of the disease: the defective differentiation of hematopoietic cells resulting in marrow failure with associated peripheral blood cytopenias, and expansion of the abnormal clone in patients who undergo evolution to or toward acute myeloid leukemia (AML). Pathogenetic mechanisms contributing to clinical phenotypes relate to critical molecular and biologic features.

This article focuses on recently reported advances that describe major components of these variable clinical and underlying pathogenetic features. The discussion delineates molecular and biologic features intrinsic to the aberrant marrow hematopoietic and microenvironmental influences in MDS. Particular attention is given to the prognostic features associated with disease stability or progression.

Clinical Features

Prognostic Characterization

The International Prognostic Scoring System (IPSS) has been an important standard for assessing the prognosis of adult patients with untreated primary MDS.1 However, since its publication in 1997, additional prognostic systems have been suggested providing other parameters to indicate meaningful differences in clinical outcomes,2-5 and the WHO hematopathologists added a morphologic refinement of the French-American-British classification.6,7 In addition, the WHO Prognostic Scoring System (WPSS)2,3 provided new insights into prognostic variables, adding red blood cell (RBC) transfusion dependence along with IPSS cytogenetic classification and WHO dysplastic categories. Importantly, newer cytogenetic groupings have been reported to be prognostically valuable and to refine those features used in the IPSS.8

To refine the IPSS and evaluate many of the suggested prognostic features defined over the past decade, the International Working Group for Prognosis in MDS project assembled a large combined database of 7012 patients with untreated primary MDS from multiple institutions in 11 countries for more precise analysis.9 This system comprehensively integrated the numerous known clinical features into a method that analyzed prognosis more precisely than the initial IPSS. Bone marrow cytogenetics, marrow blast percentage, and cytopenias remained the basis of the new system (the Revised IPSS [IPSS-R]).10 Novel components of this scoring method include 5 rather than 3 cytogenetic prognostic subgroups with specific and new classifications of several less common cytogenetic subsets; splitting the low marrow blast percentage value; and depth of cytopenias. This model defined 5 major prognostic categories, rather than the 4 present in the IPSS.

A major component of this IPSS-R schema was the provision of 5 cytogenetic subgroups (vs 3 in the IPSS) based on an increased number of specific prognostic chromosomal categories (15) as developed by the new cytogenetic system (8) versus 7 in the IPSS. This increase in defined cytogenetic categories occurred because a larger number of patients were available for analysis of some of the relatively rare cytogenetic categories, thus improving the prognostic accuracy.

Splitting patients with fewer than 5% marrow blasts into those with 0% to 2% and greater than 2% to fewer than 5% provided groups with very-low-risk versus low-risk features. The presence of 10% to 20% marrow blasts had a similar effect on clinical outcomes, as did 21% to 30% blasts; thus, these 2 categories were combined in the predictive model. Scoring the depth of cytopenias according to the IPSS-R through subdivision at clinically and statistically relevant cut points rather than solely counting their presence was useful. The degree of anemia is an important correlate of poor clinical outcomes in MDS and seems to be a good surrogate for RBC transfusion dependence.11 In this regard, low hemoglobin levels have recently replaced RBC transfusion dependence as a prognostic parameter of the WPSS.11 Underlying this finding, chronic anemia may contribute to the high nonleukemic mortality related to cardiac disease in patients with MDS.2,3,11 The other cytopenic IPSS-R cut points (ie, low neutrophil and platelet levels) also have clinical relevance.12-16 Various other differentiating features in the IPSS-R were additive to the 5 major parameters for predicting survival, albeit not for AML evolution: age, performance status, serum ferritin, and lactate dehydrogenase levels. The impact of age was a major prognostic parameter for overall survival, which was previously shown with the IPSS and in other studies.1,2,17-20 Although these features had some additive impact on survival, this effect was relatively minor compared with that of the 5 major features used to define the IPSS-R.

Thus, compared with the IPSS, the IPSS-R showed improved predictive prognostic power with more precise prognostic categories (5 vs 4 groups in the IPSS). In particular, a substantial proportion of the patients previously placed within the IPSS intermediate-1 and -2 categories (≈20%) were more precisely separated into all 5 IPSS-R categories. For therapeutic decision-making, the IPSS-R very low and low categories correspond with the lower risk categories, and high and very high categories with the higher risk categories. Recent investigations from several centers have validated the clinical utility of this IPSS-R system for risk analysis of patients with MDS in a variety of settings.21-24

Flow cytometric studies showing diagnostic and prognostic value for analysis of MDS bone marrow have recently been reported, showing the potential clinical impact of this technology.25 This approach is addressed by van de Loosdrecht and Westers elsewhere in this issue.

