6 Markers/5 Colors Extended White Blood Cell Differential by Flow Cytometry

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1 Original Article 6 Markers/5 Colors Extended White Blood Cell Differential by Flow Cytometry Jean-Luc Faucher, 1 Charlotte Lacronique-Gazaille, 1 Elise Frebet, 1 Franck Trimoreau, 1 Magali Donnard, 1 Dominique Bordessoule, 2 Francis Lacombe, 3 Jean Feuillard 1 * 1 Laboratoire d Hematologie, H^opital Dupuytren, Limoges, France 2 Service d Hematologie Clinique, H^opital Dupuytren, Limoges, France 3 Laboratoire d Hematologie, H^opital Haut Lev^eque, Bordeaux, France Received 18 March 2007; Revision Received 7 June 2007; Accepted 17 July 2007 This article contains supplementary material available via the Internet at jpages/ /suppmat. Grant sponsors: Cancerop^ole Grand-Sud- Ouest, P^ole de Competitivite Cancer-Bio- Sante, Ligue Nationale contre le Cancer, Conseil Regional du Limousin. *Correspondence to: Jean Feuillard, Laboratoire d Hematologie and UMR CNRS 6101, CHU Dupuytren, 2 Avenue Martin Luther King, Limoges Cedex, France. jean.feuillard@chu-limoges.fr Published online 18 September 2007 in Wiley InterScience ( wiley.com) DOI: /cyto.a International Society for Analytical Cytology Abstract Electronic white blood cell (WBC) differential by standard cytology (hematology analyzer and visual inspection of blood smears) is limited to five types and identification of abnormal cells is only qualitative, often problematic, poorly reproducible, and labour costing. We present our results on WBC differential by flow cytometry (FCM) with a 6 markers, 5 colors CD36-FITC/CD2-PE1CRTH2-PE/CD19-ECD/CD16-Cy5/CD45-Cy7 combination, on 379 subjects, with detection of 12 different circulating cell types, among them 11 were quantified. Detection of quantitative abnormalities of whole leucocytes, neutrophils, eosinophils, basophils, monocytes, or lymphocytes was comparable by FCM and by standard cytology in terms of sensitivity and specificity. FCM was better than standard cytology in detection and quantification of circulating blast cells or immature granulocytes, with a first lineage orientation in the former case. All cases of lymphocytosis, with lineage assignment, were detected by FCM. FCM identified a group of patients with excess of CD16pos monocytes as those having an inflammatory syndrome. WBC differential by FCM is at least as reliable as by standard cytology. FCM superiority consists in identification and systematic quantification of parameters that cannot be assessed by standard cytology such as lineage orientation of blast cells or lymphocytes, and expression of markers of interest such as CD16 on inflammatory monocytes. ' 2007 International Society for Analytical Cytology Key terms white blood cell differential; flow cytometry; screening for hematological malignancies SCREENING for hematological disorders is routinely performed by counting circulating cells with hematology analyzers. But identification of circulating white blood cells (WBCs) by electronic counters is limited to only five cell-types: lymphocytes, monocytes, neutrophils, eosinophils, and basophils. Moreover, although most cell hematology analyzers are very good in detection of quantitative abnormalities, qualitative recognition of abnormal WBCs is poor, and microscopic examination of blood smears is needed for most cases to ascertain the presence of abnormal circulating cells. Therefore, both electronic WBC count and microscopic inspection of blood smears are needed to establish a reliable WBC differential. This traditional scheme, referred to as traditional or standard cytology, was set up in the 70s. Standard cytology is based on the expertise of cytologists and technicians, which is noticeably variable. Blood smear reviewing is time consuming and difficult to standardize. A recent study shows that, in a median institution among 263 hospitals and independent laboratories, manual review of peripheral blood smears were performed on 26.7% of specimens. The authors raised clearly the question of how to reduce the rate of manual peripheral blood smear review and to improve the efficiency of generating blood cell count results (1). In our institutions (JF, FL), <5% of reviewed blood smears will lead to further investigations. Last but not least, detection of hematological disorders by standard cytology very often leads to an immunophenotypic characterization of abnormal cells by flow cytometry (FCM) in Cytometry Part A 71A: , 2007

