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Keywords:

  • myeloid nuclear differentiation antigen (MNDA);
  • myelodysplastic syndrome (MDS);
  • flow cytometry;
  • leukemia

Abstract

  1. Top of page
  2. Abstract
  3. MATERIAL AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. LITERATURE CITED

Background:

Myeloid nuclear differentiation antigen (MNDA) is expressed in myelomonocytic cells with highest levels in mature granulocytes and monocytes. It is suggested to be expressed more weakly in patients with myelodysplastic syndromes (MDS). The analysis of MNDA therefore may improve diagnostic capabilities of multiparameter flow cytometry (MFC) in MDS.

Methods:

We used MFC for detection of MNDA expression in 269 patients with suspected or known MDS, acute myeloid leukemia (AML) or chronic myelomonocytic leukemia (CMML), cytopenia of unknown cause or without malignancy (negative controls). Results were compared with the diagnoses revealed by cytomorphology (CM) and cytogenetics (CG).

Results:

Percentages of granulocytes and monocytes with diminished MNDA expression (dimG and dimM) were higher in patients with MDS (mean ± SD, 20% ± 20%, P < 0.001 and 31% ± 24%, P < 0.001) and AML (27% ± 27%, P = 0.007 and 45% ± 31%, P = 0.001) diagnosed by CM, vs. patients without MDS (8% ± 10% and 16% ± 11%), respectively. Significant differences were also found for mean fluorescence intensity (MFI) of MNDA in monocytes which was lower in MDS (mean ± SD, 71 ± 36, P = 0.004) and AML (55 ± 39, P < 0.001) vs. no MDS samples (85 ± 28), respectively. Within patients with MDS, cases with cytogenetic aberrations showed a trend to higher %dimG (24% ± 18%, P = 0.083) compared with those without (16% ± 21%). Cut-off values for %dimG (12%) and %dimM (22%) as well as for MFI in monocytes (72) were defined capable of discriminating between MDS and non-MDS.

Conclusion:

MNDA expression in bone marrow cells can be assessed reliably by MFC and may facilitate evaluation of dyspoiesis when added to a standard MDS MFC panel. © 2012 International Clinical Cytometry Society

Myelodysplastic syndromes (MDS) include a group of biologically complex, heterogeneous and clinically variable clonal hematopoietic stem cell disorders. Dyspoiesis and increased apoptosis of hematopoietic cells in the bone marrow (BM) are followed by peripheral cytopenias and patients are at increased risk of evolution to acute leukemia. MDS patients have a reduced life expectancy in comparison with healthy controls mainly due to either infectious complications in a neutropenic state, bleeding, or progression to leukemia (1).

Because of the aforementioned heterogeneity, establishing the diagnosis MDS especially in patients with early stages of the disease can be a major challenge. Classification systems (2–6) rely on cytomorphologically detected signs of dysplasia and percentages of blasts in the BM as well as on chromosomal aberrations. Both methods, cytomorphology (CM) on the one hand and metaphase cytogenetics (CG) on the other hand harbour specific limitations. CM is a highly subjective method and therefore reproducibility has several drawbacks (7). Especially MDS with blast counts below 5% may be difficult to diagnose, as there are overlapping features with reactive conditions and nonmalignant disorders. The major limitation of CG is the fact that only approximately 50% of patients with MDS show acquired chromosomal aberrations that may prove the diagnosis of MDS (8–10) with the frequencies of those showing dependence on disease stage (11).

Multiparameter flow cytometry (MFC) is able to detect aberrant antigen expressions on the surface of different cell lineages related to MDS and therefore is considered to improve diagnostics in MDS. The method is increasingly used for diagnosing MDS and is also established as co-criterion in newer recommendations for diagnostic workup (5, 12–15). The value of MFC for making the diagnosis MDS and even in detecting prognostic factors for this disease has been demonstrated in a number of studies (16–19). Different “flow scores” have been introduced for MFC in MDS (20–22). However, MFC is also not free of subjective weighing, for example, in judging maturation patterns for granulocytes.

