Curr Hematol Malig Rep (2013) 8:361–369 DOI 10.1007/s11899-013-0180-3
MYELODYSPLASTIC SYNDROMES (M SEKERES, SECTION EDITOR)
Standardizing the Initial Evaluation for Myelodysplastic Syndromes Danielle Marshall & Gail J. Roboz
Published online: 1 November 2013 # Springer Science+Business Media New York 2013
Abstract The myelodysplastic syndromes (MDS) pose a unique diagnostic challenge for clinicians and pathologists due to the clinicopathologic heterogeneity of the disease and overlapping features with other benign and malignant disorders. Currently, the initial evaluation of a patient with suspected MDS centers around a detailed medical history, review of the peripheral blood and bone marrow by an expert hematopathologist and risk stratification using laboratory results, morphology and cytogenetics. More sophisticated technologies, including multi-color flow cytometry, fluorescence in-situ hybridization (FISH), next-generation sequencing, and others are emerging and promise to offer significant refinements in diagnostic, prognostic and, hopefully, therapeutic information. With the incidence and prevalence of MDS increasing worldwide, it is critical for clinicians to optimize the initial evaluation of a patient with suspected disease, using a standard schema, to facilitate accurate diagnosis, risk stratification and treatment. Keywords Myelodysplastic syndrome . Diagnosis . Dysplasia . Cytopenia . Risk stratification . Initial evaluation . Differential diagnosis . Cytogenetics . Morphology . Molecular genetics . Hematologic malignancy
D. Marshall Department of Medicine, Weill Medical College of Cornell University, 515 E. 71st Street, “S” Building, Room S262, New York, NY 10021, USA e-mail:
[email protected] G. J. Roboz (*) Leukemia Program, Weill Cornell Medical College and The New York Presbyterian Hospital, 520 East 70th Street, Starr Pavilion, 3rd Floor, New York, NY 10021, USA e-mail:
[email protected]
Introduction The myelodysplastic syndromes (MDS) comprise a heterogeneous group of clonal hematopoietic stem cell disorders, characterized by one or more peripheral cytopenias, morphologic dysplasia, ineffective hematopoiesis and a variable propensity to transform to acute myeloid leukemia (AML). The pathogenesis of MDS is incompletely understood and driven by a complex interplay of abnormalities in DNA methylation, apoptosis, differentiation, immune function, signaling, stromal regulation and other processes within the bone marrow microenvironment [1–3]. The clinical and laboratory features of MDS often overlap with other benign and malignant hematological disorders. Also, accurate diagnosis of MDS involves integrating the results from an expanding array of technologically sophisticated diagnostic tools, including multi-color flow cytometry, cytogenetics, fluorescence in situ hybridization (FISH), genome-wide screening and others. Thus, establishing the diagnosis of MDS is challenging for both clinicians and pathologists. The incidence of MDS is estimated to be five per 100,000 individuals per year in the general population, with a sharp increase to 26 per 100,00 per year among those over 70 years old [4]. However, due to the diagnostic challenges described above and major inconsistencies in reporting, these statistics may significantly underestimate the true incidence of the disease. Also, it is expected that the combination of an aging population, a rising number of survivors of cancer chemotherapy and radiation therapy (known risk factors for the development of MDS), and the availability of better MDS treatments will result in increased incidence and prevalence of the disease [5]. In fact, it seems that this diagnosis, once considered rare, is becoming a significant, worldwide health problem. Therefore, to facilitate the accurate diagnosis, risk stratification and treatment of MDS, it is essential to optimize the initial evaluation of a patient with suspected disease. The
362
Curr Hematol Malig Rep (2013) 8:361–369
objective of this review is to describe the essential elements of the diagnostic workup of MDS, and to highlight emerging areas of academic investigation that may soon become part of day-to-day practice.
The Essentials Clinical Assessment In general, it is the identification of one or more cytopenias on peripheral blood laboratory testing that prompts suspicion of MDS. Patients are frequently asymptomatic, but may also present with signs or symptoms of bone marrow failure, such as fatigue (very common), shortness of breath, bleeding or bruising. The 2014 updated guidelines for diagnosing MDS have recently been released from the National Comprehensive Cancer Network (NCCN) and include the elements listed in Table 1 [6•]. Importantly, the differential diagnosis of cytopenias is broad and includes many benign and malignant disorders; these must be systematically excluded prior to confirming the diagnosis of MDS (Fig. 1). The value of a detailed history cannot be overemphasized and should include: 1. The severity, duration and pace of each identified cytopenia with review of other laboratory data prior to diagnosis, if available (especially thyroid function, lactate dehydrogenase, ferritin, renal function). 2. All medical comorbidities and their severity; a formal comorbidity index, such as the Hematopoietic Stem Cell Transplantation Comorbidity Index (HCT-CI) or Adult Comorbidity Evaluation-27 (ACE-27) may be most relevant, as these have been validated in MDS and have specific prognostic implications [7, 8]. 3. Past and current medications, including all over-thecounter drugs and supplements. 4. Transfusion history, with type of blood product, number of transfusions and dates, if available.