2 Table 1. Distribution of pathological groups (one patient may belong to several groups) PATHOLOGICAL GROUPS NUMBER OF PATIENTS PATIENTS WITH A HEMATOLOGICAL MALIGNANCY NUMBER OF PATIENTS Emergency/intensive care 41 B-cell acute lymphoblastic leukemia 1 Cancer 35 T-cell acute lymphoblastic leukemia 2 Infection 42 Acute myeloblastic leukaemia (M1, M2, M4, M5) 18 Surgery 43 Promyelocytic leukemia 1 Heart/Lung 32 Myelodysplastic or myeloproliferative syndrome 8 Digestive 19 Aplasia 5 Hematology 117 Chronic lymphocytic leukemia 23 Internal Medicine 18 Non-Hodgkin lymphoma with leukemic phase 2 External Consulting 41 Non-Hodgkin lymphoma without leukemic phase 22 Others 41 Myeloma 10 Other 8 order to quickly confirm the cytological abnormalities and to get a first diagnostic hypothesis as close as possible to the final diagnostic conclusion. One question is whether it is possible to propose a WBCdifferentialbyFCM(2).Theoreticaladvantagesofa WBCdifferentialbasedonanimmunologicalrecognitionof cells by FCM would be (i) to increase specificity of cell recognition without decreasing sensitivity, (ii) to enhance the hematological information, identifying cell types that are beyond the possibilities of cytology such as B-cells or T-cells and (iii) to render the process of cell recognition independent of the manufacturer, with the view to elaborate a universal strategy of automatic cell recognition and counting. In fact, flow cytometers are already used as cell counters in two well-defined cases: CD341 cell and CD41 lymphocyte count (3 5). It is also of note that a recent publication describes an automated method for quantifying peripheral blood lymphocyte subsets and diagnosis screening of leukemic phases of B-cell disorders (6). These cases correspond to niches that are inaccessible to standard cytology. These examples also demonstrate that any current 4 6 colors flow cytometer can be used as a cell counter, with well defined procedures, calibration methods, internal controls, and with external independent quality controls. Some attempts have already been done on quantification of circulating monocytes (7,8), basophils (9), or granulocytes (10). FCM enumeration of circulating monocytes tend to be the reference (11).However,toourknowledge,neitherasinglecombination of antibodies nor a FCM strategy has been proposed to replace the hematology analyzer. To enumerate the five circulating blood cell types plus blast cells with presumed lineage identification plus immature granulocytes, plus B-cells, plus T-cells, plus cytotoxic T/NKcells, plus inflammatory monocytes by FCM, we have defined a 6 antibodies/5 colors combination, referred to as 5 colors single tube. We present our results on a comparative study of WBC differential between standard cytology and FCM with this single 5 colors tube. These results are discussed with a view to the future of being able to have a fully automated, extended FCM WBC differential as the first step in the evaluation of blood cell disorders. MATERIALS AND METHODS Patients and Cytological Analysis Three hundred and seventy-nine blood samples were collected on EDTA tubes and were analysed between September 2005 and March 2006, corresponding to 39 adult control volunteers (mean age , sex ratio m/f 5 1) and 340 patients (mean age , sex ratio m/f 5 1.3), with their informed consent for additional studies of their remaining blood samples obtained in the normal course of the care of their disease. Distribution of patients in the different pathological groups is given in Table 1. Furthermore, 4 normal bone marrow samples were analyzed. Electronic complete blood count was performed with an Advia 120 TM hematology analyzer (Bayer). At least two blood