To make MFC more objective, there have been approaches to express aberrancies by numbers [e.g., with mean fluorescence intensities (MFIs) +/− a multiple of the standard deviation (SD)] for different antigens (21). Regardless of these efforts to improve objectivity in MFC for MDS it would be desirable to diagnose MDS by MFC with just one reliable marker as surrogate, preferably one that can be measured by numbers.

Myeloid nuclear differentiation antigen (MNDA) is a 407 amino acid nuclear hematopoietic protein of the interferon inducible p200-familiy proteins, and its encoding gene is located at chromosomal band 1q21-22 (23, 24). It is capable of DNA binding and mediating protein–protein interaction, thereby slowing down proliferation, modulating cell survival and promoting differentiation (25). MNDA is expressed in maturating normal and neoplastic myelomonocytic cells, a subset of lymphocytes and some lymphomas but not in other human cells or tissues. Its expression mounts with differentiation, the highest expression shown in mature granulocytes and monocytes (23, 26). MNDA expression has been proven to be diminished on mRNA and protein levels in patients with familial and sporadic MDS (25, 27, 28). Because it is suggested to be aberrantly expressed in MDS, the assessment of its expression might improve the diagnostic capabilities of MFC in MDS. Recently, McClintock-Treep et al. (29) assessed the expression of MNDA by means of MFC in 20 patients with MDS and 19 normal control subjects showing higher proportions of cells with diminished expression of MNDA in the myeloid progenitor subset in patients with MDS compared with controls. Differences in MFI of MNDA in those cells or other cell lineages were not addressed in their study. The objective of this study was to assess MNDA expression differences in different cell compartments between MDS, acute myeloid leukemia (AML), other cytopenic conditions and negative controls in a comprehensive cohort of patients and to correlate the results with those of CM and CG performed in parallel.

MATERIAL AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIAL AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. LITERATURE CITED

Patients

BM samples from 269 patients were included in this prospective study. All samples were sent to MLL Munich Leukemia Laboratory for diagnostic analysis by means of CM, CG (235/269 patients), and MFC. Samples were analyzed between March 2011 and July 2011. In 170 cases, MDS was suspected by the referring hematologists because of low peripheral blood counts and/or other clinical aspects; in eight patients, chronic myelomonocytic leukemia (CMML) was suspected. Two samples were sent for suspected leukemia and 19 for cytopenias of unknown cause. Another 37 patients with known MDS (30 samples without and 7 samples with previous MDS-specific therapy) were sent to MLL for follow-up as well as 3 samples with known CMML (2 without therapy). In another 30 samples, suspected lymphoma was excluded; these cases were included into this study as negative controls. Patients with known non-MDS hematological malignancies were excluded from this study. Of the 269 patients, 116 were females with a median age of 72 years (range, 23-90 years) and 153 were males with a median age of 72 years (range, 21-90 years). All patients had given informed consent for the diagnostic analyses and for further workup and research procedures. The study was performed in concordance to the Declaration of Helsinki.

CM and CG

CM was performed on May-Gruenwald-Giemsa stained BM slides. Additionally, cytochemistry was performed using iron staining, staining with myeloperoxidase and non-specific esterase using alpha-naphtyl-acetate (30–32). Diagnoses were made according to FAB criteria (33–35) and especially following the WHO classification system (6, 36). Chromosome banding analyses, performed in accordance to standard protocols, were classified according to international System for Human Cytogenetic Nomenclature (37–39). Difficult cases were clarified using fluorescence in situ hybridisation in accordance with standard procedures (40).

Multiparameter Flow Cytometry

For MFC, samples were adjusted to a concentration of 1 × 106 cells/mL. The combination of antibodies utilized for fivefold staining for standard MDS MFC (Table 1) is described elsewhere (17). All antibodies except for CD66c (BD Biosciences, Heidelberg, Germany) were purchased from Immunotech (Marseilles, France). One hundred microliters of the cell suspension was added to each tube with the corresponding monoclonal antibodies. Cells were incubated in the dark for 15 min followed by addition of ammonium chloride based erythrocyte lysis buffer (Roth, Karlsruhe, Germany) for 10 min. Afterwards they were centrifuged, washed in phosphate-buffered saline (PBS) and resuspended in 250 μL PBS. Acquisition (50,000 events) was performed on Navios cytometers (Beckman Coulter, Miami, FL) and data analysis was done using Kaluza software (version 1.1, Beckman Coulter).

