Screening Bone Marrow Samples for Abnormal ... - Wiley Online Library

Cytometry Part B (Clinical Cytometry) 88B:253–260 (2015)

Original Article

Screening Bone Marrow Samples for Abnormal Lymphoid Populations and Myelodysplasia-Related Features with One 10-Color 14-Antibody Screening Tube Amr Rajab and Anna Porwit* Flow Cytometry Laboratory, Department of Laboratory Hematology, Laboratory Medicine Program, University Health Network, Toronto General Hospital, Toronto, Ontario, Canada

Background: We have designed one-tube 14-antibody 10-color flow cytometry (FCM) panel that would provide maximum information on lymphoid and myeloid cell subsets in bone marrow aspirates (BMA) from patients with cytopenia(s). Samples and Methods: BMA from 8 normal donors, from 286 non-malignant hospital controls, 92 myelodysplastic syndromes (MDS), 47 myeloproliferative neoplasms (MPN), and from 14 MDS/MPN patients were investigated. One tube 14-monoclonal antibody (MAb) 10-fluorochrome panel included: kappa1CD4 FITC, Lambda1CD8 PE, CD3 1 CD14 ECD, CD34 APC, CD201CD56 PC7, CD10 APC-A750, CD19 APC-A700, CD33 PC5.5, CD5 PB, and CD45 KO. Kappa/lambda expression was evaluated separately in CD191, CD101 and CD51 B-cells. CD41CD31, CD81CD31, CD51CD31 T-lymphocyte subsets were enumerated. Blasts were evaluated using CD45/SSC and CD34 gating. The FCM score for MDS (sc. Ogata score) included CD341 myeloblast and B-progenitor cluster size, myeloblast/lymphocyte CD45 expression, and granulocyte/lymphocyte SSC ratio. Results: Abnormal lymphoid populations or increased plasma cells were found in 18 patients (4%). A 43/92 BMA from MDS and 7/14 from MDS/MPN patients had score >2. Score >2 had 92.5% positive predictive value for MDS/MDS-MPN diagnosis. Negative predictive value for MDS/MDS-MPN was 83% for scores under 3 and 88% for scores under 2. All but two of normal/hospital control samples had FCM score 2 are highly indicative of MDS or MDS-MPN. C 2015 International Clinical Cytometry Society V

Key terms: flow cytometry; bone marrow; lymphoma; myelodysplastic syndrome

How to cite this article: Rajab, A. and Porwit, A. Screening Bone Marrow Samples for Abnormal Lymphoid Populations and Myelodysplasia-Related Features with One 10-Color 14-Antibody Screening Tube. Cytometry Part B 2015; 88B: 253–260.

Currently, clinical laboratories face increasing demand for flow cytometry (FCM) services and limited budget. Therefore, we have searched for a screening panel that would provide maximum immunophenotyping information on both lymphoid and myeloid cell subsets in bone marrow aspirates (BMA) and meet economic constraints. Significant numbers of BMA referred to the Flow Cytometry Laboratory, University Health Network (UHN), Toronto, ON, are from patients with unexplained cytopenia(s). Many of these samples are accompanied by insufficient clinical information, lack provisional diagnosis, and provided smears are not adequate. The majority of these samples will not show evidence for lymphoproliferative disorder or

C 2015 International Clinical Cytometry Society V

acute leukemia but many patients have cytopenia (s) and a query of myelodysplastic syndrome (MDS) is raised. The choice of the antigens during the development of the screening panel followed published international Correspondence to: Anna Porwit, MD, PhD, Professor, Department of Pathobiology and Laboratory Medicine, University Health Network, Toronto General Hospital, 200 Elizabeth Street, 11th Floor, R415, Toronto, ON, M5G 2C4, Canada. E-mail: [email protected] Received 10 August 2014; Revised 8 January 2015; Accepted 30 January 2015 Published online 30 April 2015 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/cyto.b.21233

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Table 1 Diagnoses and MDS-score Distribution in 440 BMA Evaluated with the Screening Panel FCM-score

Normal; n 5 8 Hospital controlsa; N 5 207 MDS; n 5 92 MDS-MPN; n 5 14 MPN; n 5 47 B-cell or plasma cell neoplasm; n 5 18 Post treatment for other malignancy; n 5 33 Post BM transplant; n 5 21