smears were performed for each sample. After May Grunwald Giemsa staining, percentage of each cell subtype was calculated as the mean of two independent a-isothyocyanate counting of 200 cells under microscope. Flow Cytometry and Antibodies Antibodies used in this study were fluoresceine a-isothyocyanate (FITC) conjugated CD36 monoclonal antibody (mab) (CD36-FITC, clone FA6.152, ref IM 0766), phycoerythrin (PE) conjugated CD2 mab (CD2-PE, clone 39C1.5, ref A07744), PE conjugated CRTH2 mab (CRTH2-PE, clone BM16, ref A07413), PE-Texas Red (PE-TR, so-called ECD) conjugated CD19 mab (CD19-ECD, clone J4.19, ref A07770), PE-cyanine 5 (Cy5) conjugated CD16 mab (CD16-Cy5, clone 3G8, ref A07767) and PE-cyanine 7 (Cy7) conjugated CD45 mab (CD45-Cy7, clone J.3, ref IM 3548), from Beckman Coulter (Miami, Florida). The 5 colors single tube combination used for extended WBC differential by FCM was CD36- FITC/CD2-PE1CRTH2-PE/CD19-ECD/CD16-Cy5/aCD45-Cy7. Direct immunolabellings were performed on 50 ll whole peripheral blood. After 20 min incubation, red blood cells were lysed with Versalyse TM enzymatic reagent (Beckman Coulter, Villepinte, France) following instructions of the manufacturer, without washing and without fixative. Beads (flow-count fluorosphere, Beckman Coulter) were added to each tube to allow an absolute count of each cell type. The analyzer was a 5 colors Cytometry Part A 71A: ,

3 Figure 1. Gating strategy to enumerate 1 circulating blood cell types. Panel 1: Selection of CD45pos WBCs (gate A). Panel 2: enumeration of neutrophils and selection of CD16pos/SSClow (gate B), CD16neg/SSClow (gate C), and CD16neg/SSChigh cells (gate D). Panel 3: from the gate C, selection of CD2pos or CRTH2pos (gate E) and CD2neg/CRTH2neg (gate F) cells. Panel 4: from the gate F, selection of CD19neg (gate G) and CD19pos cells (gate H). Panel 5: from the gate E, enumeration of basophils and non cytotoxic T-lymphocytes. Panel 6 and 7: from the gate G, enumeration of monocytes and CD19neg CD2neg cells (myeloid precursors?). Panel 8: from the gate H, enumeration of B- cell precursors and mature B-cells. Panel 9: from gate B, enumeration of CD2pos/CD16pos cytotoxic lymphocytes and CD16pos monocytes. Panel 10: from gate D, enumeration of immature granulocytes and selection of CD45high/SSChigh cells (Gate I): Panel 11: from gate I, enumeration CRTH2pos/SSChigh eosinophils. Panel 1, 7, and 8 are from a normal bone marrow sample. Panel 2, 3, 4, 5, 6, 9, 10, and 11 are from a normal blood sample. The logical successive gatings are indicated on the top of each graph. FC500 flow cytometer from Beckman Coulter. Spectral compensation was performed using an automatic calibration technique (Advanced Digital Compensation from Beckman Coulter) following the protocol of the supplier. Analysis and absolute cell count were performed after acquiring at least 50,000 events. Before each series of acquisition, settings of photomultipliers were checked with fluorescence beads for calibration (flow-set fluorospheres; Beckman Coulter) according to the manufacturer s recommendation for correction of variations in the laser power. Gating Strategy A preliminary step consisted in elimination of cellular debris on the SSC/FSC scattergram (not shown). The gating strategy was based on two different gates: orientating gates and specific gates (Fig. 1). Orientating gates allowed to progressively pre-select cell types of interest. Specific gates correspond to presumed targeted cell types. A color code was assigned to each specific gate (each presumed cell type) to facilitate the reading of FCM scattergrams (Table 3). The first orientating gate was defined on the CD45/SSC scattergram, targeting the WBCs (Fig. 1, panel 1, gate A). The 2nd scattergram, SSC/CD16 (Fig. 1, panel 2), allowed to define one specific gate for neutrophils (color code red, SSChigh, CD16pos), and three orientating gates: CD16 pos/ssc low (gate B), CD16neg/SSClow or int (gate C) and CD16neg/ SSChigh (gate D). The 3rd scattergram, CD45/CD21CRTH2, was gated on A and C (Fig. 1, panel 3): two orientating gates were defined, one for CD2pos or CRTH2pos events (gate E), and one for CD2neg and CRTH2neg events (gate F). The 4th scattergram, CD36/CD19, was gated on A and C and F; we drew one orientating gate for the CD19neg/CD36pos (gate G) and one orientating gate for the CD19pos/CD36neg (gate H) 936 Improved WBC Differential by FCM

