Evaluation of flow cytometric assessment of myeloid nuclear differentiation antigen expression as a diagnostic marker for myelodysplastic syndromes in a series of 269 patients

Abstract Background: Myelodysplastic syndromes (MDS) are considered clonal diseases and are diagnosed according to WHO by cytomorphology and cytogenetics. The diagnostic potential of flow cytometric aberrancies has not yet been comprehensively evaluated. Aim: Multicenter prospective evaluation of diagnostic potential of flow cytometric aberrancies predefined according to European LeukemiaNet (ELN). Methods: 1682 patients undergoing diagnostics for suspected MDS according to WHO 2016 criteria were analyzed in parallel by flow cytometry according to ELN recommendations. Results: Median age was 72 years (18-97). MDS, MPN-RS-T or CMML were confirmed by cytomophology in 1029 (61%) cases, 653 (39%) were non-MDS. IPSS-R data was available in 857 (51%). An overall flow cytometric readout was available in 1679 (99.8%). 1001 (60%) were in agreement with MDS while 678 (40%) were not. Flow cytometric readout significantly correlated with cytomorphologic diagnosis (p<0.001): 850 (51%) were positive by both methods (flow+/cyto+), 502 (30%) were flow-/cyto-, 176 (10%) were flow-/cyto+ and 151 (9%) flow+/cyto-. The rate of flow+ was higher in high-risk MDS (MDS-EB1/2, 92%) and CMML (89%) compared to low-risk MDS (76%). Accordingly, regarding IPSS-R highest frequency of flow+ was found in very high risk (96%) and lowest one in very low risk group (64%). Non-MDS cases had a fewer myeloid progenitor cells (MPC) (mean±SD, 0.8±0.9%) compared to low-risk MDS (1.7±2.3%, p<0.001), high-risk MDS (6.3±5.0%, p<0.001) and CMML (1.9±2.6%, p<0.001). In particular, MPC >3% was strongly associated with MDS/CMML (286/293, 98%, p<0.001). Antigen expression aberrancies in MPC were more frequent in cases with MDS or CMML than in non-MDS cases but differed between entities with lower frequencies in low-risk MDS cases (table 1). Neutrophil aberrancies were found more frequently in neoplastic cases than in non-MDS cases (table 1). Again, frequencies of aberrations were higher for high-risk MDS as compared to low-risk MDS while this was not the case for CMML showing frequencies rather similar to low-risk MDS. Frequencies of aberrancies in monocytes revealed a similar figure as in neutrophils with higher rates in neoplastic cases but clearly significant numbers positive in non-MDS cases. Interestingly, frequencies were not higher in high-risk MDS as compared to low-risk MDS. As anticipated, frequencies were highest in CMML (table 1). Regarding erythroid cells only an aberrant percentage of them and aberrant CD71 expression were found in a reasonable number of cases. Importantly, rates of positivity were rather high in non-MDS cases which did not differ from CMML cases (table 1). In order to identify the diagnostic value of each individual aberrancy multivariate analyses were performed in the three subgroups, low-risk MDS, high-risk MDS and CMML, as well as in the total cohort. In low-risk MDS ten aberrancies were independently related to MDS (table 2). Five of these aberrancies were found in MPCs, two each in neutrophils and monocytes and one in erythroid cells. In high-risk MDS 11 aberrancies were independently related to MDS (table 2). Eight were found in MPCs, two in neutrophils, none in monocytes and one in erythroid cells. In CMML 12 aberrancies were independently related to CMML (table 2). Four were found in MPCs, neutrophils and monocytes, respectively, and none in erythroid cells. Considering all these three groups together and all aberrancies identified significantly related to MDS/CMML in at least one group in univariate analysis, multivariate analysis identified 12 aberrancies independently related to MDS/CMML (table 2). Six were found in MPCs, two in neutrophils, three in monocytes and one in erythroid cells. Taking into consideration only aberrancies independently associated with MDS/CMML, three such aberrancies resulted in an 80% agreement with the cytomorphologic diagnosis of MDS/CMML, i.e. 20% concordantly negative and 60% concordantly positive. Importantly, this applies without need of at least two cell compartments being affected as specified in the ELN recommendations. Conclusions: This multicenter prospective evaluation confirms the diagnostic potential of flow cytometric aberrancies. A core set of 17 markers identified as independently related to a diagnosis of MDS/CMML is suggested mandatory for flow cytometric evaluation of suspected MDS. An MPC count >3% should be considered indicative of MDS/CMML. Figure 1 Figure 1. Disclosures Kern: MLL Munich Leukemia Laboratory: Other: Part ownership. Eidenschink Brodersen: Hematologics, Inc.: Current Employment, Other: Equity Ownership. Van de Loosdrecht: Celgene: Consultancy, Research Funding; Amgen: Consultancy; Roche: Consultancy; Novartis: Consultancy; Alexion: Consultancy.