Table 1 Required elements for the diagnosis of MDS from the 2014 guidelines of the National Comprehensive Cancer Network (NCCN) [3] • History and physical exam • CBC, platelets, differential, reticulocyte count • Examination of peripheral smear • Bone marrow aspiration with iron stain and biopsy and cytogenetics by standard karyotyping • Serum erythropoietin (prior to red blood cell [RBC] transfusion) • RBC folate, serum B12 • Serum ferritin, iron, total iron-binding capacity (TIBC) • Documentation of transfusion history • TSH (thyroid stimulating hormone)
Fig. 1 Differential diagnosis of single o multi-lineage cytopenias
5. Prior therapy with radiation, chemotherapy or immunomodulatory agents. 6. Family history of blood disorders (may prompt genetic screening, e.g. for Fanconi’s anemia, dyskeratosis congenital or RUNX1 mutations) [6•]. 7. Significant occupational or other toxic exposures, e.g. heavy metals (especially arsenic), organic solvents, smoking, alcohol. Pathologic Classification The 2008 World Health Organization (WHO) classification of MDS (Table 2) has largely replaced the historical FrenchAmerican-British system [9], but both rely heavily on distinguishing characteristic morphologic features of the bone marrow aspirate, biopsy and peripheral blood [10, 11•]. This process generally requires an experienced hematopathologist. Morphological classification is based primarily on the percent of blasts in the peripheral blood and bone marrow, the type and degree of dysplasia and the presence of ring sideroblasts. Dysgranulopoiesis is characterized by nuclear hypolobation (pseudo-Pelger-Huët anomaly) and irregular hypersegmentation, cytoplasmic hypogranularity and the presence of pseudo Chediak-Higashi granules [6•, 10]. Dyserythropoiesis manifests as abnormalities in the nucleus, including budding, megaloblastic changes, internuclear bridging, nuclear hyperlobation, multinuclearity, and karyorrhexis. The cytoplasm of dysplastic erythroid cells may contain ring sideroblasts and vacuoles and demonstrate positive staining by the Periodic acid-Schiff test. Dysplastic megakaryocytes are characterized by small size, nuclear hypolobation and multinucleation. Bone marrow biopsy specimens are also evaluated histopathologically for cellularity,
Curr Hematol Malig Rep (2013) 8:361–369 Table 2 2008 WHO Classification of MDSa [10]
363
Disease subtype
Blood
Bone marrow
Refractory cytopenia with unilineage dysplasia (RCUD)a
Single or bicytopenia
Dysplasia in ≥10 % of one cell line
Refractory anemia with ringed sideroblasts (RARS)
Anemia
< 5 % blasts ≥ 15 % of erythroid precursors w/ring sideroblasts
No blasts
Erythroid dysplasia only < 5 % blasts Refractory cytopenia with multilineage dysplasia (RCMD)
Cytopenia(s)
Refractory anemia with excess blasts-1 (RAEB-1)
Cytopenia(s)
Dysplasia in ≥10 % of cells in ≥2 hematopoietic lineages, ± 15 % ring sideroblasts, < 5 % blasts Unilineage or multilineage dysplasia
≤2–4 % blasts
No Auer rods
<1×109/L monocytes
9
Refractory anemia with excess blasts-2 (RAEB-2) a
This subtype includes refractory anemia (RA), refractory neutropenia (RN), and refractory thrombocytopenia (RT). MDS, unclassified, previously contained all cases of RN and RT
Myelodysplastic syndrome, unclassified (MDS-U) MDS associated with isolated del(5q)
b
In the 2008 WHO classification, RAEB-t (as previously classified by the FAB group) is classified as AML with myelodysplasia-related changes ,and may be more akin to MDS than AML [9, 10]
Refractory anemia with excess blasts in transformation (RAEB-T)b
degree of maturation, degree of fibrosis and the presence of iron stores [6•]. Myeloperoxidase (MPO) and nonspecific esterase staining may be performed for lineage clarification. Cytomorphology and histopathology are especially useful in evaluating hypocellular or fibrotic marrow specimens, in which morphology may be compromised and flow cytometry is of limited utility [6•, 10]. The WHO classification combines morphologic assessment of the blood and marrow with flow cytometry, cytogenetics, molecular genetics and clinical information. The 2008 revisions resulted in new subtypes and newly recognized disease entities based on these refined diagnostic criteria, and constitute the current standard of care for the pathologic diagnosis of MDS [11•]. An International Consensus Working Group was convened in an effort to standardize the pathologic evaluation of MDS, and established the following mandatory criteria: stable cytopenia for at least 6 months (unless accompanied by a specific karyotype or bilineage dysplasia, in which case 2 months of stable cytopenias are adequate); exclusion of other potential causes of dysplasia or cytopenia; and at least one of the following criteria: 1) dysplasia (≥10 % in one or more of the three major bone marrow lineages); 2) a blast cell count of 5– 19 %; and 3) a specific MDS-associated karyotype, e.g. del(5q), del (20q), +8 or −7/del(7q) [12]. Other corroborating data may be obtained from flow cytometry, bone marrow histology,
<1×10 /L monocytes Cytopenia(s)
5–9 % blasts Unilineage or multilineage dysplasia
5–19 % blasts
Auer rods
<1×109/L monocytes Cytopenias
Anemia
±10–19 % blasts Unilineage dysplasia or no dysplasia but characteristic MDS cytogenetics, < 5 % blasts Unilineage erythroid dysplasia
Platelets normal or increased
Isolated del(5q)
Cytopenias
<5 % blasts Multilineage dysplasia
5–19 % blasts
Auer rods ± 20–30 % blasts
immunohistochemistry and molecular markers. Patients with persistent cytopenia(s) in the absence of overt dysplasia or an MDS-defining cytogenetic abnormality fall into the category of “idiopathic cytopenia of undetermined significance” (ICUS) and require careful monitoring for progression of disease [13]. Cytogenetics Historically, MDS has been characterized by the highest rate of cytogenetic aberrancies of all the hematological malignancies. Chromosomal abnormalities can be identified in approximately 50 % of MDS patients using conventional metaphase cytogenetic analysis [10, 14, 15•]. More sensitive techniques, such as single-nucleotide polymorphism microarrays (SNPA) and array comparative genomic hybridization (CGH), can identify abnormalities in nearly 80 % of cases, but these methods are not yet in common use [16–18]. Specific cytogenetic abnormalities including −7/ del(7q), -5/del(5q), inv(3)(q21q26.2), t(6;9)(p23;q34), and others define the diagnosis of MDS even in the absence of dysplasia, and a number of abnormalities are strong indicators of prognosis and clinical outcome [10]. Emerging data are slowly clarifying the pathogenic roles of specific genes that fall within chromosomal lesions, but these remain largely unknown for the majority of frequently identified abnormalities.