Biologic and Molecular Abnormalities

Multifactorial pathogenetic features underlying MDS relate to primary disease-specific intrinsic hematopoietic stem cell (HSC) and progenitor lesions combined with an altered marrow microenvironmental milieux. These findings show that cytogenetic abnormalities, oncogenic mutations, and epigenetic changes, are associated with disease progression in MDS. A major final common pathogenetic pathway causing ineffective hematopoiesis in MDS has been the varying degrees of apoptosis of the hematopoietic precursors and their progeny, with increased apoptosis in lower-risk compared with higher-risk disease.26-31 This apoptotic process in hematopoietic precursors is increased early in the disease with associated peripheral cytopenias and diminishes with disease progression, thus permitting expansion of the abnormal clone.

Marrow Stromal Influences

Abnormal marrow stromal influences, including altered function of intramedullary phagocytic cells and an excess of inflammatory cytokines, strongly affect these altered hematopoietic processes. HSCs and myeloid progenitors in MDS have recently been characterized. A report of recent data using purified immunophenotypically defined human HSCs from MDS samples transplanted into immunodeficient mice suggested that HSCs are disease-initiating cells in MDS.30 Fluorescence in situ hybridization and gene expression data from purified HSCs of patients with del(5q) MDS also suggested an HSC origin for MDS.31-34 Loss of the more mature granulocyte-macrophage progenitors (GMPs) in the bone marrow of lower-risk patients with MDS (ie, with <5% marrow blasts) was demonstrated.30 Associated with this, in lower-risk compared with higher-risk MDS, increased prophagocytic calreticulin molecules were present on the GMP compared with antiphagocytic molecules (CD47).30 Thus, this reduction in GMPs in lower-risk MDS seems to be secondary to both increased programmed cell removal by intramedullary macrophages and to programmed cell death (apoptosis), the former being caused by upregulation of calreticulin. In higher-risk MDS, the frequency of myeloid progenitors in the bone marrow was higher than in lower-risk MDS, related to their evasion of phagocytosis through upregulation of CD4730 and decreased apoptosis.27,30 These findings of the expanded number of abnormal progenitors in higher-risk disease are consistent with these altered mechanisms of cell removal or cell death in MDS being associated with disease progression to or toward AML.

Molecular Features

Recent findings have provided major molecular insights into specific gene mutations playing critical roles in the development and clinical outcome of MDS, and its propensity to progress to a more aggressive stage. Somatic point mutations have been identified in more than 70% of patients with MDS, including most cases with a normal karyotype. These mutations are major predictors of clinical phenotype, and may also predict prognosis independent of existing clinical variables.35,36

Prognostic Molecular Abnormalities

Molecular investigations have indicated that both single-gene mutations and global differential expression profiles of genes from marrow cells have major prognostic value.37,38 These abnormalities involve genes engaged in molecular signaling and differentiation, regulation of cell cycle progression, apoptosis, transcription, translation, and epigenetics (Table 1). Genetic alterations have included oncogenic mutations, amplifications or deletions, transcriptional RNA splicing abnormalities, epigenetic changes, and/or altered telomere dynamics.

Investigations using next-generation DNA sequencing technology showed a substantial number of somatic gene mutations in marrow from patients with MDS.39 These mutations were found in 51% of the patients in at least 1 of 18 genes, including those with normal cytogenetics. Most of these mutations caused loss of function rather than being activating mutations. Some were mutually exclusive, whereas others (eg, TET2 mutations, the most commonly found mutation in ≈20% of patients) were associated with other mutations, suggesting the codependence of these mutations being related to disease status. Five gene mutations (TP53, EZH2, ETV6, RUNX1, ASXL1), present in 3% to 14% of the patients, were associated with poor overall survival (Table 1). Although these data did not relate to the potential for patients to develop AML, some of these mutations were associated with distinct clinical phenotypes and prognosis regarding survival. TP53 mutations were mainly seen in higher-risk patients, whereas mutations in EZH2 and ASXL1 were generally present in those with lower risk. RUNX and N-RAS mutations were often associated with chromosome 7 abnormalities. Having at least one of these abnormalities was additive to IPSS risk regarding patient survival, with their presence shifting patients to the next higher IPSS category. In other studies, TET2 gene mutations were also found in approximately 20% of patients with MDS, which were associated with improved prognosis.40,41

Table 1

Gene Mutations Related to Poor Prognosis in Myelodysplastic Syndromes

Table 1

In a recent study of 738 patients with MDS in which 111 candidate genes were evaluated, 41 high-confidence oncogenic mutations were found.42 One or more molecular lesions was present in 78% of the patients, 15% with pairwise associations. More than 10% of the patients had 4 gene mutations (SF3B1, TET2, SRSF2, ASXL1); 43% had 2 or 3 mutations. U2-spliceosome mutations were found in 51% of the patients. These abnormalities were generally mutually exclusive, but did co-occur with DNA methylation genes. These findings provided prognostic information in which an inverse correlation was seen between gene mutation number and overall and leukemia-free survival. Two new inactivating mutations were found (CUX1, IRF1). Mutations in CUX1 had a negative prognostic impact (Table 1).