Table 1. Monoclonal Antibody Combinations Used for Diagnosing MDS by MFC
CombinationFITCPEECDPC5PC7
  1. FITC, fluorescein isothiocyanate; PE, phycoerythrin; ECD, phycoerythrin-Texas Red; PC5, phycoerythrin-isocyanin 5; PC7, phycoerythrin-isocyanin 7; Mo-Ab, monoclonal antibody; MNDA, myeloid nuclear differentiation antigen.

Mo-Ab1IgG1IgG2aIgG1IgG1CD45
 Clone697.1Mc77T4-1F5679.1Mc7679.1Mc7J33
Mo-Ab2CD11bCD13HLA-DRCD16CD45
 CloneBEAR1SJ1D1Immu3573G8J33
Mo-Ab3CD71CD235aCD19CD2CD45
 CloneYDJ1.2.211E4B-7-6J3.11939C1.5J33
Mo-Ab4CD61CD5CD14CD4CD45
 CloneSZ21BL1aRMO5213B8.2J33
Mo-Ab5CD15CD66cCD3CD64CD45
 Clone80H5B6.2UCHT122J33
Mo-Ab6CD65CD56CD10CD33CD45
 Clone88H7N901ALB1D3HL60.251J33
Mo-Ab7CD36CD38CD34CD7CD45
 CloneFA6-152T165818H8.1J33
Combination MNDA
Mo-Ab1MNDACD45CD34  
 Clone3C1FJ33581  

For MNDA assessment, 100 μL of cell suspension were fixated with 100 μL of 8% fomaldehyde (Polysciences Inc., Warrington, PA) and incubated for 10 min. For permeabilization, 1 mL of IntraCell working solution (Trillium Diagnostics, Bangor, ME) was added and cells were incubated for 30 min in the dark. Cells were then washed with PBS, resuspended in 50 μL PBS and stained with 5 μL of MNDA-antibody (fluorescein isothiocyanate, FITC-conjugated, clone 3C1F, Trillium Diagnostics), 5 μL antibody against CD34 (phycoerythrin-Texas Red, ECD-conjugated) and 5μL antibody against CD45 (phycoerythrin, PE-conjugated, both Immunotech) for 30 min. After another washing step, cells were resuspended in 250 μL PBS. Acquisition was carried out on a Navios cytometer (Beckman Coulter), data analysis was performed with Kaluza software (version 1.1, Beckman Coulter).

Gating Strategy

Gating for standard MDS MFC was done as described previously (17). Gating for MNDA was done using CD45/SSC plots and CD34/SSC plots to identify cellular compartments. Granulocytes were identified in the CD45intermediate/SSCintermediate-to-high region, myeloid precursors/blasts in the CD45intermediate/SSClow region, lymphocytes were CD45high/SSClow and monocytes CD45high/SSCintermediate. CD34-positive blasts were defined by CD34intermediate-to-high/SSClow (Fig. 1). For all populations except lymphocytes, we sought to include all cells into the respective gates. Lymphocytes were used as negative control, therefore analysis aimed at obtaining a most homogenous population with a clear MNDA fluorescence peak. MNDA expression was then assessed for the individual populations as displayed in histograms. MNDA MFI as well as the percentages of cells with diminished MNDA expression within the respective cell compartments were explored (Fig. 2).