364
Interstitial deletions of chromosome 5q are the most common cytogenetic abnormality in MDS, and are identified in 10–15 % of patients [10, 14]. Clinically, patients with 5q deletions fall into two categories: those with del(5q) in conjunction with other cytogenetic abnormalities and/or TP53 mutation, and those with del(5q) as an isolated abnormality [19]. Patients in the first category have often received prior treatment with alkylating agents and/or radiation and have an aggressive clinical course, with a high risk of transformation to acute myeloid leukemia (AML) and poor outcomes. Patients in the second group, especially those with the 5q- syndrome (macrocytic anemia, normal or elevated platelet count, hypolobated micromegakaryocytes), generally have a favorable prognosis with low risk for transformation to AML [20]. Interestingly, although deletions of 5q are uniformly hemizygous, neither mutations nor loss of heterozygosity have been identified in the remaining allele, suggesting that the pathogenesis of MDS with 5q- deletion may be caused by haploinsufficiency or loss of tumor suppression [21, 22]. Abnormalities of chromosome 7 are seen most frequently as monosomy 7 or interstitial deletion of 7q, and are present in 10 % of de novo MDS and up to 50 % of secondary MDS after exposure to alkylating agents [10]. These lesions are generally associated with poor clinical outcomes, though a deletion of 7q may have slightly better overall survival and slightly lower risk of AML transformation than loss of the entire chromosome [14, 23]. Trisomy 8 is seen in 5–10 % of MDS patients, and is associated with an intermediate prognosis and increased response rates to immunosuppressive therapy [14, 24]. Recent evaluation of a large, international database of 2,902 MDS patients identified clonal abnormalities in 45 % of patients and defined 19 distinct cytogenetic categories [14]. These, in turn, distinguished five prognostic subgroups ranging from very good (isolated del (11q) or –Y, median survival 61 months) to very poor (>3 abnormalities, median survival 6 months). The most frequently observed abnormalities were del(5q) [n =180], +8 [n =133], -Y [n =60], del(20q) [n =48], −7 [n =46], and del (11q) [n =20]. Complex abnormalities (3–20) were seen in 9 % of patients (n =254) and were associated with extremely poor overall survival, as has been consistently reported in the literature [14, 25, 26]. The presence of complex cytogenetic abnormalities is probably evidence of clonal instability, and it has been shown that the acquisition of cytogenetic abnormalities in International Prognostic Scoring System (IPSS) low and intermediate-1 MDS patients predicts shorter transformationfree survival (13 vs. 52 months, p =0.01) and worse overall survival (17 vs. 62 months) compared to patients without acquired abnormalities [27•]. Monosomal karyotype (MK) has been shown to confer a very poor prognosis in acute myeloid leukemia [28, 29]. The prognostic implications of MK independent of complex karyotype are less clear in MDS. Several analyses have found MK to be an independent predictor of poor prognosis [30–32],
Curr Hematol Malig Rep (2013) 8:361–369
while others have not [33, 34]. In either case, MK, whether alone or in combination with other abnormalities, is an indicator of aggressive disease and poor prognosis. Frustratingly, bone marrow aspiration for some patients with MDS yields a “dry tap” or there are simply too few metaphase cells to detect cytogenetic abnormalities. Braulke et al. have recently shown that molecular cytogenetic results from CD34+ peripheral blood cells are strongly correlated (tau=0.86, p <0.01) with conventional chromosome banding [35]. Further confirmatory studies are required, but this type of analysis would be especially helpful for diagnosis in patients for whom conventional karyotyping is unsuccessful, or potentially as an alternative to serial bone marrow biopsies in lower risk patients [36].
Risk Stratification The initial evaluation of a patient with MDS should culminate in an assessment of risk and prognosis. Clinical risk stratification integrates cytogenetic information from standard metaphase banding with bone marrow blast percentage and peripheral blood cytopenias to identify subgroups that have diagnostic, therapeutic and prognostic implications in MDS. The International Prognostic Scoring System (IPSS), originally published in 1997, identified four risk categories based on these elements and has been widely validated and used [37]. The IPSS defines cytopenias as hemoglobin <10 g/dL, absolute neutrophil count (ANC) <1.8×109/L and platelets <100× 109L. Karyotype is divided into “good, intermediate and poor” and blasts are in categories of <5 %, 5–10 %, 11–20 % and 21–30 %. These elements are scored and the resultant groups have proved more accurate in assessing prognosis than previous classification systems, including the FAB [6•]. Subsequently, the WHO-classification based prognostic scoring system (WPSS) was designed to incorporate the morphologic categories from the WHO, the IPSS cytogenetic categories and the clinical assessment of transfusion dependency [38]. This has recently been refined to replace transfusion dependency with the presence or absence of severe anemia (hemoglobin levels <9 g/dL for males and <8 g/dL for females), which is a less subjective and clinically more important assessment [39]. The WPSS is not clearly a more powerful prognostic tool than the IPSS, but is included in the 2014 NCCN guidelines [6•]. The IPSS has limited ability to discriminate prognosis in lower risk MDS categories, which showed a wide range in median survival. The Lower-Risk Prognostic Scoring System (LR-PSS) was developed to address this issue and in particular identify patients with IPSS Low or Int-1 disease who have a poor prognosis, despite their relatively favorable risk stratification [40]. Significant independent predictors of survival by multivariate analysis included unfavorable cytogenetics (as defined by IPSS), age ≥60 years, decreased hemoglobin
Curr Hematol Malig Rep (2013) 8:361–369