Studies have recently defined numerous molecular abnormalities in chronic myelomonocytic leukemia (CMML).43 Nine mutations were particularly frequent, of which 93% patients had at least one such lesion (TET2, 61%; SRSF2, 47%; ASLX1, 44%; RAS, 30%; RUNX, 22%; CBL, 19%; EZH2, 11%; JAK2, 7%; IDH1/2, 5%; Table 1). The SRSF2 mutation, a member of the spliceosome complex, was generally associated with a good prognosis,43 whereas worse prognosis was found in patients with U2AF1 and DNMT3A mutations44 (Table 1).

SETBP1 mutations were recently found in a variety of myeloid malignancies (in 15% of patients with CMML and secondary AML, 7% of those with chronic myelogenous leukemia in blast crisis).45 Increased SETBP1 expression was found in MDS and therapy-related AML. This gain-of-function mutation regulates gene expression, increasing HoxA9/10 and decreasing RUNX1 expression. This mutation was shown to be acquired during leukemic evolution, have increased expression in AML, and be associated with a poor prognosis46 (Table 1). Of interest, SETBP1 is also associated with congenital cancer susceptibility (Schinzel-Giedion syndrome).45

Patients with del(5q) cytogenetics have a distinctive form of MDS, with a remarkably high erythroid and cytogenetic responsiveness to the drug lenalidomide. However, the durability of that response and the potential for AML evolution in these patients are variable. Long-term outcomes are poorer in patients with del(5q) MDS with additional cytogenetic lesions than in those with del(5q) alone.47 In contrast to earlier investigations, recent data using very sensitive next-generation sequencing techniques showed that a higher-than-expected subset of lower-risk patients with del(5q) MDS (18%) had TP53 mutations.48 The patients with mutated TP53 had poorer erythroid and cytogenetic responses to lenalidomide and a higher potential for AML evolution. These findings, with prognostic and therapeutic implications for TP53 mutations (Table 1), indicate the importance of molecular findings to help define existing heterogeneity within even an MDS subtype with a single cytogenetic abnormality.

Abnormal Transcriptional mRNA Splicing

Recurrent somatic mutations in components of the spliceosome have recently been identified with whole-genome and whole-exome sequencing of samples from patients with MDS.49-52 As a class, these mutations, including U2AF35, ZRSR2, SRSF2, and SF3B1, are remarkably common, affecting 45% to 85% of patients with MDS, depending on the morphologic subtype.49 Most of the mutations, which occurred in a mutually exclusive manner, affected genes involved in pre-mRNA processing, inducing abnormal RNA splicing and compromised hematopoiesis. Splicing mutations are generally enriched in diseases characterized by morphologic dysplasia, such as MDS, CMML, and AML with myelodysplasia-related changes. These data indicate that genetic alterations of the major transcriptional splicing components could be translated into dysfunctional proteins contributing to MDS pathogenesis. Further investigations using massively parallel sequencing technology have extended the implications of mRNA splicing abnormalities in MDS, showing mutations in SF3B1 in 20% of 354 patients, and have a high degree of specificity (65%) in patients with ring sideroblasts.50 In addition, patients with this mutation had improved survival compared with those lacking the mutation (Table 1).

Single Nucleotide Polymorphisms

In addition to standard metaphase cytogenetic analysis, single nucleotide polymorphism analysis (SNP-A) has usefully expanded the ability to analyze chromosomal abnormalities and improve the prognostic assessment of patients with MDS, including permitting evaluation of those with or without cytogenetic abnormalities.53Approximately 75% of patients with MDS had cryptic cytogenetic lesions shown by SNP-A compared with only approximately 50% by standard metaphase cytogenetics. This was particularly evident in those with normal cytogenetics, wherein 58% of the patients had abnormal SNP-A results. Patients with SNP abnormalities had poorer clinical outcomes than those lacking these findings. Recently, analysis of patients with hypoplastic MDS also showed a substantial increase in clonal abnormalities by SNP-A compared with standard metaphase cytogenetics.54 The SNP abnormalities were higher in patients with hypoplastic MDS than in those with aplastic anemia, including those with normal metaphase cytogenetics. Of interest, a portion of the patients with aplastic anemia had evolving abnormalities, suggesting that they may have initially had MDS.