4 MARKER Table 2. Cellular expression profile of the markers used CD36 CD2 CRTH2 CD19 CD16 CD45 CELLULAR EXPRESSION Monocytes, erythrocytes, platelets T-blasts, CD3pos T-lymphocytes, NK cells Activated T-cells, Eosinophils, Basophils B-blasts, B-lymphocytes Cytotoxic T/NK cells, neutrophils, inflammatory monocytes White blood cells (Fig. 1, panel 4). A CD45/SSC scattergramm was gated on A, C, and E, corresponding to CD2pos or CRTH2pos events (Fig. 1 panel 5); two specific gates were drawn, one for basophils (color code: black) and one for the noncytotoxic T-lymphocytes (color code: dark pink). From the CD19neg orientating gate G, two specific gates were drawn, one for monocytes (color code green) on the 6th scattergram, CD45/CD36 (Fig. 1, panel 6), and one for presumed myeloid precursors (CD19neg, CD2neg and CRTH2neg, color code light pink) on the 7th scattergram, CD45/SSC, (Fig. 1, panel 7). From the CD19pos orientating gate H, two specific gates were drawn on the 8th scattergram, CD45/SSC (Fig. 1, panel 8), one for B- lymphocytes (blue) and one for B-cell precursors (turquoise blue). The 9th scattergram, CD36/CD21CRTH2, was gated on CD16pos/SSClow cells (gate B, Fig. 1, panel 9); two specific gates were drawn, one for cytotoxic CD16pos lymphocytes (yellow) and one for activated CD16pos, CD36pos monocytes (emerald). The SSChigh/CD16neg gate D of the 3rd scattergram allowed to draw the specific gate for immature granulocytes (purple) and one orientating gate (Gate I) that targets eosinophils (Fig. 1, panel 10). The gate for eosinophils (orange) was defined on a CD21CRTH2/SSC scattergram (Fig. 1, panel 11). Statistical Analysis FCM results were collected by two of us (JLF and CLG). The data was first fed to a dedicated database system for PC and then were exported to an Excel TM table before final statistical analysis. Standard deviations, v 2 test, t-test, and Pearson correlation coefficient were calculated using the pre-programmed commands of the Excel TM software. Percentiles, sensitivities, and specificities were calculated following standard statistical methods (12) using the Excel TM sofware. Normal values of each FCM cell type were defined by the 5th and the 95th percentiles for mature cells. ROC (Receiver Operating Characteristics) curves were used to define normal values for blast cells and immature granulocytes by FCM (13). Strength of the link between FCM and cytology enumeration of WBC was estimated by the area under the ROC curve and by the Pearson correlation coefficient (14). RESULTS The Gating Strategy to Detect 12 Cell Types in the Blood To detect 12 different circulating WBC types with one 5 colors single tube, we used the CD36-FITC/CD2- PE1CRTH2-PE/CD19-ECD/CD16-Cy5/CD45-Cy7 combination. The CD45 marker was expressed on all WBC types with high expression levels (CD45high) on mature cells and low expression levels (CD45low) on immature cells, and being negative on red blood cells (15 17). Characteristics of the other markers are summarized in Table 2. These markers were chosen because they are differently expressed on various cell types, each of them with different scattergram (SSC) characteristics and/or CD45 expression levels (Table 3), allowing to establish progressive gating strategies. CD36 and CD19 were chosen to target monocytes and B-lymphocyte lineage respectively. Among granulocytes, CRTH2 marker is expressed by eosinophils and basophils. CD16 is expressed on neutrophils, cytotoxic lymphocytes, and so called inflammatory monocytes. CD2 rather than CD3 was chosen because CD2 is expressed on T and most NK cells, allowing to quantify both non cytotoxic CD2pos/CD16neg T-lymphocytes and the CD2pos/CD16pos cytotoxic compartment. Moreover, the CD2 marker would allow to detect most cases of T-ALL since, even if