(<10 g/dL), decreased platelet count (<50×109/L or 50–200× 109/L) and bone marrow blasts ≥4 %. These factors were given weighted scores and resulted in three risk categories, with median survival 80.3 months in category 1, 26.6 months for category 2 and 14.2 months for category 3 [40]. This LRPSS has been validated and is used for more precise risk stratification of lower-risk MDS patients [6•, 41]. A revised IPSS (IPSS-R) was published in 2012, based on 7,012 MDS patients pooled from 18 databases [26]. The IPSSR defines five new prognostic categories, with median survival ranging from 8.8 years in the very low-risk group to 0.8 years in the very high-risk group. Like the IPSS, the IPSS-R is based on cytogenetics, marrow blast percentage and cytopenias. However, the IPSS-R further refines these categories by having five cytogenetic subgroups instead of three, dividing patients with fewer than 5 % blasts into those with 0–2 % and >2–5 % blasts, consolidating patients with 11–20 % and 21–30 % blasts into a single group with >1 0 % blasts, and scoring the depth of cytopenias based on clinically and statistically relevant levels [26]. Prospective validation of the IPSS-R is required, but data so far suggest it will be more powerful than the original tool. For example, when the IPSSR was combined with the WHO classification system, it was shown to have stronger predictive power than the original IPSS [25]. Also, the Gruppo Romano Mielodisplasie retrospectively evaluated 380 patients, including those who had received treatments with transfusions, lenalidomide, azacitidine and chemotherapy, using the IPSS, IPSS-R and WPSS (WHO prognostic scoring system) classifications [42]. Of the three systems, the IPSS-R was the strongest predictor of both leukemia-free survival and overall survival. In this analysis, serum ferritin and red blood cell transfusion dependence, neither of which is included in the IPSS-R, were also independent prognostic indicators of overall survival and leukemia-free survival, respectively [42]. Emerging Tools and Technologies While it is clear that morphology and cytogenetics remain central to the initial diagnostic evaluation of MDS, other technologies are playing increasingly important roles, especially in the many cases where standard assessments fail to yield conclusive results. Investigators and clinicians are already struggling with exactly how to incorporate these data into daily practice, and expert panels have been and continue to be convened to define new guidelines [43]. Fluorescence In-Situ Hybridization (FISH) FISH testing does not cover the whole genome and will not detect all cytogenetic aberrancies; it can be used only for selected chromosomal regions. However, several studies have demonstrated that FISH may offer increased sensitivity over
365
conventional cytogenetics in the detection of certain abnormalities [44, 45], and it is also useful when a conventional chromosome banding analysis is unsuccessful or cannot be performed [46]. Flow Cytometry (FC) Basic immunophenotyping is performed routinely as part of the pathologic evaluation of bone marrow samples to characterize blasts and evaluate lymphoid populations. Flow cytometric evaluation of the peripheral blood is especially important to identify patients with paroxysmal nocturnal hemoglobinuria (PNH) and large granular lymphocytic leukemia (LGL). More sophisticated, multicolor FC may identify aberrancies in differentiation or antigen expression in both immature (blast) and maturing myeloid populations, and can be especially useful in cases in which the morphology and/or cytogenetics are unclear [10, 47]. Individual abnormalities are seen infrequently in normal controls, and the presence of multiple aberrancies has significantly higher predictive value in MDS [47, 48]. However, FC is, in many respects, an art form, and inconsistent methodologies and variability in reporting and interpretation of results have hampered its widespread integration into MDS classification and risk stratification systems. The current 2008 WHO classification recognizes the presence of three or more immunophenotypic aberrancies involving the myeloid lineage as suggestive of MDS, but not sufficient for its diagnosis [10]. Importantly, although morphologic and immunophenotypic assessments of CD34+ cells generally correlate well, marrow fibrosis and hemodilution of samples may significantly alter immunophenotypic findings, and thus, manual differential counts from bone marrow aspirate samples remain the gold standard and are the basis for all current risk stratification systems [10, 47]. The European LeukemiaNet (ELN) has led worldwide efforts to standardize the use of FC in MDS, and has published guidelines for the assessment of dysplasia in immature myeloid and monocytic progenitors, maturing neutrophils, monocytes, progenitor B cells and the erythroid compartment [47, 49–51]. Recommendations are also available for standardization of sample preparation, instrument setup and quality assessment, data acquisition, gating strategies and evaluation of appropriate normal controls [47, 50, 51]. Even with these guidelines and recommendations, FC should be used only in conjunction with other clinical and pathologic data and, in general, should be repeated at regular intervals if there is any uncertainty about the results. Expertly interpreted FC has been used to diagnose MDS in cases where cytomorphology and/or cytogenetics were inconclusive [52, 53]. The ELN developed an FC scoring system using CD34 and CD45 as markers based on 417 patients with low-risk MDS and 380 controls with non-clonal cytopenias [54]. FC patterns from the MDS patients demonstrated
366
increased myeloblast-related cluster size, decreased CD34+ Bprogenitor-related cluster size, aberrant myeloblast CD45 expression and decreased granulocyte side scatter (P <0.001). These parameters were used to create an FC score, which was validated in 797 patients and found to have 69 % sensitivity and 92 % specificity. There was also a strong correlation between high FC scores and multilineage dysplasia, transfusion dependency, poor-risk cytogenetics and likelihood of progression to MDS/AML [54]. Further studies and prospective validation of this scoring system are warranted, as are investigations of the utility of FC in discriminating prognosis, predicting response to treatment and monitoring minimal residual disease in MDS.