MicroRNA and Ribosomal Biogenesis Abnormalities

Additional molecular features in del(5q), such as ribosomal biogenesis dysfunction and altered microRNA (miRNA) levels, also contribute to the phenotype of these patients. They have haploinsufficiency of the ribosomal protein RPS14, which activates p53, causing marrow cell apoptosis, but is blocked by the drug lenalidomide.55,56 The patients with del(5q) and low RPS14 expression had better survival than those lacking this abnormality.57 Additionally, the thrombocytosis seen in these patients relates to the decreased level of several microRNAs (miR145, miR146).58 Selective overexpression of miR181 family members was particularly detected in higher-risk MDS.59 In addition, patients with lower-risk MDS with such overexpression had poorer survival.

Gene Expression Deregulation

Deregulated gene pathways and RNA expression have been shown in MDS. Using microarray techniques, distinctive gene expression profiles (GEPs) with poor-risk gene expression signatures of MDS marrow CD34+ cells were shown in patients whose disease transformed to AML within a relatively short time (ie, 14 months) compared with those with stable disease.37 Other GEP studies have shown prognostic import for MDS.38 Among the most significantly deregulated gene pathways in early MDS were immunodeficiency, apoptosis, and chemokine signaling, whereas advanced MDS was characterized by deregulation of DNA damage response and checkpoint pathways.60

Epigenetic Alterations

Epigenetic mechanisms, such as DNA methylation and histone modifications, drive clonally propagated changes in gene expression, and these acquired abnormalities can therefore serve as molecular mediators of pathway dysfunction in neoplasia.61 MDS is characterized by frequent epigenetic abnormalities, including the hypermethylation of genes that control proliferation, adhesion, and other characteristic features of this leukemia. Alterations in DNA methylation have been implicated in the pathogenesis of MDS, although the underlying mechanism remains largely unknown. DNA hypermethylation of a variety of genes may be found in patients with early-stage MDS, affecting disparate cell functions, including CDKN2A (cell cycle), DAPK1, RIL (adhesion, motility), CDH1, and CDH13 (adhesion, motility). Disease progression is associated with additional epigenetic events. MDS and secondary AML display unique patterns and an abundance of aberrant DNA methylation.62 Modification of this hypermethylation gene profile is being used therapeutically in treating patients with MDS with hypomethylating agents such as 5-azacytidine and decitabine, often with beneficial results.

Methylation of CpG dinucleotides is mediated by DNA methyltransferases (DNMTs), including DNMT1, DNMT3A, and DNMT3B. DNMT3A mutations have been reported in patients with de novo AML, and more recently heterozygous mutations of DNMT3A were identified in 8% of patients with MDS.63 These patients had poorer overall survival and more rapid progression to AML than those without these mutations (Table 1). These findings suggest a link to the treatment responses to hypomethylating agents (DNMT inhibitors) seen in MDS.

Altered Telomere Dynamics

Telomerase, containing the human telomerase reverse transcriptase (hTERT) catalytic subunit and a small integral RNA component, synthesizes telomeres, the ends of eukaryotic chromosomes. Inhibition of telomerase activity causes cellular senescence and cell death. Telomere dynamics are altered in MDS, with telomere shortening along with disease progression, leading to genetic instability with susceptibility to further molecular alterations as the disease persists.64,65 Telomerase activity and hTERT expression is increased in marrow cells from patients with MDS, and patients with more severe disease showed significantly higher levels of hTERT expression and telomerase activity than those with more favorable disease.66 These data suggest the potential role of altered telomere dynamics in MDS progression.

Summary

The IPSS-R, with its risk-based method of characterizing primary untreated MDS, was shown to possess improved prognostic utility for assessing survival and AML evolution compared with the IPSS and other prior classification systems. As such, the IPSS-R is beneficial for clinical determination of prognostic status and for aiding the design and analysis of clinical trials for this disease. Combining these clinical features with the recently defined molecular lesions should markedly enhance the ability to provide more precise diagnostic and prognostic analyses for these patients.