FCM-score 2

FCM-score >2

0

1

2

3

4

Positive cases

5 105 7 2 13 8

3 80 19 4 18 7

0 20 23 1 9 3

0 2 31 5 7 0

0 0 12 2 0 0

0(0%) 2 (1%) 43 (47%) 7 (50%) 7(15%) 0 (0%)

14

14

4

1

0

4

10

6

1

0

Sensitivity

Specificity 100% 99%

Positive cases

Sensitivity

Specificity

100%

0 (0%) 22 (14%) 66 (72%) 8 (57%) 16 (34%) 3(17%)

1 (3%)

97%

5(15%)

85%

1 (5%)

95%

7 (33%)

67%

47% 50% 15%

100% 89% 72% 57% 34% 83%

a Hospital controls (HC): Patients with cytopenia(s) with no evidence of underlying malignancy, BM samples with reactive inflammatory changes or lymphoma staging specimens without lymphoma involvement.

guidelines to allow detection of aberrant lymphoid populations and to provide orientation in the myeloid compartment of the bone marrow (BM) (1–5). At first, the screening tube was validated to detect lymphoid malignancies according to the Ontario Laboratory Accreditation requirements. Validation was done using 32 patient samples, which were analyzed by both the screening tube and 10-color Lymphoma/Leukemia panels. We have also evaluated the main subpopulations of granulopoietic cells, monocytes and blasts, including enumeration of CD341 cells. After successful validation, the screening tube has been applied in routine diagnostics, mainly for BMA from patients with cytopenia(s) and for staging BMA in patients with known CD51 or CD101 B-cell lymphoma diagnosis. After the panel had been used in clinical practice for 1 year, we performed a retrospective study to establish its value in screening for MDS - related features. Our panel makes it possible to determine all elements of the previously reported FCM MDS score, the so called Ogata score (6,7). The Ogata score includes CD341 myeloblast and B-progenitor cluster size, myeloblast/lymphocyte CD45 expression, and granulocyte/lymphocyte side scatter (SSC) ratio (6,7). This score has been validated in an international study and has been reported to be of prognostic significance in MDS patients (7,8). It has been recommended to be used for screening purposes by the International/European Leukemia Net Working Group for Flow Cytometry in MDS (9) and confirmed as useful in clinical practice (10). MATERIALS AND METHODS Samples During 12 months, 741 BMA were investigated using the screening panel. In 479 cases, full morphology, cytogenetics, basic clinical information and CBC data could be retrieved from the pathology reports (patient charts were not reviewed). The MDS scores were not reported prospectively, thus, the scores were not taken into consideration in the diagnostic process. Retrospectively analyzed MDS scores were correlated with final diagnoses and cytogenetic data available in the pathology

reports. The final diagnosis was not available in the pathology reports of 39 patients due to insufficient material or insufficient clinical data. These cases were excluded from further analysis. Thus, the final analysis included 440 patients (Table 1). Diagnosis of MDS (N 5 92), myeloproliferative neoplasm (MPN, N 5 47) and MDS/MPN (N 5 14) was based on integrated morphological evaluation, clinical data and karyotype analysis, and followed the WHO 2008 classification (11). Control Samples from Patients with No Hematological Malignancy Included i. Eight BMA from normal donors screened before BM transplant. ii. Two hundred and seven BMA from so called hospital controls (HC), i.e., patients with cytopenia(s) and no evidence of underlying malignancy, BM samples with reactive inflammatory changes, or lymphoma staging specimens without lymphoma involvement. iii. Thirty-three BMA from patients previously treated for non-hematological malignancy with no morphological or cytogenetic evidence for therapy-related MDS. iv. Twenty-one BMA acquired in the course of follow-up post BM transplant. Methods BMA were filtered and washed twice using warm PBS (2 3 5 min, 450 g). About 100 ll of the washed sample were incubated with MAb cocktail (Table 2) for 15 min in the dark at room temperature. Following the incubation, samples were lysed using VersaLyse [Beckman Coulter (BC), Miami, FL], washed and suspended in IOTest 3 Fixative (BC) and PBS. A minimum of 50 3 103 events were acquired on the NaviosTM Flow cytometer (BC). All antibodies were titrated, using signal-to-background ratio (12) to determine optimal signal-to-noise separation and minimize background fluorescence. Antibody cocktail was prepared for 50 runs. Initially, the cocktail was compared to individually added MAb to make sure antibodies do not cross-react. In addition, the cocktail stability was verified