Curr Hematol Malig Rep (2013) 8:361–369
mutations is a major breakthrough in understanding the pathophysiology of MDS, and international efforts are underway to define the practical relevance of these mutations in the diagnosis, risk stratification and treatment of MDS. Many other somatic mutations have been identified in MDS, of variable frequency, allele burden, prognostic and diagnostic importance. The low incidence and significant variety of single-gene mutations suggests that these abnormalities are only part of a highly complex disease pathogenesis. Other data from gene expression profiling, assessments of global methylation, and miRNA profiling are also likely to contribute clinically applicable prognostic and, hopefully, therapeutic information in the near future.
Molecular Genetics The last decade has seen an explosion in next-generation DNA sequencing technologies and, as a result, molecular abnormalities, including somatic point mutations and copy number variations, have been identified in the majority of patients with MDS [55, 56]. Recurrent mutations have been identified in genes involving tyrosine kinase signaling, differentiation, cell cycle regulators, apoptosis, transcriptional regulation, epigenetic regulation and RNA splicing, and some mutations are associated with prognosis and/or clinicopathologic phenotype [3, 56]. Most of these mutations result in loss of function, rather than activation of the particular gene. Mutations in TP53, EZH2, ETV6, RUNX1 and ASXL1 have been associated with poor survival independent of other risk factors and can be tested in a commercially available panel [57•]. The same mutations were associated with shorter overall survival in lower-risk MDS patients independent of the LR-PSS [41]. Even within the relatively favorable subtype of lower-risk MDS patients with del (5q), 18 % were shown to have TP53 mutations using next-gen techniques, and patients with this mutation had inferior cytogenetic and erythroid responses to lenalidomide, as well as higher rates of transformation to AML [19]. It should be noted that the ability of any currently available MDS therapy to alter the prognosis of patients with one of more of these mutations is unclear. Recurrent mutations of the small nuclear ribonucleoprotein (snRNP) complex of the spliceosome machinery, including U2AF1, SRSF2, and SF3B1 are strongly associated with MDS [58–60]. The spliceosome is a complex of snRNA and protein subunits that removes introns and ligates flanking exons from precursor RNA segments to generate mature messenger RNAs [56]. Splicing mutations are found in 45– 85 % of MDS cases and are especially common in diagnoses characterized by significant dysplasia; e.g., chronic myelomonocytic leukemia and therapy-related MDS [56]. In particular, mutations in the splicing machinery were found in 84.9 % of MDS patient with ring sideroblasts and 43.9 % of MDS patients without ring sideroblasts, compared to 6.6 % in de novo AML patients [61]. Identification of spliceosome
Conclusions MDS is a growing health problem, with significant associated morbidity, mortality and healthcare costs. There is a clear list of “essentials” that must be included in routine clinical practice for the initial evaluation of a patient with suspected MDS: a detailed history and physical examination; expert evaluation of peripheral blood, bone marrow aspirate and bone marrow biopsy samples; and conventional cytogenetics. The obvious, major problem is that these “classical” techniques fail to clarify the nature of abnormal cytopenias for many patients, leaving diagnostic and therapeutic dilemmas for pathologists and clinicians. Additional measures, such as FISH, FC, and even next-gen sequencing, are already obtainable in the community setting and may be useful in diagnostically difficult cases, but in general, there is much to be learned about the prognostic and therapeutic utility of results from these modalities. Furthermore, while refinements in risk stratification are clearly important, it is much less clear that any of the currently available therapeutic modalities, including stem cell transplantation, are effective in altering prognosis, and novel drugs and therapeutic strategies are desperately needed. Thus, it is absolutely critical that as many newly diagnosed MDS patients as possible are enrolled onto prospective registries or databases so they can be followed for treatments and outcomes. Such registries are best conceived as prospective monitoring trials with extensive clinical annotation and correlative scientific work that includes all the “bells and whistles” of current technologic advances. The newly formed MDS Clinical Research Consortium, which includes Weill Cornell Medical Center; Cleveland Clinic Taussig Cancer Institute; DanaFarber Cancer Institute; MD Anderson Cancer Center; H. Lee Moffitt Cancer Center and Research Institute; and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, is launching just such an initiative and hopefully many others will join. Community physicians, academic physician–scientists, and patient advocacy groups must work together to help patients understand that participating in such efforts will
Curr Hematol Malig Rep (2013) 8:361–369
immeasurably accelerate progress in understanding and treating MDS, and that patients themselves are likely to benefit directly from their own contributions.
367
12.
Compliance with Ethics Guidelines Conflict of Interest Danielle Marshall and Gail J. Roboz declare that they have no conflict of interest. Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors.
13.
14.
References 15.