The biologic and molecular data presented herein provide insights into mechanisms underlying MDS and their propensity to progress to more aggressive stages. The novel findings of programmed cell removal and cell death (apoptosis) contribute to the understanding of stage-dependent ineffective hematopoiesis in MDS. The specific genetic alterations present in individual patients with MDS explain much of the clinical heterogeneity exemplified by this spectrum of diseases. Given the low incidence and variety of single-gene mutations in MDS, individual genetic lesions are unlikely to be the sole disease-causing abnormalities in these disorders. Rather, a combination of cooperative mutations may be required, possibly together with epigenetic changes of specific gene expression. Defining lesions of the RNA splicing machinery associated with transcriptional regulatory abnormalities in MDS has opened key avenues for exploring underlying pathogenetic features. Therefore, these findings have the potential to engender discovery of targets for biospecific therapy. Extending the use of more comprehensive and sensitive methods for molecular profiling using next-generation sequencing techniques to evaluate MDS marrow cells will likely define further critical biologic lesions underlying this spectrum of diseases.

Dr. Greenberg has disclosed that he receives clinical research funding from Onconova Therapeutics, Inc.; GlaxoSmithKline; KaloBios Pharmaceuticals, Inc.; and Amgen Inc. He is on the advisory board for Novartis AG.

EDITOR

Kerrin M. Green, MA, Assistant Managing Editor, JNCCN—Journal of the National Comprehensive Cancer Network

Ms. Green has disclosed that she has no relevant financial relationships.

CE AUTHORS

Deborah J. Moonan, RN, BSN, Manager, CE Supporter Outreach

Ms. Moonan has disclosed the following relationship with commercial interests: AstraZeneca: Stockholder/Former Employee.

Kristina M. Gregory, RN, MSN, OCN, Vice President, Clinical Information Operations

Ms. Gregory has disclosed that she has no relevant financial relationships.

References

  • 1.

    Greenberg P, Cox C, LeBeau MM et al.. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood 1997;89:20792088.

  • 2.

    Malcovati L, Porta M, Pascutto C et al.. Prognostic factors and life expectancy in myelodysplastic syndromes classified according to WHO criteria, a basis for clinical decision making. J Clin Oncol 2005;23:75947603.

    • Search Google Scholar
    • Export Citation
  • 3.

    Malcovati L, Germing U, Kuendgen A et al.. Time-dependent prognostic scoringsystem for predicting survival and leukemic evolution in myelodysplastic syndromes. J Clin Oncol 2007;25:35033510.

    • Search Google Scholar
    • Export Citation
  • 4.

    Kantarjian H, O’Brien S, Ravandi F et al.. Proposal for a new risk model inmyelodysplastic syndrome that accounts for events not considered in the original International Prognostic Scoring System. Cancer 2008;113:13511361.

    • Search Google Scholar
    • Export Citation
  • 5.

    Della Porta MG, Luca Malcovati L, Strupp C et al.. Risk stratification based on bothdisease status and extra-hematologic comorbidities in patients with myelodysplastic syndrome. Haematologica 2011;96:441449.

    • Search Google Scholar
    • Export Citation
  • 6.

    Vardiman JW, Thiele J, Arber DA et al.. The 2008 revision of the WHO classificationof myeloid neoplasms and acute leukemia, rationale and important changes. Blood 2009;114:937951.

    • Search Google Scholar
    • Export Citation
  • 7.

    Bennett JM, Catovsky D, Daniel MT et al.. Proposals for the classification of themyelodysplastic syndromes. Br J Haematol 1982;51:189199.

  • 8.

    Schanz J, Tüchler H, Solé F et al.. New comprehensive cytogenetic scoring system forprimary myelodysplastic syndromes and oligoblastic AML following MDS derived froman international database merge. J Clin Oncol 2012;30:820829.

    • Search Google Scholar
    • Export Citation
  • 9.

    Greenberg P, Tuechler H, Schanz J et al.. Revised International Prognostic Scoring System for Myelodysplastic Syndromes. Blood 2012;120:24542465.

  • 10.

    Kao JM, McMillan A, Greenberg PL. International MDS risk analysis workshop(IMRAW)/IPSS re-analyzed: impact of cytopenias on clinical outcomes inmyelodysplastic syndromes. Am J Hematol 2008;83:765770.

    • Search Google Scholar
    • Export Citation
  • 11.

    Malcovati L, Della Porta MG, Strupp C et al.. Impact of the degree of anemia on theoutcome of patients with myelodysplastic syndrome and its integration into the WHO classification-based Prognostic Scoring System (WPSS). Haematologica 2011;96:14331440.

    • Search Google Scholar
    • Export Citation
  • 12.

    Sanz GF, Sanz MA, Vallespi T et al.. Two regression models and a scoring system for predicting survival and planning treatment in myelodysplastic syndromes: a multivariate analysis of prognostic factors in 370 patients. Blood 1989;74:395408.

    • Search Google Scholar
    • Export Citation
  • 13.