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Flow cytometry in the diagnosis of myelodysplastic syndromes and the value of myeloid nuclear differentiation antigen

Cytometry Part B Clinical Cytometry ◽

10.1002/cyto.b.21190 ◽

2015 ◽

Vol 92 (3) ◽

pp. 200-206 ◽

Cited By ~ 6

Author(s):

Frauke Bellos ◽

Wolfgang Kern

Keyword(s):

Flow Cytometry ◽

Myelodysplastic Syndromes ◽

Differentiation Antigen ◽

Nuclear Differentiation

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Quantitative Assessment of Myeloid Nuclear Differentiation Antigen Distinguishes Myelodysplastic Syndrome From Normal Bone Marrow.

Blood ◽

10.1182/blood.v114.22.1754.1754 ◽

2009 ◽

Vol 114 (22) ◽

pp. 1754-1754

Author(s):

Head R. Head ◽

Sara A. McClintock-Treep ◽

Leanne flye-Blakemore ◽

Claudio Mosse ◽

Madan Jagasia ◽

...

Keyword(s):

Flow Cytometric Analysis ◽

Bimodal Distribution ◽

Refractory Anemia ◽

Low Grade ◽

Differentiation Antigen ◽

Down Regulation ◽

Flow Cytometric ◽

Nuclear Differentiation ◽

Quantitative Flow ◽

Myeloid Progenitors

Abstract Abstract 1754 Poster Board I-780 Introduction Definitive diagnosis and classification of MDS are often difficult because of variable presence of diagnostic criteria and imprecision and ambiguities of interpretation of both morphologic and ancillary data. An objective criterion that reliably distinguishes MDS from normal marrow would greatly facilitate diagnosis, and might contribute to subclassification of MDS. Gene expression profiling has identified marked (7 fold) down-regulation of myeloid nuclear differentiation antigen (MNDA) message in cases of MDS (Hofmann WK, et al, Blood 2002;100:3553-60), and we have previously shown down-regulation of MNDA protein expression in random MDS cases using immunohistochemistry and flow cytometry (Briggs RC, et al. Cancer Research 2006;66:4645-51). To continue our previous analyses, we evaluated MNDA expression in myeloid progenitors using quantitative flow cytometric analysis in MDS and normal control marrow samples. Patients and Methods The study included 20 MDS patients receiving only supportive care undergoing bone marrow sampling for clinical purposes, and 19 frequency age-matched normal controls undergoing orthopedic surgery with no antecedent primary hematologic abnormalities. MDS diagnosis was based on 2008 WHO criteria. Quantitative flow cytometric analysis was performed with an FC500 flow cytometer (Beckman Coulter, Fullerton, CA). Cells were treated with CD45-PE and CD34-ECD (Beckman Coulter), washed in PBS with 2% FCS, and permeabilized with PermiFlow. MNDA-Alexa-488 was added at a granulocyte-monocyte specific concentration, with analysis using Winlist 5.0 software (Verity Software, Topsham, ME) with DDE links to ModFitLT 3.0 using modifications of published methods. Differentiating myeloid progenitors were identified as high side scatter/intermediate CD45/CD34-negative cells, with lymphocytes (low side scatter/high CD45/CD34-negative cells) serving as an internal dim MNDA control in each sample. Results MDS cases consisted of 12 patients with refractory cytopenia with multilineage dysplasia (RCMD), 3 with refractory anemia with excess blasts-1(RAEB-1), 4 with RAEB-2, and 1 with therapy-related MDS. In myeloid progenitors in MDS patients, the median percent of MNDA-dim cells was 67.4% (range 0.7-97.5%, interquartile range 44.9-82.7%). The analogous median percent of MNDA-dim cells in control patients was 1.2% (range 0.2-13.7%, interquartile range 0.6-2.7%). The area under the ROC curve was 0.96 (p = 9×10-7), indicating almost complete discrimination between cases and controls. 19 of 20 MDS patients demonstrated bimodal distribution of MNDA expression comprising a distinct MNDA-dim population and a separate MNDA-normal population, suggesting an admixture of MDS and normal cells. 18 of 19 control patients demonstrated a single population of MNDA-normal cells without evidence of a bimodal distribution. The single MDS patient with normal MNDA expression had prior clinical and laboratory features suggestive of refractory anemia with ringed sideroblasts. The single pediatric MDS patient had reduced MNDA expression similar to other high grade MDS samples. Patients showed trends for MDS subtype (p = 0.21) and IPSS score (p = 0.07) versus percent MNDA-dim myeloid progenitors. These data demonstrate remarkable sensitivity and specificity for use of MNDA expression to detect MDS. Conclusions Quantitative flow cytometric analysis of MNDA expression in marrow myeloid progenitors is a promising objective test for diagnosis of MDS, demonstrating a striking difference of MNDA expression in myeloid progenitors in MDS versus control patients. Our results require elaboration with analysis of low grade cases. A single possible low grade MDS case in this series demonstrated MNDA expression identical to normal control samples. Our results also require elaboration in cases constituting the differential diagnosis of MDS to evaluate the clinical utility of MNDA evaluation. The biological significance of down-regulation of MNDA in MDS is uncertain, although MNDA has been implicated in regulation of programmed cell death. Our results suggest a mix of normal and abnormal myelopoiesis in MDS patients, as predicted by cytogenetics in many cases of MDS. In summary, testing of MNDA expression in myeloid progenitors shows great promise as an objective test for diagnosis of MDS in marrow samples. Disclosures No relevant conflicts of interest to declare.