Papers of particular interest, published recently, have been highlighted as: • Of major importance 1. Issa JP. The myelodysplastic syndrome as a prototypical epigenetic disease. Blood. 2013;121(19):3811–7. doi:10.1182/blood-2013-02451757. 2. Pang WW, Pluvinage JV, Price EA, Sridhar K, Arber DA, Greenberg PL, et al. Hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes. Proc Natl Acad Sci U S A. 2013;110(8): 3011–6. doi:10.1073/pnas.1222861110. 3. Greenberg PL. The multifaceted nature of myelodysplastic syndromes: clinical, molecular, and biological prognostic features. J Natl Compr Canc Netw. 2013;11(7):877–85. 4. Howlader NNA, Krapcho M, Garshell J, Neyman N, Altekruse SF, Kosary CL, et al., editors. SEER cancer statistics review, 1975–2010: section 30 Myelodysplastic Syndromes (MDS), Chronic Myeloproliferative Disorders (CMD), and Chronic Myelomonocytic Leukemia (CMML). Bethesda: National Cancer Institute; 2013. http://seer.cancer.gov/csr/1975_2010/. Accessed August 15, 2013 2013. 5. Sekeres MA. Epidemiology, natural history, and practice patterns of patients with myelodysplastic syndromes in 2010. J Natl Compr Canc Netw. 2011;9(1):57–63. 6. • Greenberg PL, Attar E, Bennett JM, Bloomfield CD, Borate U, De Castro CM, et al. Myelodysplastic syndromes. J Natl Compr Canc Netw. 2013;11(7):838–74. Current NCCN guidelines for the diagnosis and treatment of MDS provide detailed recommendations and the standards of care based on updated data, with am extensive list of references. 7. Pellagatti A, Cazzola M, Giagounidis A, Perry J, Malcovati L, Della Porta MG, et al. Deregulated gene expression pathways in myelodysplastic syndrome hematopoietic stem cells. Leukemia. 2010;24(4):756–64. doi:10.1038/leu.2010.31. 8. Naqvi K, Garcia-Manero G, Sardesai S, Oh J, Vigil CE, Pierce S, et al. Association of comorbidities with overall survival in myelodysplastic syndrome: development of a prognostic model. J Clin Oncol. 2011;29(16):2240–6. doi:10.1200/JCO.2010.31.3353. 9. Bennett JM, Catovsky D, Daniel MT, Flandrin G, Galton DA, Gralnick HR, et al. Proposals for the classification of the myelodysplastic syndromes. Br J Haematol. 1982;51(2):189–99. 10. Swerdlow S, Campo E, Harris NL, Jaff ES, Pileri SA, Stein H, et al. WHO classification of tumours of haematopoietic and lymphoid tissues. 4th ed. Lyon: IARC Press; 2008. 11. • Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114(5):937–51. doi:10.1182/
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
blood-2009-03-209262. The updated 2008 pathologic classification of hematopoietic malignancies is an essential reference and integrates clinical and pathology data. Valent P, Horny HP, Bennett JM, Fonatsch C, Germing U, Greenberg P, et al. Definitions and standards in the diagnosis and treatment of the myelodysplastic syndromes: Consensus statements and report from a working conference. Leuk Res. 2007;31(6):727–36. doi:10.1016/j. leukres.2006.11.009. Valent P, Bain BJ, Bennett JM, Wimazal F, Sperr WR, Mufti G, et al. Idiopathic cytopenia of undetermined significance (ICUS) and idiopathic dysplasia of uncertain significance (IDUS), and their distinction from low risk MDS. Leuk Res. 2012;36(1):1–5. doi:10.1016/j. leukres.2011.08.016. Schanz J, Tuchler H, Sole F, Mallo M, Luno E, Cervera J, et al. New comprehensive cytogenetic scoring system for primary myelodysplastic syndromes (MDS) and oligoblastic acute myeloid leukemia after MDS derived from an international database merge. J Clin Oncol. 2012;30(8):820–9. doi:10.1200/JCO.2011.35.6394. • Afable 2nd MG, Wlodarski M, Makishima H, Shaik M, Sekeres MA, Tiu RV, et al. SNP array-based karyotyping: differences and similarities between aplastic anemia and hypocellular myelodysplastic syndromes. Blood. 2011;117(25):6876–84. doi:10.1182/blood-2010-11-314393. The most recent and comprehensive analysis of cytogenetics in MDS serves as the basis for the IPSS-R. Mohamedali AM, Alkhatabi H, Kulasekararaj A, Shinde S, Mian S, Malik F, et al. Utility of peripheral blood for cytogenetic and mutation analysis in myelodysplastic syndrome. Blood. 2013;122(4):567–70. doi:10.1182/blood-2012-12-471847. Tiu RV, Gondek LP, O’Keefe CL, Elson P, Huh J, Mohamedali A, et al. Prognostic impact of SNP array karyotyping in myelodysplastic syndromes and related myeloid malignancies. Blood. 2011;117(17): 4552–60. doi:10.1182/blood-2010-07-295857. Thiel A, Beier M, Ingenhag D, Servan K, Hein M, Moeller V, et al. Comprehensive array CGH of normal karyotype myelodysplastic syndromes reveals hidden recurrent and individual genomic copy number alterations with prognostic relevance. Leukemia. 2011;25(3):387–99. doi:10.1038/leu.2010.293. Jadersten M, Saft L, Smith A, Kulasekararaj A, Pomplun S, Gohring G, et al. TP53 mutations in low-risk myelodysplastic syndromes with del(5q) predict disease progression. J Clin Oncol. 2011;29(15):1971– 9. doi:10.1200/JCO.2010.31.8576. Padron E, Komrokji R, List AF. The 5q- syndrome: biology and treatment. Curr Treat Options Oncol. 2011;12(4):354–68. doi:10. 1007/s11864-011-0165-1. Graubert TA, Payton MA, Shao J, Walgren RA, Monahan RS, Frater JL, et al. Integrated genomic analysis implicates haploinsufficiency of multiple chromosome 5q31.2 genes in de novo myelodysplastic syndromes pathogenesis. PloS one. 2009;4(2):e4583. Heinrichs S, Kulkarni RV, Bueso-Ramos CE, Levine RL, Loh ML, Li C, et al. Accurate detection of uniparental disomy and microdeletions by SNP array analysis in myelodysplastic syndromes with normal cytogenetics. Leukemia. 2009;23(9):1605–13. doi:10.1038/leu.2009.82. Hussain FT, Nguyen EP, Raza S, Knudson R, Pardanani A, Hanson CA, et al. Sole abnormalities of chromosome 7 in myeloid malignancies: spectrum, histopathologic correlates, and prognostic implications. Am J Hematol. 2012;87(7):684–6. doi:10.1002/ajh.23230. Saumell S, Florensa L, Luno E, Sanzo C, Canizo C, Hernandez JM, et al. Prognostic value of trisomy 8 as a single anomaly and the influence of additional cytogenetic aberrations in primary myelodysplastic syndromes. Br J Haematol. 2012;159(3):311–21. doi:10.1111/bjh.12035. Bernasconi P, Klersy C, Boni M, Cavigliano PM, Dambruoso I, Zappatore R. Validation of the new comprehensive cytogenetic scoring system (NCCSS) on 630 consecutive de novo MDS patients from a single institution. Am J Hematol. 2013;88(2):120–9. doi:10.1002/ ajh.23369.