    Cordoba I, Gonzalez-Porras JR, Such E et al.. The degree of neutropenia has aprognostic impact in low risk myelodysplastic syndrome. Leuk Res 2012;36:287292.

    • Search Google Scholar
    • Export Citation
  • 14.

    Kantarjian H, Giles F, List A et al.. The incidence and impact of thrombocytopenia in myelodysplastic syndromes. Cancer 2007;109:17051714.

  • 15.

    Aul C, Gattermann N, Heyll A et al.. Primary myelodysplastic syndromes: analysis of prognostic factors in 235 patients and proposals for an improved scoring system. Leukemia 1992;6:5259.

    • Search Google Scholar
    • Export Citation
  • 16.

    Gonzalez-Porras JR, Cordoba I, Such E et al.. Prognostic impact of severe thrombocytopenia in low-risk myelodysplastic syndrome. Cancer 2011;117:55295537.

    • Search Google Scholar
    • Export Citation
  • 17.

    Morel P, Declercq C, Hebbar M et al.. Prognostic factors in myelodysplasticsyndromes: critical analysis of the impact of age and gender and failure to identify a very-low-risk group using standard mortality ratio techniques. Br J Haematol 1996;94:116119.

    • Search Google Scholar
    • Export Citation
  • 18.

    Kuendgen A, Strupp C, Aivado M et al.. Myelodysplastic syndromes in patientsyounger than age 50. J Clin Oncol 2006;24:53585365.

  • 19.

    Nösslinger T, Tüchler H, Germing U et al.. Prognostic impact of age and gender in 897 untreated patients with primary myelodysplastic syndromes. Ann Oncol 2010;21:120125.

    • Search Google Scholar
    • Export Citation
  • 20.

    Stauder R, Noesslinger T, Pfeilstöcker M et al.. Impact of age and comorbidity in myelodysplastic syndromes. J Natl Compr Canc Netw 2008;6:927934.

    • Search Google Scholar
    • Export Citation
  • 21.

    Ades L, Lamarque M, Raynaud S et al.. IPSS-r is a powerful tool to evaluate the outcome of MDS patient treated with azacitidine: the GFM experience [abstract]. Blood 2012;120:Abstract 422.

    • Search Google Scholar
    • Export Citation
  • 22.

    Stölzel F, Kramer M, Mohr B et al.. The prognostic impact of the IPSS-R cytogenetic scoring system for patients with MDS allows a risk-stratification for patients with MDS-derived AML [abstract]. Blood 2012;120:Abstract 1715.

    • Search Google Scholar
    • Export Citation
  • 23.

    Messa E, Gioia D, Evangelista A et al.. High predictive value of the IPSS-R: an external analysis of 646 patients from a multiregional Italian MDS registry [abstract]. Blood 2012;120:Abstract 1702.

    • Search Google Scholar
    • Export Citation
  • 24.

    Mishra A, Al Ali NH, Corrales-Yepez M et al.. Validation of the R-IPSS for patients with MDS: therapeutic implications [abstract]. Blood 2012;120:Abstract 2816.

    • Search Google Scholar
    • Export Citation
  • 25.

    Westers TM, Ireland R, Wolfgang Kern W et al.. Standardization of flow cytometry in myelodysplastic syndromes: a report from an international consortium and the European LeukemiaNet Working Group. Leukemia 2012;26:17301741.

    • Search Google Scholar
    • Export Citation
  • 26.

    Greenberg PL. Pathogenetic mechanisms underlying myelodysplastic syndrome. In: Greenberg PL, ed. Myelodysplastic Syndromes: Clinical and Biological Advances. Cambridge, England: Cambridge University Press; 2006:6394.

    • Search Google Scholar
    • Export Citation
  • 27.

    Rajapaksa R, Ginzton N, Rott L, Greenberg PL. Altered oncogene expression and apoptosis in myelodysplastic syndrome marrow cells. Blood 1996;88:42754287.

    • Search Google Scholar
    • Export Citation
  • 28.

    Raza A, Mundle S, Iftikhar A et al.. Simultaneous assessment of cell kinetics and programmed cell death in bone marrow biopsies of myelodysplastics reveals extensive apoptosis as the probable basis for ineffective hematopoiesis. Am J Hematol 1995;48:143154.

    • Search Google Scholar
    • Export Citation
  • 29.

    Parker J, Mufti G, Rasool F et al.. The role of apoptosis, proliferation and the Bcl2-related proteins in the myelodysplastic syndromes and acute myeloid leukemia secondary to MDS. Blood 2000;96:39323938.