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Figure 1. Gating strategy for MNDA. For MNDA MFC gating, cell compartments (lymphocytes, Ly; granulocytes, Gra; monocytes, Mo; and myeloid precursors/blasts, Bla) were gated in the CD45/SSC plot as described in the text. CD34-positive cells were gated in the CD34/SSC plot. Since Ly were used as negative controls, the aim was not to include all respective cells into the gate but to reduce the gate in order to obtain a most homogeneous population with a sharp MNDA fluorescence peak. For all other populations, we sought to include all respective cells into the gates. MNDA expression was then assessed for the individual cell populations. [Color figure can be viewed in the online issue which is available at wileyonlinelibrary.com]

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Figure 2. (a) Results MNDA in healthy individuals. MNDA expression is displayed for each gated cell population (lymphocytes, Ly; granulocytes, Gra; monocytes, Mo; and myeloid precursors/blasts, Bla; CD34-positive cells) in a histogram. Percentages of cells with diminished and normal MNDA expression of each population were identified as well as the corresponding MFIs. In healthy individuals, predominantly one homogeneous Gra and Mo population, respectively, with high expression of MNDA was detected (unimodal distribution). In the Bla gate, all healthy individuals had two populations with different MNDA expression levels, the larger one with lower MNDA expression. Almost all CD34-positive cells showed a low MNDA expression in all healthy individuals. (b) Typical bimodal MNDA expression in MDS patients. In most patients with MDS, a bimodal MNDA expression pattern was encountered in the Gra and Mo populations, with one peak within the “normal” region and the other peak with a diminished MNDA expression level. (c) Trimodal MNDA expression in MDS patients. Some patients with MDS displayed a trimodal MNDA expression pattern in the Gra and Mo populations, with one MNDA peak within the “normal” region and two other peaks with diminished MNDA expression levels. (d) Typical MNDA expression pattern in MDS patients. In some patients with MDS, a transition between cells with normal and diminished MNDA expression was seen in the Gra population. MNDA levels above 101 were determined normal; levels below that were determined diminished. [Color figure can be viewed in the online issue which is available at wileyonlinelibrary.com]

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Statistical Analysis

Expression levels of MNDA (MFI) in different cell lineages and percentages of cells with diminished and normal MNDA expression for all of the earlier mentioned cellular compartments were compared using the Student's t test. Comparisons were made between diagnoses grouped according to CM as: no MDS (n = 100; these negative controls comprise 70 cases analyzed for suspected MDS as well as 30 cases analyzed for suspected lymphoma), MDS (n = 85), CMML (n = 9), AML (n = 19), myelodysplastic/myeloproliferative disease (MDS/MPN, n = 3), and possible MDS (n = 53, patients with morphological signs of dysplasia but not sufficient for diagnosing MDS). Additionally, differences between patients with MDS and with (n = 35) and without (n = 46) cytogenetic aberrations were studied.

For MNDA parameters showing best correlation to CM results [percentages of granulocytes with diminished MNDA expression (%dimG), percentages of monocytes with diminished MNDA expression (%dimM) and MFI in monocytes (MFI Mo)] separation according to the best cut-off levels, respectively, was compared with CM results by Fisher's exact test. All calculations were done using SPSS software (version 14.0.1, SPSS Inc., Chicago, IL). The reported P values are two-sided and significance was defined as P < 0.05.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIAL AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. LITERATURE CITED

Patients

A total of 269 BM samples from 269 patients with peripheral cytopenias, suspected or proven MDS or leukemia or with suspected lymphoma were analyzed in this study. The composition of the respective diagnoses reflects the spectrum of diagnoses yielded in a population analyzed for the cause of cytopenia and therefore includes a large portion of cases with MDS but also other diagnoses. Furthermore, cases with suspected lymphoma had been included as negative controls. Patient characteristics are detailed in Table 2. Under the terms of CM, 85 patients were diagnosed “MDS,” 100 patients were diagnosed “no MDS” (including 30 patients analyzed for suspected lymphoma), 9 patients “CMML,” 19 patients “AML,” 3 patients were diagnosed “MDS/MPN” (including one patient with RARS-T) and another 53 patients were diagnosed “possible MDS.” The term “possible MDS” meant there were cytomorphologic dysplastic features present which were not sufficient for diagnosing MDS. Within the MDS group, the following distribution between disease stages [according to WHO classification (6, 36)] was encountered: 2 patients with RA, 3 with RARS, 15 with RCMD, 8 with RCMD-RS, 35 with RAEB-1, 16 with RAEB-2, and 6 patients had 5q-syndrome. Defining low-risk MDS as <5% BM blasts and high-risk MDS as ≥5% BM blasts, 34 patients had low-risk MDS versus 51 patients with high-risk MDS.