368 26. Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Sole F, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120(12):2454–65. doi:10. 1182/blood-2012-03-420489. 27. • Jabbour E, Takahashi K, Wang X, Cornelison AM, Abruzzo L, Kadia T, et al. Acquisition of cytogenetic abnormalities in patients with IPSS defined lower-risk myelodysplastic syndrome is associated with poor prognosis and transformation to acute myelogenous leukemia. Am J Hematol. 2013. doi:10.1002/ajh.23513. This reference is the manuscript introducing the revised IPSS, which is expected to become the new gold standard of risk stratification in MDS. 28. Haferlach C, Alpermann T, Schnittger S, Kern W, Chromik J, Schmid C, et al. Prognostic value of monosomal karyotype in comparison to complex aberrant karyotype in acute myeloid leukemia: a study on 824 cases with aberrant karyotype. Blood. 2012;119(9):2122–5. doi: 10.1182/blood-2011-10-385781. 29. Voutiadou G, Papaioannou G, Gaitatzi M, Lalayanni C, Syrigou A, Vadikoliou C, et al. Monosomal karyotype in acute myeloid leukemia defines a distinct subgroup within the adverse cytogenetic risk category. Cancer Genet. 2013;206(1–2):32–6. doi:10.1016/j.cancergen. 2012.10.003. 30. Gangat N, Patnaik MM, Begna K, Kourelis T, Knudson RA, Ketterling RP, et al. Evaluation of revised IPSS cytogenetic risk stratification and prognostic impact of monosomal karyotype in 783 patients with primary myelodysplastic syndromes. Am J Hematol. 2013;88(8):690–3. doi:10.1002/ajh.23477. 31. Cluzeau T, Mounier N, Karsenti JM, Richez V, Legros L, Gastaud L, et al. Monosomal karyotype improves IPSS-R stratification in MDS and AML patients treated with Azacitidine. Am J Hematol. 2013. doi:10.1002/ajh.23509. 32. Patnaik MM, Hanson CA, Hodnefield JM, Knudson R, Van Dyke DL, Tefferi A. Monosomal karyotype in myelodysplastic syndromes, with or without monosomy 7 or 5, is prognostically worse than an otherwise complex karyotype. Leukemia. 2011;25(2):266–70. doi: 10.1038/leu.2010.258. 33. Schanz J, Tuchler H, Sole F, Mallo M, Luno E, Cervera J, et al. Monosomal karyotype in MDS: explaining the poor prognosis? Leukemia. 2013. doi:10.1038/leu.2013.187. 34. Valcarcel D, Adema V, Sole F, Ortega M, Nomdedeu B, Sanz G, et al. Complex, not monosomal, karyotype is the cytogenetic marker of poorest prognosis in patients with primary myelodysplastic syndrome. J Clin Oncol. 2013;31(7):916–22. doi:10.1200/JCO.2012.41.6073. 35. Braulke F, Jung K, Schanz J, Gotze K, Muller-Thomas C, Platzbecker U, et al. Molecular cytogenetic monitoring from CD34+ peripheral blood cells in myelodysplastic syndromes: First results from a prospective multicenter German diagnostic study. Leuk Res. 2013;37(8):900–6. doi:10.1016/j.leukres.2013.03.019. 36. Braulke F, Jung K, Schanz J, Gotze K, Muller-Thomas C, Platzbecker U, et al. Molecular cytogenetic monitoring from CD34+ peripheral blood cells in myelodysplastic syndromes: First results from a prospective multicenter German diagnostic study. Leuk Res. 2013. doi:10.1016/j.leukres.2013.03.019. 37. Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G, et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997;89(6):2079–88. 38. Malcovati L, Germing U, Kuendgen A, Della Porta MG, Pascutto C, Invernizzi R, et al. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes. J Clin Oncol. 2007;25(23):3503–10. doi:10.1200/JCO.2006. 08.5696. 39. Malcovati L, Della Porta MG, Strupp C, Ambaglio I, Kuendgen A, Nachtkamp K, et al. Impact of the degree of anemia on the outcome of patients with myelodysplastic syndrome and its integration into the WHO classification-based Prognostic Scoring System (WPSS). Haematologica. 2011;96(10):1433–40. doi:10.3324/haematol.2011. 044602.