not completely specific, membrane expression of CD2 Table 3. Presumed deduced cell types from the gating properties of each cell type studied GATING PROPERTIES PRESUMED CELL TYPE COLORS CODE COLORS SSClow, CD45high, CD16-, CD2 and CRTH2-, CD19pos B-lymphocytes Blue SSClow, CD45low, CD16-, CD2 and CRTH2-, CD19pos B-cell precursors Turquoise blue SSClow, CD45high, CD16neg, CD2pos or CRTH2pos Noncytotoxic T-lymphocytes Dark pink SSClow, CD45high, CD16pos, CD2pos or CRTH2pos Cytotoxic T/NK lymphocytes Yellow SSClow, CD45low, CD16neg, CD2pos or CRTH2pos T-cell precursors Grey SSClow, CD45low, CD19-, CD2neg and CRTH2neg Myeloid precursors Light pink SSChigh, CD45int, CD16neg, CD2neg and CRTH2neg Immature granulocytes Purple SSChigh, CD45high, CD16pos Neutrophils Red SSChigh, CD45high, CD16neg, CD2pos or CRTH2pos Eosinophils Orange SSCint, CD45int, CD16neg, CD2pos or CRTH2pos Basophils Black SSCint, CD16neg, CD2neg and CRTH2 neg, CD19neg, CD36pos CD16neg monocytes Green SSCint, CD16pos, CD2neg and CRTH2 neg, CD19neg, CD36pos CD16pos monocytes Emerald Cytometry Part A 71A: ,

5 Figure 2. Example of abnormal FCM WBC differential. The number of each panel, the different gates and the logical gatings are the same as those described in Figure 1. A: panels 1, 2, 3, 4 and 7 of a case of AML4. B: panels 1, 2, 3, 4, and 8 of a case of leukemic phase of a splenic lymphoma with villous lymphocytes. C: panel 1, 2, 5, 10, and 11 of a case of a stroke and recent iatrogenic infection. is found on blast cells of most T-ALL cases, whereas CD3 expression is only intracytoplasmic in most of these cases. The gating strategy was based on two different types of gates: orientating gates and specific gates (Fig. 1 and Table 3). Orientating gates allowed to progressively pre-select cell types of interest. Specific gates correspond to presumed targeted cell types. A color code was assigned to each specific gate (each presumed cell type) to facilitate the reading of FCM scattergrams (Table 3). The successive gatings through the different scattergrams are illustrated in Figure 1. Immature granulocytes and precursor cells were hardly detectable in normal blood. However, analysis of normal bone marrow and pathological samples showed that these cell types were easily identified with this gating strategy when they exist (Fig. 1, panels 1, 7 and 8 and Fig. 2A and 2C). Note that the color code permits to visualize the different cells types on the CD45/SSC scattergram (Fig. 1, panel 1), in agreement with the known CD45/ SSC characteristics of the cells (18,19). As shown in Figure 1, this strategy allowed to precisely enumerate different circulating cell sub-types. Only CD2 positive T-cell blasts were poorly discriminated. Nevertheless, T-cell precursors are completely absent from normal blood, and could be detected in case of T acute lymphoblastic leukaemia (see Supplemental Material). Three examples of abnormal FCM WBC differential are shown in Figure 2. The first case (Fig. 2A) corresponded to a blast alarm on the hematology analyzer. Concentration of circulating CD2 and CD19 negative blast cells, (myeloid?), was 0.57 G/L. FCM also evidenced an increase of monocyte count at 5.2 G/L, half of them being CD16 positive, as well as circulating immature granulocytes at 1.8 G/L. This case was further diagnosed as an acute myelomonocytic leukaemia (M4) according to the FAB classification. The second case (Fig. 2B) corresponded to an increase of circulating lymphocytes. FCM showed that these cells were mature CD19 positive B-lymphocytes at 50 G/L. This case was further diagnosed as a splenic lymphoma with villous lymphocytes. The third case (Fig. 2C) was a patient in the intensive care unit for a cerebrovascular accident 8 days before, with an alarm for immature granulocytes at the hematology analyzer the day of analysis. FCM results showed that immature circulating myelocytes were at 0.26 G/L, with a slight increase of CD2 and CD19 negative (myeloid?) precursors at G/L. A clear discrimination 938 Improved WBC Differential by FCM