Table 2. Patient Characteristics
No. of patients269
Sex (male/female)153/116
Age, median years (range)72 (21–90)
 All patients72 (23–90)
 Female patients72 (21–90)
 Male patients 
Diagnosis (CM), no. of patients (%):
 No MDS100 (37)
 Possible MDS53 (20)
 MDS85 (32)
  Low risk (BM blasts <5%)34 (13)
  High risk (BM blasts ≥5%)51 (19)
 AML19 (7)
 CMML9 (3)
 MDS/MPN3 (1)

Assessment of MNDA Expression by MFC

We analyzed MNDA expression by MFC in different cell lineages (lymphocytes, granulocytes, monocytes, and myeloid precursors/blasts). As described previously, the highest MNDA expression was seen in granulocytes and monocytes, with lower expression of MNDA in myeloid precursors/blasts. Bimodal and in 10 cases even trimodal expression in granulocytes and monocytes with variable MNDA expression could be found predominantly in patients with MDS, whereas patients without MDS mostly displayed a homogeneous expression of MNDA with only one strong fluorescence peak. Cells with an MNDA expression in the range of healthy individuals (peak fluorescence intensity above 10) were considered “normal”, cells with lower MNDA expression were determined “diminished”. Considering MNDA expression in the myeloid precursor/blast compartment all patients showed two populations, respectively, with peaks below and above 10. Similar to the strategy in granulocytes and monocytes, cells were titled “diminished” if peak fluorescence intensity was below 10 and “bright” if it was above 10. Almost all cells within the CD34-positive compartment expressed low levels of MNDA (fluorescence intensity <10) in all samples. To exclude spikes and false positive cells in those few exemptions with CD34-positive cells with higher MNDA expression, only cells with low MNDA level were included for the calculation of MFI. Examples for the different MNDA expression patterns in healthy individuals versus patients with MDS are pictured in Figures 2b-2d.

In some patients, preferably patients diagnosed MDS, a smooth transition between cells with diminished and normal MNDA expression was seen and no clear cut-off point between the populations could be established. In those situations, MNDA fluorescence intensity >10 was determined “normal” expression, while all events below this level were rated “diminished” expression (Fig. 2d).

Differences in MNDA Expression Between MDS and Controls

Regarding quantitative evaluation of MNDA expression, MDS and AML samples harboured consistently higher percentages of granulocytes and monocytes with diminished MNDA expression as compared with other samples. In detail, separating patients according to the CM result, the percentages of granulocytes with dim expression of MNDA (%dimG, mean ± SD, 20% ± 20% vs. 8% ± 10%, P < 0.001) as well as the respective percentages in monocytes (%dimM, 31% ± 24% vs. 16% ± 11%, P < 0.001) were significantly higher in cases with MDS versus cases without. MDS patients also had a lower MNDA MFI in monocytes (mean ± SD, 71 ± 36 vs. 85 ± 28, P = 0.004) in comparison with patients without MDS.

Looking at the myeloid precursors/blasts and the CD34-positive cells patients with MDS expressed lower MNDA levels in “myeloid progenitors/blasts with bright MNDA expression” as defined in the methods section (MFI 67 ± 24 vs. 86 ± 66, P = 0.007) and in CD34-positive cells (MFI 2.5 ± 0.9 vs. 2.8 ± 1.2, P = 0.031) in comparison to patients without MDS. There were no respective differences for myeloid progenitors/blasts with dim MNDA expression.