Curr Hematol Malig Rep (2013) 8:361–369 40. Garcia-Manero G, Shan J, Faderl S, Cortes J, Ravandi F, Borthakur G, et al. A prognostic score for patients with lower risk myelodysplastic syndrome. Leukemia. 2008;22(3):538–43. doi:10.1038/sj.leu.2405070. 41. Bejar R, Stevenson KE, Caughey BA, Abdel-Wahab O, Steensma DP, Galili N, et al. Validation of a prognostic model and the impact of mutations in patients with lower-risk myelodysplastic syndromes. J Clin Oncol. 2012;30(27):3376–82. doi:10.1200/JCO.2011.40.7379. 42. Voso MT, Fenu S, Latagliata R, Buccisano F, Piciocchi A, AloeSpiriti MA, et al. Revised International Prognostic Scoring System (IPSS) 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 Oncol. 2013;31(21):2671–7. doi: 10.1200/JCO.2012.48.0764. 43. Platzbecker U, Santini V, Mufti GJ, Haferlach C, Maciejewski JP, Park S, et al. Update on developments in the diagnosis and prognostic evaluation of patients with myelodysplastic syndromes (MDS): consensus statements and report from an expert workshop. Leuk Res. 2012;36(3):264–70. doi:10.1016/j.leukres.2011.11.005. 44. Adema V, Hernandez JM, Abaigar M, Lumbreras E, Such E, Calull A, et al. Application of FISH 7q in MDS patients without monosomy 7 or 7q deletion by conventional G-banding cytogenetics: does −7/ 7q- detection by FISH have prognostic value? Leuk Res. 2013;37(4): 416–21. doi:10.1016/j.leukres.2012.12.010. 45. Mallo M, Arenillas L, Espinet B, Salido M, Hernandez JM, Lumbreras E, et al. Fluorescence in situ hybridization improves the detection of 5q31 deletion in myelodysplastic syndromes without cytogenetic evidence of 5q. Haematologica. 2008;93(7):1001–8. doi: 10.3324/haematol.13012. 46. Seegmiller AC, Wasserman A, Kim AS, Kressin MK, Marx ER, Zutter MM, et al. Limited utility of fluorescence in situ hybridization for common abnormalities of myelodysplastic syndrome at first presentation and follow-up of myeloid neoplasms. Leuk Lymphoma. 2013. doi: 10.3109/10428194.2013.801470. 47. van de Loosdrecht AA, Westers TM. Cutting edge: flow cytometry in myelodysplastic syndromes. J Natl Compr Canc Netw. 2013;11(7): 892–902. 48. Wells DA, Benesch M, Loken MR, Vallejo C, Myerson D, Leisenring WM, et al. Myeloid and monocytic dyspoiesis as determined by flow cytometric scoring in myelodysplastic syndrome correlates with the IPSS and with outcome after hematopoietic stem cell transplantation. Blood. 2003;102(1):394–403. doi:10.1182/blood-2002-09-2768. 49. van de Loosdrecht AA, Ireland R, Kern W, Della Porta MG, Alhan C, Balleisen JS, et al. Rationale for the clinical application of flow cytometry in patients with myelodysplastic syndromes: position paper of an International Consortium and the European LeukemiaNet Working Group. Leuk Lymphoma. 2013;54(3):472–5. doi:10.3109/10428194. 2012.718341. 50. Westers TM, Ireland R, Kern W, Alhan C, Balleisen JS, Bettelheim P, et al. Standardization of flow cytometry in myelodysplastic syndromes: a report from an international consortium and the European LeukemiaNet Working Group. Leukemia. 2012;26(7):1730–41. doi: 10.1038/leu.2012.30. 51. Westers TM, van der Velden VH, Alhan C, Bekkema R, Bijkerk A, Brooimans RA, et al. Implementation of flow cytometry in the diagnostic work-up of myelodysplastic syndromes in a multicenter approach: report from the Dutch Working Party on Flow Cytometry in MDS. Leuk Res. 2012;36(4):422–30. doi:10.1016/j.leukres.2011.09.015. 52. Kern W, Haferlach C, Schnittger S, Haferlach T. Clinical utility of multiparameter flow cytometry in the diagnosis of 1013 patients with suspected myelodysplastic syndrome: correlation to cytomorphology, cytogenetics, and clinical data. Cancer. 2010;116(19):4549–63. doi:10. 1002/cncr.25353. 53. Bacher U, Haferlach T, Kern W, Weiss T, Schnittger S, Haferlach C. The impact of cytomorphology, cytogenetics, molecular genetics, and immunophenotyping in a comprehensive diagnostic workup of
Curr Hematol Malig Rep (2013) 8:361–369
54.
55.
56.
57.
myelodysplastic syndromes. Cancer. 2009;115(19):4524–32. doi:10. 1002/cncr.24501. Della Porta MG, Picone C, Pascutto C, Malcovati L, Tamura H, Handa H, et al. Multicenter validation of a reproducible flow cytometric score for the diagnosis of low-grade myelodysplastic syndromes: results of a European LeukemiaNET study. Haematologica. 2012;97(8):1209–17. doi:10.3324/haematol.2011.048421. Bejar R, Levine R, Ebert BL. Unraveling the molecular pathophysiology of myelodysplastic syndromes. J Clin Oncol. 2011;29(5):504– 15. doi:10.1200/JCO.2010.31.1175. Lindsley RC, Ebert BL. Molecular pathophysiology of myelodysplastic syndromes. Annu Rev Pathol. 2013;8:21–47. doi:10.1146/ annurev-pathol-011811-132436. • Bejar R, Stevenson K, Abdel-Wahab O, Galili N, Nilsson B, GarciaManero G, et al. Clinical effect of point mutations in myelodysplastic syndromes. New Engl J Med. 2011;364(26):2496–506. doi:10.1056/
369
58.
59.
60.
61.
NEJMoa1013343. This reference is an excellent review of what is currently known about the molecular pathophysiology of MDS. Graubert TA, Shen D, Ding L, Okeyo-Owuor T, Lunn CL, Shao J, et al. Recurrent mutations in the U2AF1 splicing factor in myelodysplastic syndromes. Nat Genet. 2012;44(1):53–7. doi:10.1038/ng.1031. Papaemmanuil E, Cazzola M, Boultwood J, Malcovati L, Vyas P, Bowen D, et al. Somatic SF3B1 mutation in myelodysplasia with ring sideroblasts. New Engl J Med. 2011;365(15):1384–95. doi:10.1056/ NEJMoa1103283. Abdel-Wahab O, Levine R. The spliceosome as an indicted conspirator in myeloid malignancies. Cancer Cell. 2011;20(4):420–3. doi:10.1016/j.ccr.2011.10.004. 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(7367):64–9. doi:10.1038/ nature10496.