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Degree of Aberrant Antigen Expression in Myelodysplastic Syndromes Correlates with the Number of Molecular Mutations

Blood ◽

10.1182/blood.v126.23.2856.2856 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2856-2856

Author(s):

Wolfgang Kern ◽

Manja Meggendorfer ◽

Seishi Ogawa ◽

Claudia Haferlach ◽

Susanne Schnittger ◽

...

Keyword(s):

Flow Cytometry ◽

Molecular Genetics ◽

Myelodysplastic Syndromes ◽

Antigen Expression ◽

Erythroid Cells ◽

Employment Equity ◽

Cell Compartment ◽

Flow Cytometric ◽

Equity Ownership ◽

Myeloid Progenitors

Abstract Introduction: The diagnostic approach for suspected myelodysplastic syndromes (MDS) is evolving and flow cytometry and molecular genetics are increasingly considered to be applied in addition to cytomorphology and cytogenetics. While reports on comparisons of flow cytometric findings with results of cytomorphology and cytogenetics are available, data on comparisons between results obtained by flow cytometry and molecular genetics, however, have not yet been presented in detail. Aims: 1) To assess the correlation between flow cytometric findings on MDS-specific aberrant antigen expression and the presence of molecular mutations in patients with cytomorphologically proven MDS. 2) To determine the respective impact of flow cytometric findings and of molecular mutations on survival in patients with MDS. Patients and methods: In 256 patients (male/female, 161/95; median age 72 years, range 24-90) with proven MDS (137 low-risk MDS, 119 RAEB1/2) we compared data on aberrantly expressed antigens (AEA) determined according to ELN guidelines (Westers, Leukemia 2012) to the previously published mutational status of 104 genes (Haferlach, Leukemia 2014). Results: Median numbers (ranges) of AEA were 0 (0-3) in myeloid progenitors, 2 (0-4) in granulocytes, 1 (0-5) in monocytes and 0 (0-1) in erythroid cells. Median number of mutation was 2 (0-7). The number of AEA in myeloid progenitors, granulocytes and monocytes increased with increasing number of mutations (r=0.257, p<0.001). Accordingly, in cases with ≥3 mutations the number of AEA in myeloid progenitors, granulocytes and monocytes was higher than in cases with ≤2 mutations (mean±SD, 3.9±1.9 vs. 3.0±2.0, p=0.001). This correlation was significant also when considering granulocytes as a single cell compartment (r=0.308, p<0.001) but non-significant trends only for myeloid progenitors and monocytes. No such correlation was observed for erythroid cells. Specifically, mutations in each of the genes TET2, ASXL1, SRSF2, STAG2, ZRSR2 or NF1 were associated with significantly higher numbers of AEA in ≥1 cell compartment. Cases with mutations in ≥1 of these genes (n=145), as compared to those without these 6 mutations (n=111), had higher numbers of AEA in myeloid progenitors (0.4±0.7 vs. 0.2±0.5, p=0.037), granulocytes (2.0±1.1 vs. 1.4±1.1, p<0.001) and monocytes (1.5±1.3 vs. 1.0±1.0, p=0.002). Consequently, the difference in the total of AEA was even larger (3.9±2.0 vs. 2.7±1.9, p<0.001). Regarding scoring points according to IPSS-R, there was a significant correlation with the number of AEA in granulocytes (r=0.189, p=0.004) as well as with the number of AEA in monocytes (r=0.159, p=0.017). Consequently, there was also a significant correlation between the IPSS-R scoring points and the number of AEA in myeloid progenitors, granulocytes and monocytes (r=0.227, p=0.001). Overall survival was impacted by the presence of mutations in ≥1 of the genes TP53, EZH2, ETV6, RUNX1 and ASXL1 (p<0.001, HR 2.9) published by Bejar (NEJM 2011) as well as by the presence of ≥3 AEA in myeloid progenitors, granulocytes and monocytes (p=0.015, HR 1.7) and by IPSS-R (p<0.001, HR 1.4). Multivariate analysis considering mutations and AEA revealed an independent significance for both of them (mutations, p<0.001, HR 2.9; AEA, p=0.017, HR 1.7). However, inclusion of also IPSS-R as a covariate resulted in a trend only for AEA (p=0.16, HR 1.4) and independent significance for mutations (p<0.001, HR 2.3) and IPSS-R (p<0.001, HR 1.3). Conclusions: This data demonstrates that the degree of flow cytometric findings on MDS-related aberrant antigen expression correlates with the number of molecular mutations as well as with the IPSS-R. The present result therefore further support the consideration of both flow cytometry and molecular genetics for the diagnostic work-up of MDS in an integrated approach in combination with cytomorphology and cytogenetics. Disclosures Kern: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Myeloid Nuclear Differentiation Antigen (MNDA) Expression: A Useful Marker in the Diagnosis of Myelodysplastic Syndromes By Flow Cytometry

Blood ◽

10.1182/blood.v126.23.5235.5235 ◽

2015 ◽

Vol 126 (23) ◽

pp. 5235-5235

Author(s):

Frauke Bellos ◽

Torsten Haferlach ◽

Bruce H. Davis ◽

Claudia Haferlach ◽

Susanne Schnittger ◽

...

Keyword(s):