MNDA Expression in Borderline Cases and in AML

In cases with dysplastic features seen in CM which are not sufficient for the diagnosis of MDS and are therefore diagnostically challenging, we noted smaller but still significant differences as compared with cases with no MDS regarding %dimM (24% ± 17% vs. 16% ± 11%, P = 0.004) and MNDA MFI in monocytes (73 ± 25 vs. 85 ± 28, P = 0.011) as well as a strong trend to higher %dimG (13% ± 19% vs. 8% ± 10%, P = 0.07).

When comparing AML cases (diagnosed by CM) to patients without MDS, even larger differences than for MDS cases were observed for %dimG (27% ± 27% vs. 8% ± 10%, P = 0.007) and %dimM (45% ± 31% vs. 16% ± 11%, P = 0.001). We also detected a lower MNDA MFI in monocytes (55 ± 39 vs. 85 ± 28, P < 0.001) in AML patients as compared with samples with no MDS.

MNDA Expression in Diagnostic Subcohorts

Box-plots showing the different percentages of dimG and dimM as well as MFI in monocytes in cases without MDS, possible MDS, MDS, AML, and CMML as diagnosed by CM are shown in Figure 3. Interestingly, in patients with CMML no differences in MNDA expression were found when compared with patients with no MDS. We also examined MNDA expression levels in different MDS subgroups with low (MDS RA, RARS, RCMD, RCMD-RS) or high (RAEB-1 and RAEB-2) risk profiles. No significant differences in %dimG (17% ± 17% vs. 21.5% ± 21.5%, P = 0.272), %dimM (30% ± 23% vs. 32% ± 26%, P = 0.711) or MNDA MFI in monocytes (70 ± 31 vs. 72 ± 39, P = 0.779) were present.

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Figure 3. %dimG, %dimM, and MFI Mo in different patient groups by CM. %dimG and %dimM as well as MFI in monocytes in patients with no sign of MDS, possible MDS, MDS, AML, CMML, and MDS/MPN as diagnosed by CM are diagrammed as boxplots. Values for %dimG were 8 ± 10 (mean % ± SD), 13 ± 19, 20 ± 20, 27 ± 27, and 3.5 ± 3.0, respectively. Values for %dimM were 16 ± 11, 24 ± 17, 31 ± 24, 45 ± 31, and 8.5 ± 8.0, respectively, and values for MFI Mo were 85 ± 28 (mean ± SD), 73 ± 25, 71 ± 36, 55 ± 39, and 81 ± 29, respectively. [Color figure can be viewed in the online issue which is available at wileyonlinelibrary.com]

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MNDA Expression According to CG Results

We compared patients with MDS harbouring an aberrant karyotype to patients with a normal karyotype discovering a trend to higher values of %dimG (24% ± 18% vs. 16% ± 21%, P = 0.083) in the former.

Determination of Diagnostic Cut-Off Levels for MNDA

To evaluate MNDA expression as a diagnostic tool for MDS, we defined the most suitable cut-off values for the earlier mentioned variables with significant differences in patients with vs. without MDS (%dimG, %dimM, MFI Mo) capable of discriminating between “MDS” vs. “no MDS” as diagnosed with CM. Using cut-off levels of 12% dimG, 22% dimM and an MFI in monocytes of 72 the most significant differences were found: Patients with results beyond these cut-off levels were diagnosed MDS by CM in 72.1%, 71.4%, and 61.8%, respectively. Vice versa, patients diagnosed “no MDS” were found in 81.0%, 80.0%, and 71.0%, respectively, to exhibit ≤12% dimG, ≤22% dimM and MFI in monocytes of ≥72 (Table 3).

Table 3. Cut-Off Values for Discrimination of Patients With MDS Versus Patients Without MDS as Diagnosed by CM Considering %dimG, %dimM, and MFI in monocytes
 No MDSMDS 
  1. Cut-off values discriminating best between patients with MDS vs. patients without were defined at %dimG 12%, %dimM 22%, and MFI Mo 72. Percentages given without brackets indicate the proportion of cases classified as no MDS or MDS based on the respective MNDA parameter (correlating to specificity). Percentages given with brackets indicate the proportion of cases below and above the respective MNDA cut-off with the groups no MDS and MDS (correlating to sensitivity).