Cytometry Part B: Clinical Cytometry

10-COLOR 14-ANTIBODY BONE MARROW SCREENING TUBE

Table 2 Antibodiesa used in the 14 MAb 10-Color Screening Panel Fluorescence FITC PE ECD PC5.5 PC7 APC A700 A750 PB KO a

Ab

Clone

Titre (ml)

CD4 Kappa CD8 Lambda CD3 CD14 CD33 CD20 CD56 CD34 CD19 CD10 CD5 CD45

13B8.2 Polyclonal B9.11 Polyclonal UCHT1 RMO52 D3HL60.251 B9E9 N901 581 J3-119 ALB1 BL1a J.33

10 10 10 10 5 3 3 5 10 5 3 5 5 5

All antibodies from Beckman Coulter, Miami, FL, USA.

over a period of 2 weeks by comparing it to individually added MAb. This was done by statistically comparing the percentages and MFI on positive populations using control non-malignant BMA samples stained with the screening tube cocktail vs. individually added MAb. Instrument scatter settings were optimized using a whole blood sample lysed with VersaLyse (BC). The recently published International Clinical Cytometry Society guidelines for validation of FCM assays were followed (12,13). Instrument PMTs, excluding FL10, were optimized using whole blood stained CD4. The marker CD4 was chosen since the pattern of CD4 in a whole blood sample includes a bright positive population (T-helper cells), a dim positive population (monocytes) and negative populations (granulocytes, B cells, and T suppressor cells). FL10 was optimized using whole blood stained with CD45 KO. FL10 voltage was adjusted to place the lymphocyte population at the end of the third log. Following the PMT optimization, target channels were computed using FlowSet Pro (BC) and calculated by acquiring twenty runs over 10 days. The mean and acceptable ranges for each channel were calculated. The compensation matrix was calculated using whole blood, which was stained with single CD45 antibodies for each channel. Subsequently, the compensation for the screening tube was adjusted using a normal BMA stained with the whole panel. This was possible since BMA always contain both positive and negative populations with all applied antibodies. Instrument alignments and fluidics were checked daily using Flow Check Pro (BC), while Flow Set Pro (BC) was used to monitor instrument performance. Normal samples ran during each day’s routine work allowed to confirm the validity of compensation settings. Instrument setup, compensation, quality control and validation process have been described in detail in the ICCS enewsletter 2014, vol.5 no.2 (http://www.cytometry.org/ public/newsletters/eICCS- 5-2/article2.php). FCM data analysis Analysis was performed using Kaluza software (BC). Primary analysis (reported prospectively) focused on


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evaluation of lymphoid subsets and also provided orientation in the numbers of CD341 cells and myelomonocytic compartment (CD331CD101, CD331CD102, CD141) (illustrated in Fig. 1). Non-viable cells (called Debris, plot A) are excluded from analysis using fastidious forward (FSC) vs.SSC gating. All consequent dot plots are created using a Boolean gate called “Living cells” (=NOT Debris), which excludes non-viable cells. Major BM cell subpopulations are mapped on CD45/SSC plot (B). CD341 cells are enumerated (C) and myeloid and lymphoid CD341 subsets are gated on CD19/CD33 plot (D). In addition, CD5, CD14 and CD3 expression on CD341 cells is investigated (E). Similarly the CD45- and the dim CD451 populations are investigated using dot plots CD19 vs.CD33 and CD3/CD14 vs.CD5 (not shown). B-cells are gated on CD19/SSC plot (F). Kappa and Lambda expression is evaluated within the total B-cell population (G). A dot plot of CD19 vs.CD5 of the lymphoid region is used to detect CD19/ CD5 dual positive population and to enumerate T-cell using CD51/CD192 population (H). B-cell maturation pattern is evaluated using CD20 vs.CD10 expression (I). If significant populations of B-cells positive for CD5 or CD10 were found, kappa and lambda expression is also evaluated in these B-cell subsets. In normal BMA, plasma cells are located in the CD191CD20-CD10- quadrant. If there are >2% of cells in this quadrant, the myeloma panel is added (6) to investigate cytoplasmic kappa and lambda expression in plasma cells. CD41 and CD81 Tlymphocyte subsets are enumerated after gating of CD31 T-cells on SSC/CD31CD14ECD plot (J, K). CD3 and CD5 are investigated on T-cell population using CD5 vs.CD3/ CD14 of the gated lymphoid population (L). CD141 monocytes are also enumerated (J). CD561 NK cells are enumerated using CD3 v. CD201CD56 plot after B-cells are removed from analysis using Boolean gating strategy [i.e., Lymphs AND (NOT CD191)] (M). Maturation of granulopoietic and monocytic cells is studied using plots CD33 vs.CD14 and CD33 vs.CD10 (N,O). CD10 expression on neutrophils could be further evaluated on SSC/ CD10 plot (P). Analysis of the Ogata score was performed retrospectively. Elements and analysis of the score are illustrated in Figure 2 (normal findings) and Figure 3 (MDS-related features). This score includes CD341 myeloblast and B-progenitor cluster size (defined by CD45 and side scatter characteristics on CD341 cells) (Figs. 2B and 2C), lymphocyte/myeloblast CD45 expression (MFI) ratio (Figs. 2E and 2F), and granulocyte/lymphocyte side scatter mode ratio (Fig. 2D). One score point is given for each of the following features: i. Gated CD341 myeloblasts are 2% of all nucleated cells, ii. B-cell progenitors are 5% of CD341 cells, iii. lymphocyte to myeloblast CD45 MFI ratio is 4 or 7.5, iv. granulocyte to lymphocyte SSC mode ratio is 6. Thus, FCM score can range between 0 and 4. Figures 2A–2F illustrate normal values resulting in score 0. Figures 3A–3F shows example of BMA with score 4 found in a patient investigated with query MDS.