6 have defined normal values and ranges for absolute count of each FCM type (Tables 5 and 6). Comparison of these values with those expected for standard cytology showed that FCM results were very close to those of standard cytology for normal subjects both for mean values and for the 5th and the 95th percentiles (Table 6). We then analysed the whole series of patients in a global manner. Correlation of leukocyte count was excellent between standard cytology and FCM for the whole series of samples, with a Pearson correlation coefficient of 0.97 (Fig. 3). Pearson correlation coefficients were of 0.90, 0.97, 0.36, 0.86, and 0.93, for neutrophils, eosinophils, basophils monocytes, and lymphocytes. For each of these five cell types, FCM thresholds were determined using ROC curves in order to define the best compromise between sensitivity and specificity for that would predict increased or decreased absolute counts if using standard cytology (Fig. 3 and Table 7), and to evaluate the strength of the link between cytology and cytometry by calculating the ROC curve area (13,14). FCM lower and upper thresholds defined by ROC curves were close to those corresponding to FCM 5th and the 95th percentiles of normal subjects and to normal ranges of standard cytology (Table 7). Specificity of FCM for detection of decreased or increased absolute cell count for standard cytological WBC types was always above 85%, and sensitivity above 80% except for basophils for which sensitivity was 6% (Table 7). Except for basophils, ROC curve areas were close to one, evidencing a very strong link between FCM and standard cytology. These results suggest that detection and counting of standard cytological WBC types by FCM with the 5 colors single tube combination is as reliable as standard cytology. Figure 3. Comparison of circulating WBC count between FCM and hematology analyzer. Upper panel: correlation between FCM (X-axis) and automaton (Y-axis). The number of leukocytes is in G/L. Values of the slope s, the Pearson correlation coefficient r and the Student t-test p are indicated within the graph. Middle and lower panels: ROC curves for detection of leucocytosis of leucopenia: the ROC curve area is indicated in each graph. and quantification of basophils and eosinophils was also possible, and did not evidence any quantitative abnormality for these cells. This result was then interpreted as reactive circulating immature granulocytes in the context of a iatrogenic infection. Comparison Between Standard Cytology and Flow Cytometry in Detection and Counting of Standard Cytological WBCs Criteria for recognition of the different cells were completely different between FCM and standard cytology, and the number of WBC cell types was significantly higher with FCM than with standard cytology. Therefore, to perform a comparison between both methodologies, we have established correspondences so that standard cytological types correspond to the sum of different FCM types (Table 4). In a first step, we Detection and Quantification of Circulating Immature Granulocytes and/or Blast Cells by Flow Cytometry, Compared with Standard Cytology FCM technique allowed detection and quantification of normal circulating precursors and immature granulocytes (Table 5). Mean and 95th percentile of circulating precursors by FCM were and G/L, close to those expected for normal ranges of circulating CD341 cells (Ref. 3 and our unpublished results). Mean and 95th percentile of circulating immature granulocytes by FCM were and 0.19 G/L respectively. Presence of blast cells was systematically assessed under the microscope and corresponded to at least 1% of blasts counted among 200 counted cells, meaning that at least two blast cells were recognized. Thus, in accordance with this very well-known limitation, we could not quantify normal levels of circulating precursors by standard cytology. Percentages of circulating immature granulocytes were also assessed by cytological examination of blood smears. Mean and 95th percentile of circulating immature granulocytes by cytology were and 0.01 G/L, respectively. But in fact, the cytological answer was also much closer to presence or absence answer than to genuine quantification, since 31/39 (80%) normal subjects had no detectable circulating immature granulocytes by cytology. Cytometry Part A 71A: ,