    • Search Google Scholar
    • Export Citation
  • 30.

    Pang WW, Pluvinage JV, Price EA et al.. On hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes. Proc Natl Acad Sci (USA) 2013;110:30113016.

    • Search Google Scholar
    • Export Citation
  • 31.

    Nilsson L, Astrand-Grundström I, Anderson K et al.. Involvement and functional impairment of the CD34(+)CD38(-)Thy-1(+) hematopoietic stem cell pool in myelodysplastic syndromes with trisomy 8. Blood 2002;100:259267.

    • Search Google Scholar
    • Export Citation
  • 32.

    Nilsson L, Edén P, Olsson E et al.. The molecular signature of MDS stem cells supports a stem-cell origin of 5q myelodysplastic syndromes. Blood 2007;110:30053014.

    • Search Google Scholar
    • Export Citation
  • 33.

    Tehranchi R, Woll PS, Anderson K et al.. Persistent malignant stem cells in del(5q) myelodysplasia in remission. N Engl J Med 2010;363:10251037.

  • 34.

    Will B, Zhou L, Vogler TO et al.. Stem and progenitor cells in myelodysplastic syndromes show aberrant stage-specific expansion and harbor genetic and epigenetic alterations. Blood 2012;120:20762086.

    • Search Google Scholar
    • Export Citation
  • 35.

    Bejar R, Levine R, Ebert BL. Unraveling the molecular pathophysiology of myelodysplastic syndromes. J Clin Oncol 2011;29:504515.

  • 36.

    Rocquain J, Carbuccia N, Trouplin V et al.. Combined mutations of ASXL1, CBL, FLT3, IDH1,IDH2, JAK2, KRAS, NPM1, NRAS, RUNX1, TET2 and WT1 genes in myelodysplastic syndromes and acute myeloid leukemias. Biomed Central Cancer 2010;10:401408.

    • Search Google Scholar
    • Export Citation
  • 37.

    Sridhar K, Ross D, Tibshirani R et al.. Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression. Blood 2009;114:48474858.

    • Search Google Scholar
    • Export Citation
  • 38.

    Mills K, Kohlmann A, Williams PM et al.. Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome. Blood 2009;114:10631072.

    • Search Google Scholar
    • Export Citation
  • 39.

    Bejar R, Stevenson K, Abdel-Wahab O et al.. Clinical effect of point mutations in myelodysplastic syndromes. N Engl J Med 2011;364:24962506.

  • 40.

    Jankowska AM, Szpurka H, Tiu RV et al.. Loss of heterozygosity 4q24 and TET2 mutations associated with myelodysplastic/myeloproliferative neoplasms. Blood 2009;113:64036410.

    • Search Google Scholar
    • Export Citation
  • 41.

    Kosmider O, Gelsi-Boyer V, Cheok M et al.. TET2 mutation is an independent favorable prognostic factor in myelodysplastic syndromes. Blood 2009;114:32853291.

    • Search Google Scholar
    • Export Citation
  • 42.

    Papaemmanuil E, Gerstung M, Malcovati et al.. High throughput targeted gene sequencing in 738 myelodysplastic syndromes patients reveals novel oncogenic genes, rare driver mutations and complex molecular signatures with potential impact for patient diagnosis and prognosis in the clinic [abstract]. Blood 2012;120:Abstract LBA-5.

    • Search Google Scholar
    • Export Citation
  • 43.

    Meggendorfer M, Roller A, Haferlach T et al.. SRSF2 mutations in 275 cases with chronic myelomonocytic leukemia (CMML). Blood 2012;120:30803088.

  • 44.

    Abu Kar S, Jankowska A, Makishima H 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;98:107113.

    • Search Google Scholar
    • Export Citation
  • 45.

    Makishima H, Yoshida K, Nguyen N et al.. Somatic mutations in Schinzel-Giedion syndrome gene SETBP1 determine progression in myeloid malignancies [abstract]. Blood 2012;120:Abstract 3.

    • Search Google Scholar
    • Export Citation
  • 46.

    Cristóbal I, Blanco FJ, Garcia-Orti L et al.. SETBP1 overexpression is a novel leukemogenic mechanism that predicts adverse outcome in elderly patients with acute myeloid leukemia. Blood 2010;115:615625.

    • Search Google Scholar
    • Export Citation
  • 47.

    Mallo M, Cervera J, Schanz J et al.. Impact of adjunct cytogenetic abnormalities for prognostic stratification in patients with myelodysplastic syndrome and deletion 5q. Leukemia 2011;25:110120.

    • Search Google Scholar
    • Export Citation
  • 48.