Flow Cytometry ◽

Progenitor Cells ◽

Myelodysplastic Syndromes ◽

Normal Karyotype ◽

Differentiation Antigen ◽

Employment Equity ◽

Myeloid Progenitor ◽

Myeloid Progenitor Cells ◽

Equity Ownership ◽

Nuclear Differentiation

Abstract Background: Diagnostic workup for suspected myelodysplastic syndromes (MDS) is increasingly done with the aid of multiparamter flow cytometry (MFC) detecting aberrant antigen expression. Myeloid nuclear differentiation antigen (MNDA) is a hematopoietic protein expressed strongly in mature myeloid cells, but only weakly in myeloid progenitor cells. Recently, reduced MNDA expression was detected by MFC in monocytes (M), granulocytes (G) and myeloid progenitor cells (MP) in patients (pts) with MDS and MNDA as additional marker for MFC was proposed to improve diagnostic capabilities of MFC. Aim: To verify differences in MNDA expression in M, G and MP of pts with MDS vs. those without MDS and to test its value as additional MFC parameter in a cohort with suspected MDS. Patients and methods: We analysed bone marrow from 131 pts (median age 74, range 17-93 years) with suspected MDS by cytomorphology (CM), standard 10-color-MFC and cytogenetics (CG) in parallel. For detection of MNDA expression we applied a readily available five color intracellular staining assay using monoclonal antibodies against MNDA, CD45, CD64, CD15 and myeloperoxidase (MDS-Quant, Trillium Diagnostics, Bangor, ME). Different gating strategies to best define M [SSC/CD45 plot (A) vs CD16/CD15 plot (B)], G (A vs B) and MP (A) were used. MNDA expression in pts diagnosed with no MDS (n=35), possible MDS (n=40; based on morphologic dysplastic changes insufficient for diagnosis of MDS) and MDS (n=56) by CM was compared. We also correlated results to findings in standard MDS-MFC (n=128) and CG (n=120). Results: Based on CM diagnosis, pts with MDS showed higher percentages of G and M with weak expression of MNDA (%dimG and %dimM) than no-MDS pts irrespective of the gating strategy [mean±SD, %dimG: 16±17 vs 6±7, p<0.001 (A) and 3±3 vs 1±2, p=0.011 (B); %dimM: 22±21 vs 15±12, p=0.054 (A) and 14±25 vs 4±4, p=0.004 (B)]. Diagnostically challenging cases with "possible MDS" by CM also displayed significantly higher %dimG and %dimM than no-MDS cases [%dimG 13±14 vs 6±7, p=0.006 (A), %dimM: 23±20 vs 15±12, p=0.027 (A) and 17±24 vs 4±4, p=0.002 (B)]. Differences between MDS and possible MDS existed only in higher %dimGra in MDS gated in plot B (2.7±3.3 vs 