%dimG
 >12%n = 19; 27.9% (19.0%)n = 49; 72.1% (57.6%)n = 68; 100%
 ≤12%n = 81; 69.2% (81.0%)n = 36; 30.8% (42.4%)n = 117; 100%
 n = 100 (100%)n = 85 (100%) 
%dimM
 >22n = 20; 28.6% (20.0%)n = 50; 71.4% (58.8%)n = 70; 100%
 ≤22n = 80; 69.6% (80.0%)n = 35; 30.4% (41.2%)n = 115; 100%
 n = 100 (100%)n = 85 (100%) 
MFI Mo
 <72n = 29; 38.2% (29.0%)n = 47; 61.8% (55.3%)n = 76; 100%
 ≥72n = 71; 65.1% (71.0%)n = 38; 34.9% (44.7%)n = 109; 100%
 n = 100 (100%)n = 85 (100%) 

Integration of MNDA into a Diagnostic MFC Panel

To assess the impact of including MNDA expression as a marker into a diagnostic antibody panel for MDS we correlated the diagnostic results by CM with those by MFC without MNDA and by MFC with MNDA for patients with suspected MDS (n = 145) who were diagnosed either “no MDS,” “possible MDS,” or “MDS” by CM and at the same time either “no MDS,” “possible MDS” or “in agreement with MDS” by standard MDS MFC. While both comparisons resulted in highly significant correlations between CM and MFC (P < 0.001 for both) the use of MNDA improved the diagnostic yield of MFC: The rate of MDS cases correctly identified by MFC increased from 36/46 (78.3%) to 42/46 (91.3%) while the rate of false positive cases increased from 5/53 (9.4%) to 10/53 (18.9%). Notably, among the latter 10 cases, three carried an aberrant karyotype and must thus be considered MDS. Therefore, regarding a combination of CM and CG as comparator, MFC with MNDA resulted in a false positivity rate of 7/50 (14.0%) and a rate of 45/49 (91.8%) correctly identified MDS cases. Considering cases with “possible MDS” by CM, the addition of MNDA assessment to standard MDS MFC raised the portion of patients diagnosed “in agreement with MDS” by MFC from 26/46 patients (56.5%) to 31/46 patients (67.4%).

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIAL AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. LITERATURE CITED

The diagnosis of MDS has been clearly defined and relies on BM evaluation by CM and CG (2–6). However, equivocal results are obtained in some cases and MFC has already been established as co-criterion for the diagnosis of MDS in this situation (5, 12–15). Nevertheless, up to now, there is no exclusive tool of ensuring suspected MDS. The expression of MNDA in different human cells has been tested with different methods since its discovery. It has been detected in myelomonocytic precursors, monocytes, macrophages, subsets of normal B cells, AML blasts with maturation and certain B cell lymphomas, but not in other BM cells or nonhematopoietic cells, acute lymphatic leukemias, biphenotypic leukemias, AML without maturation and lymphatic blast crisis of chronic myeloid leukemia (23, 26, 41–44). Because both protein and gene expression of MNDA have been found at lower levels in patients with MDS (25, 27, 28) and given the availability of an MNDA-antibody applicable in MFC, the examination of MNDA expression by MFC is considered a potential discriminator between patients with MDS and those with other causes for cytopenias and healthy individuals. McClintock-Treep et al. (29) compared the BM of 20 MDS patients with BM of 19 healthy controls, suggesting there were significant differences in the percentage of myeloid precursor cells with low MNDA expression in the MDS cohort. These results needed to be verified in a larger cohort and to be extended to other cell lineages known to be involved in MDS.

In our study, we focussed on differences of MNDA expression in different BM cell compartments and detected a significantly higher percentage of granulocytes and monocytes with diminished MNDA expression in patients with MDS and AML compared with patients without MDS. Additionally, we found a significantly lower MNDA MFI in monocytes in MDS patients. Comparing our results with those of the group of McClintock-Treep (29), it has to be taken into account that according to our gating strategy, the cells titled “myeloid precursors” in their work were identical with the granulocytes in our analyses. Therefore, in our study on a large cohort of patients, we were able to confirm a significantly higher percentage of myeloid precursors/granulocytes with low MNDA expression in patients with MDS vs. those without.