    Jädersten M, Saft L, Smith A et al.. TP53 mutations in low-risk myelodysplastic syndromes with del(5q) predict disease progression. J Clin Oncol 2011;29:19711979.

    • Search Google Scholar
    • Export Citation
  • 49.

    Yoshida K, Sanada M, Shiraishi Y et al.. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature 2011;478:6469.

  • 50.

    Papaemmanuil E, Cazzola M, Boultwood J et al.. Somatic SF3B1 mutation in myelodysplasia with ring sideroblasts. N Engl J Med 2011;365:13841395.

  • 51.

    Graubert TA, Shen D, Ding L et al.. 2012. Recurrent mutations in the U2AF1 splicing factor in myelodysplastic syndromes. Nat Genet 2012;44:5357.

  • 52.

    Damm F, Kosmider O, Gelsi-Boyer V et al.. Mutations affecting mRNA splicing define distinct clinical phenotypes and correlate with patient outcome in myelodysplastic syndromes. Blood 2012;119:32113218.

    • Search Google Scholar
    • Export Citation
  • 53.

    Gondek LP, Tiu R, O’Keefe CL et al.. Chromosomal lesions and uniparental disomy detected by SNP arrays in MDS, MDS/MPD, and MDS-derived AML. Blood 2008;111:15341542.

    • Search Google Scholar
    • Export Citation
  • 54.

    Afable MG, Wlodarski M, Makishima H et al.. SNP array-based karyotyping: differences and similarities between aplastic anemia and hypocellular myelodysplastic syndromes. Blood 2011;117:68766884.

    • Search Google Scholar
    • Export Citation
  • 55.

    Ebert BL, Pretz J, Bosco J et al.. Identification of RPS14 as a 5q-syndrome gene by RNA interference screen. Nature 2008;451:335339.

  • 56.

    Pellagatti A, Marafioti T, Paterson JC et al.. Induction of p53 and up-regulation of the p53 pathway in the human 5q-syndrome. Blood 2010;115:27212723.

    • Search Google Scholar
    • Export Citation
  • 57.

    Czibere A, Burns I, Junge B. Low RPS14 expression is common in myelodysplastic syndromes without 5q-aberration and defines a subgroup of patients with prolonged survival. Haematologica 2009;94:14531455.

    • Search Google Scholar
    • Export Citation
  • 58.

    Starczynowski DT, Kuchenbauer F, Argiropoulos B et al.. Identification of miR-145 and miR-146a as mediators of the 5q-syndrome phenotype. Nature Med 2010;16:4958.

    • Search Google Scholar
    • Export Citation
  • 59.

    Sokol L, Caceres G, Volinia S et al.. Identification of a risk dependent microRNA expression signature in myelodysplastic syndromes. Br J Haematol 2011;153:2432.

    • Search Google Scholar
    • Export Citation
  • 60.

    Pellagatti A, Cazzola M, Giagounidis A et al.. Deregulated gene expression pathways in myelodysplastic syndrome hematopoietic stem cells. Leukemia 2010;24:756764.

    • Search Google Scholar
    • Export Citation
  • 61.

    Issa P. Epigenetic changes in the myelodysplastic syndrome. Hematol Oncol Clin North Am 2010;24:317330.

  • 62.

    Figueroa ME, Skrabanek L, Li Y et al.. MDS and secondary AML display unique patterns and abundance of aberrant DNA methylation. Blood 2009;114:34483458.

    • Search Google Scholar
    • Export Citation
  • 63.

    Walter MJ, Ding L, Shen D et al.. Recurrent DNMT3A mutations in patients with myelodysplastic syndromes. Leukemia 2011;25:11531158.

  • 64.

    Ohyashiki JH, Iwama H, Yahata N et al.. Telomere stability is frequently impaired in high-risk groups of patients with myelodysplastic syndromes. Clin Cancer Res 1999;5:11551160.

    • Search Google Scholar
    • Export Citation
  • 65.

    Lange K, Holm L, Vang Nielsen K et al.. Telomere shortening and chromosomal instability in myelodysplastic syndromes. Genes Chromosomes Cancer 2010;49:260269.

    • Search Google Scholar
    • Export Citation
  • 66.

    Briatore F, Barrera G, Pizzimenti S et al.. Increase of telomerase activity and hTERT expression in myelodysplastic syndromes. Cancer Biol Ther 2009;8:883889.

    • Search Google Scholar
    • Export Citation

Correspondence: Peter L. Greenberg, MD, Hematology Division, Stanford University Cancer Center, 875 Blake Wilbur Drive, Room 2335, Stanford, CA 94305-5821. E-mail: peterg@stanford.edu

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