1.6±1.9, p=0.036). Conversely, MDS pts and pts with possible MDS had higher percentages of MP with high MNDA expression (%hiMP) than no-MDS pts (17±16 vs 9±8, p=0.005 and 14±13 vs 9±8, p=0.041, respectively). MNDA expression levels measured by mean fluorescence intensity (MFI) were diminished in M of pts with MDS vs no-MDS [26±12 vs 33±9, p=0.006 (A) and 30±14 vs 39±10, p=0.002 (B), respectively] and in pts with possible MDS vs no-MDS pts [26±12 vs 33±9, p=0.004 (A) and 30±2 vs 39±10, p=0.005, respectively]. Looking at the low level MNDA MP (dimMP), higher MFIs were found in MDS compared to no-MDS (1±0.8 vs 0.7±0.4, p=0.002) and in possible MDS vs no-MDS (1.0±0.7 vs 0.7±0.4, p=0.011). Comparing results of MNDA MFC and standard MFC we also found higher MFI in dimMP (1.0±0.8 vs 0.7±0.3, p=0.039) in pts diagnosed MDS by MFC (n=63) vs those without signs of MDS (n=14). In the inexplicit cases diagnosed MDS possible by MFC (aberrant antigen expressions not sufficient for MDS diagnosis, n=51) higher percentages of dimG [16±18 vs 9±10, p=0.015 (A) and 3±3 vs 1±2, p=0.005 (B)] and dimM [16±25 vs 7±13, p=0.02 (B)] were seen as compared to no-MDS, in line with CM results. Moreover, a lower MFI in M [26±12 vs 31±11, p=0.024 (A) and 29±14 vs 36±13, p=0.02 (B)] and a higher MFI in dimMP (1.0±0.8 vs 0.9±0.6, p=0.021) could be detected. Considering CG, cases with an aberrant karyotype (n=41) had higher values for %dimM (27±23 vs 18±16, p=0.035) as compared to those with a normal karyotype (n=79). Including the most significant markers [%dimG>12 (A), %dimM>13 (B), %hiMP>15 (A), 1 point each], we created a new MNDA score with a score of ≥2 indicating MDS. Of 14 pts with a score of ≥2, 13 pts were concordantly diagnosed MDS using CM for validation; 1 pt had no MDS by CM but was classified MDS by standard MDS-MFC. Conclusions: Reduced MNDA levels and higher percentages of M and G with low MNDA expression as well as a higher percentage of MP with high MNDA expression could be confirmed in pts with MDS. Applying our newly defined MNDA score for MFC, identification of a subset of pts with MDS was possible at high specificity. Further analyses will have to evaluate this MNDA score incorporated into standard MDS-MFC panels to improve MFC-based diagnostic approaches for MDS. Disclosures Bellos: MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Davis:Trillium Diagnostics: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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