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FIG. 1. Non-viable cells are excluded from the analysis using fastidious forward (FSC) vs.ide scatter (SSC) gating (A). All consequent dot plots are created of Boolean gate (Living cells), which excludes debris. Various cell subpopulations are mapped on CD45/Side scatter (SSC) plot (B). CD341 cells are enumerated (C) and myeloid and lymphoid CD34 subsets are gated on CD19/CD33 plot (D). In addition, the expression of CD5, CD14, and CD3 on CD341 cells are investigated (E). Similarly the CD45- and the dim CD451 populations are investigated using dot plots CD19 vs.CD33 and CD3/CD14 vs.CD5 (not shown). B-cells are gated on CD19/SSC plot (F). Kappa and Lambda expression is evaluated within the total B-cell population (G). A dot plot of CD19 vs.CD5 of the lymphoid region is used to detect dual positive populations and to enumerate T-cell using CD5 (H). B-cell maturation pattern is evaluated using CD20 vs.CD10 expression (I). In normal BMA, plasma cells are located in the CD191CD202CD10- quadrant. CD41 and CD81 T-lymphocyte subsets are enumerated after gating of CD31 T-cells on SSC/CD31CD14ECD plot (J, K). CD3 and CD5 expression is investigated on T-cell population using CD5 vs.CD3/CD14 of the gated lymphoid population (L). CD141 monocytes are also enumerated (J). CD561 NK cells are enumerated using CD3 v. CD201CD56 plot after B-cells are removed from analysis using Boolean gating strategy (M). Maturation of granulopoietic and monocytic cells is studied using CD33 vs.CD14 and CD33 vs.CD10 expression (N,O). Expression of CD10 in granulocytes can be evaluated on SSC/CD10 plot (P). [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Statistical Analysis The diagnostic power to detect myelodysplasia of the cytometric scores >2 and 2 was estimated by calculating the specificity, sensitivity, positive predictive value [PPV5 no. of true positives/(no. of true positives 1 no. of false positives)], and negative predictive value

[NPV 5 defined as the no. of true negatives/(no. of true negatives 1 no. of false negatives)]. In calculation of PPV, MDS and MDS/MPN samples with scores >2 and 2 were considered as true positive and non-malignant samples with respective scores as false positive. In calculation of NPV, non-malignant samples with scores 2 are mainly seen in patients with MDS, MPN and/or MDS/MPN and that scores 3 are very rarely seen in patients with no myeloid malignancy. There was no significant correlation between the cytogenetics and MDS score in patients with myeloid malignancy, which stresses the added value of FCM score in diagnostics of myelodysplasia. All normal bone marrow samples and a great majority of hospital control patients showed scores 0 or 1. The most common parameter rendering score 1 in HC patients was low fraction of CD341 B-cell precursors, which suggests limited value of this finding if not supported by other elements of the score. Score 2 has been found in a 33/440 (7.5%) patients with cytopenia and no evidence for MDS, MDS/MPN or MPN. Two parameters, which were more often seen in patients with myelodysplasia in comparison to controls, were increased fraction of CD341 precursors and abnormal granulocyte to lymphocyte SSC mode ratio. Thus, in patients with these abnormal findings, additional immunophenotyping with a