Whilst in their study on 20 patients with MDS and 19 healthy individuals, the median level of %dimG in patients with MDS was 67.4% (range, 0.7%–97.5%) vs. 1.2% (range, 0.2%–13.7%) the difference between MDS vs. no MDS patients was less pronounced in our study (median, 13.5%; range, 0.6%–94.3% vs. 4.7%, range, 1%–79.3%; mean ± SD, 20% ± 20% vs. 8% ± 10%). Consequently, the cut-off value for %dimG capable of discriminating between patients with and without MDS was slightly higher (12%) in our hands than in the study of McClintock-Treep (8.4%).

In our work, we not only focussed on MNDA expression in granulocytes but further evaluated MNDA expression in monocytes, myeloid precursors and CD34-positive blasts. In line with the results in granulocytes, we could show a diminished expression of MNDA in a significantly greater percentage of monocytes of patients with MDS as compared with patients without. Considering absolute values of MNDA expression in different cell compartments measured by MFI, monocytes, blasts with high MNDA expression and CD34-positive blasts revealed significantly lower values for MNDA MFI in MDS patients than in patients without MDS. The application of cut-off values for %dimMo and MFI in monocytes to discriminate between MDS and no MDS also yielded significant differences; however, in congruence with published experience on the use of MFC to diagnose MDS (22, 45), MNDA expression as a single marker may not be considered sufficient to diagnose MDS. Nevertheless, when adding MNDA expression as additional marker to a standard diagnostic MDS MFC antibody panel, our results showed improved diagnostic accuracy when comparing diagnoses made by CM combined with CG versus diagnoses made by MFC.

In addition to the analyses in patients with MDS, we also examined MNDA expression in 19 patients with AML and found significantly higher percentages of %dimG and %dimM as well as lower MFI values in monocytes compared with patients without MDS. Notably, of the 19 AML patients, 5 were borderline AML/MDS and 5 had AML secondary to MDS. However, these cases did not show differences in MNDA expression as compared with the other AML cases which were morphologically and cytogenetically heterogeneous. Thus, from our data set on MNDA expression in AML no definite conclusions can be drawn. If MDS patients with lower MNDA expression might have a higher risk of progression to AML and thus an inferior prognosis should be prospectively evaluated in studies with long-term clinical follow-up. Also, MNDA expression in AML should be further examined and correlated to AML subgroups and long-term outcome.

Interestingly, MNDA expression in patients with CMML lacked aberrant levels as detected in MDS and AML and was equal to normal controls. These data might argue for differences in the pathogenesis of these diseases and thus be considered in line with classifying CMML as a myeloproliferative rather than as a myelodysplastic disease (6).

Taken together, our results indicate that MNDA expression assessed by MFC is an interesting and useful tool in the diagnostic workup for MDS, when integrated in MFC panels as an additional marker for the assessment of dyspoiesis of the myelomonocytic lineage. However, the value of the additional information gained by this marker needs to be challenged in future studies.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIAL AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. LITERATURE CITED

The authors thank Bruce Davis (Trillium Diagnostics, Bangor, ME) for kindly supplying them with the MNDA-FITC-conjugated antibody and IntraCell buffer. W.K. and F.B. performed design of study and data analysis. T.H. was responsible for cytomorphology. W.K., F.B., and E.G. were responsible for immunophenotyping. S.S. was responsible for molecular analysis. C.H. was responsible for chromosome banding analysis. T.A. performed statistical analysis. All authors reviewed the manuscript and approved the final version. F.B., T.A., and E.G. are employed by the MLL Munich Leukemia Laboratory GmbH. W.K., S.S., C.H., and T.H. declare part ownership of the MLL Munich Leukemia Laboratory GmbH.

LITERATURE CITED

  1. Top of page
  2. Abstract
  3. MATERIAL AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. LITERATURE CITED
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