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more comprehensive panel aimed at MDS-related immunophenotypic changes should be considered to search for further confirmation of myelodysplasia (29). Moreover, as previously reported by several authors [rev. in (30)], the lack of immunophenotypic changes does not preclude MDS diagnosis, which should be based on integrated information from clinical, morphological, immunophenotype, and cytogenetic data. ACKNOWLEDGMENTS Morphological assessment of bone marrow samples by Hematopathology Staff (Dr. David Barth, Dr. Hong Chang, Dr. Jan Delabie, Dr. Afaf Erfaei, Dr. Elizabeth Hyjek, Dr. Rumina Musani, Dr. Anne Tierens, Dr. Emina Torlakovic, Dr. Brian Sheridan) and processing flow cytometry samples by Flow cytometry laboratory staff (Jennifer Leung, Jessie Leung, Jordan Ngo, Josello Mandawe, May Ly, Liz Valenzuela, and Sajid Dewji) is gratefully acknowledged. Cytogenetic analyses were performed at the Cytogenetics laboratory, Laboratory Medicine Program, University Health Network, Toronto and interpreted by Dr. Ken Craddock. LITERATURE CITED 1. Davis BH, Holden JT, Bene MC, Borowitz MJ, Braylan RC, Cornfield D, Gorczyca W, Lee R, Maiese R, Orfao A, et al. 2006 Bethesda international consensus recommendations on the flow cytometric immunophenotypic analysis of hematolymphoid neoplasia: Medical indications. Cytom B Clin Cytom 2007;72:S5–S13. 2. Wood BL, Arroz M, Barnett D, DiGiuseppe J, Greig B, Kussick SJ, Oldaker T, Shenkin M, Stone E, Wallace P. 2006 Bethesda international consensus recommendations on the immunophenotypic analysis of hematolymphoid neoplasia by flow cytometry: Optimal reagents and reporting for the flow cytometric diagnosis of hematopoietic neoplasia. Cytom B Clin Cytom 2007;72:S14–S22. 3. Bene MC, Nebe T, Bettelheim P, Buldini B, Bumbea H, Kern W, Lacombe F, Lemez P, Marinov I, Matutes E, et al. Immunophenotyping of acute leukemia and lymphoproliferative disorders: A consensus proposal of the European LeukemiaNet work package 10. Leukemia 2011;25:567–574. 4. Craig FE, Foon KA. Flow cytometric immunophenotyping for hematologic neoplasms. Blood 2008;111:3941–3967. 5. Johansson U, Bloxham D, Couzens S, Jesson J, Morilla R, Erber W, Macey M. Guidelines on the use of multicolour flow cytometry in the diagnosis of haematological neoplasms. British committee for standards in haematology. Br J Haematol 2014;165:455–488. 6. Ogata K, Kishikawa Y, Satoh C, Tamura H, Dan K, Hayashi A. Diagnostic application of flow cytometric characteristics of CD341 cells in low-grade myelodysplastic syndromes. Blood 2006;108:1037–1044. 7. Della Porta MG, Picone C, Pascutto C, Malcovati L, Tamura H, Handa H, Czader M, Freeman S, Vyas P, Porwit A, 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;97:1209–1217. 8. Della Porta MG, Picone C, Tenore A, Yokose N, Malcovati L, Cazzola M, Ogata K. Prognostic significance of reproducible immunophenotypic markers of marrow dysplasia. Haematologica 2014;99:e8–e10. 9. Porwit A, van de Loosdrecht AA, Bettelheim P, Brodersen LE, Burbury K, Cremers E, Della Porta MG, Ireland R, Johansson U, Matarraz S, et al. Revisiting guidelines for integration of flow cytometry results in the WHO classification of myelodysplastic syndromes-proposal from the international/European LeukemiaNet working group for flow cytometry in MDS. Leukemia 2014;28: 1793–1798. 10. Heron M, Dovern E, Bakker-Jonges LE, Posthuma EF, Brouwer RE, Smedts F, Batstra MR. Translating the MDS flow cytometric score into clinical practice. Cytom B Clin Cytom 2014. 11. Swerdlow SH, Campo E, Harris NL, Jaffe ES , Pileri SA, Stein H, Thiele J, Vardiman J.WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues, 4th ed. Lyon: IARC; 2008.

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