7 Table 4. Correspondences between cytological and FCM blood cell types CYTOLOGICAL TYPE FCM EQUIVALENT FCM COLORS CODE Lymphocytes Monocytes Neutrophils Eosinophils Basophils Immature granulocytes Blast cells Leucocytes B-lymphocytes 1 noncytotoxic T-lymphocytes 1 cytotoxic T/NK lymphocytes CD16neg monocytes 1 CD16pos monocytes CD16pos SSChigh neutrophils Eosinophils Basophils CD16neg SSChigh immature granulocytes B-cell precursors 1 T-cell precursors 1 Myeloid precursors Sum of all the FCM cell types Even though FCM and standard cytology thresholds were very different, shapes and surface areas of ROC curves showed that FCM detection and quantification of blasts and/or circulating immature granulocytes were tightly related to detection of these events by standard cytology (Fig. 4). An FCM threshold of G/L circulating blast cells would predict the detection of blasts by cytology with a sensitivity of 94% and a specificity of 60%. With this threshold, the apparent lack of specificity of FCM was due to the absence of detection of circulating blasts by cytology. The best compromise between sensitivity and specificity, when compared with cytology, would be an FCM threshold of G/L circulating blast cells that would predict the presence of circulating blast cells by cytology with a sensitivity of 82% and a specificity of 81%. The presence of blast cells in a blood sample was cytologically unequivocal for an FCM threshold of G/L. Regarding circulating immature granulocytes, the ROC curve threshold of 0.20 G/L (close to the 95th percentile of normal subjects) would predict the detection of these cells by standard cytology with a sensitivity of 89% and a specificity of 91%. These results clearly suggest that detection and counting of circulating blasts and/or immature granulocytes by FCM with the 5 colors single tube combination gave reliable results, with good specificity and sensitivity when compared with standard cytology. Table 5. Normal peripheral blood absolute counts in G/L of each FCM cell type CELL TYPE FCM TYPE MEAN SD 5TH PERCENTILE 95TH PERCENTILE Lymphocytes Granulocytes Monocytes Immature cells B-lymphocytes Non cytotoxic T-lymphocytes Cytotoxic T/NK lymphocytes Neutrophils Eosinophils Basophils CD16neg monocytes CD16pos monocytes Immature granulocytes Myeloid precursors B-cell precursors NA NA T-cell precursors 0 <10 24 NA NA Total circulating precursors NA: Not applicable. 940 Improved WBC Differential by FCM

8 Table 6. Comparison of normal counts and normal ranges in G/L between FCM and standard cytology for the 5 standard WBC types COLORS CODE FCM TYPES STANDARD CYTOLOGICAL CELL TYPES MEAN SD FCM 5TH PERCENTILE FCM 95TH PERCENTILE EXPECTED COUNT EXPECTED RANGES Lymphocytes Neutrophils Eosinophils Basophils Monocytes Leukocytes Expected counts and ranges correspond to expected normal counts and normal ranges for standard cytology (from 20,21). FCM and Standard Cytology in the Elucidation of the Pathological Context Both FCM and standard cytology allowed the detection of blast cells in 28/28 cases of acute leukaemia (25 AML, 1 B- ALL, 2 T-ALL). Presumed lineage of cells was correctly assigned with FCM in all cases, further confirmed by an extended immunophenotypic characterisation of tumour cells. Four cases of AML in remission after chemotherapy (three after the first course and one after the second course) gave false alarms with the hematology analyzer (one called blast cell alarm and three called atypical cell alarms), that were not confirmed after reviewing blood smears under microscope. No increase in blast or immature granulocyte count was evidenced with FCM for these cases. Except one case corresponding to a technical failure, 24/ 25 of known leukemic phase of B-cell lymphoma were correctly identified, corresponding to a B-cell lymphocytosis. A T or NK cell lineage was correctly assigned in all cases of reactive lymphocytosis (14/14). Increased levels of CD2pos/CD16pos cytotoxic lymphocytes were found in 5/14 (36%) cases with benign reactive lymphocytosis. Among the 24 patients with known lymphoma and without detectable leukemic phase by standard cytology, a B-cell lymphopenia was found in 17 cases (68%), one of them being treated by chemotherapy. One case, initially though as a normal subject, showed a specific increase in the B-cell compartment without increased lymphocytosis. This case was further diagnosed as a lymphocytic lymphoma. Among the 51 patients initially cared for acute bacterial infection in absence of hematological context, 11 (21%) had detectable circulating immature granulocytes by the hematology analyzer. All these 11 cases exhibited enhanced levels of circulating immature granulocytes by FCM. Acute bacterial infection was associated with enhanced levels of circulating immature granulocytes by FCM in nine additional cases (18%), without any cytological alarm of the hematology analyzer. Presence of circulating immature granulocytes was confirmed by microscope examination of blood smears in 8/9 cases. As expected, a tendency for enhanced monocyte count with both FCM and hematology analyzer was evidenced in patients with an inflammatory syndrome and without any Figure 4. ROC curve determination of FCM thresholds for detection of circulating blast cells (upper panel) and immature granulocytes (lower panel), when compared with cytology. For cytological detection of blast cells, the answer was presence or absence with a threshold of blast cells of 1%. For cytological detection of immature granulocytes, the threshold was defined at 20/ll, corresponding to two times the cytological 95th percentile, that would correspond to 0.3% 0.5% of counted cells. Cytometry Part A 71A: ,

9 Table 7. Lower and upper Thresholds in G/L for each standard cytological WBC type, defined using ROC curves, with the corresponding specificity, sensitivity, and ROC curve area for each quantitative abnormality STANDARD CYTOLOGICAL TYPE ROC LOWER THRESHOLD ROC UPPER THRESHOLD Leukocytes Lymphocytes Neutrophils Eosinophils NA 0.45 Basophils NA Monocytes NA 1.1 Imm Gran NA 0.2 Blast cells NA 25 STANDARD CYTOLOGICAL QUANTITATIVE ABNORMALITY SPECIFICITY SENSITIVITY ROC CURVE AREA Leukocytosis Leukopenia Lymphocytosis Lymphopenia Neutrophilia Neutropenia Eosinophilia Basophilia Monocytosis Myelemia Blastosis NA: Not applicable. known hematological context (P for both FCM and hematology analyzer). This tendency was significant for CD16pos monocytes counted by FCM (P , Fig. 5), showing that this compartment could be involved in inflammatory reaction processes, as suggested by the literature (Ref. 22, for review). Reciprocally, 35/43 (82%) patients with increased levels of circulating CD16pos monocytes in absence of hematological context had an inflammatory syndrome, whereas 95/128 (74%) patients with normal count of CD16pos monocytes had no inflammatory syndrome (Chi-square, P <10 24 ). DISCUSSION We present the results of an extended differential WBC study by FCM with a 5 colors single tube combination, Figure 5. Comparison of CD16pos monocyte counts in patients without (No) or with (Yes) an inflammatory syndrome, in absence of known hematological disorder. Mean and standard deviation are represented by and bars, respectively. CD36-FITC/CD2-PE1CRTH2-PE/CD19-ECD/CD16-Cy5/ CD45-Cy7, compared with standard cytology, here defined as the combination of hematology analyzer and microscope examination of blood smears. Current staining techniques of blood and bone marrow smears, such as May Gr unwald Giemsa, Wright or Romanovsky staining, were developed at the beginning of the 20th century and are derived from the Pappenheim staining protocol (23,24). Analysis and interpretation of stained blood and bone marrow smears were codified during the 20 years after World War II (25,26). Despite undoubtful successes, such as FAB classification, and continuous improvement in the quality of the reading of blood and bone marrow smears, standard cytology remains poorly reproducible, and is now strongly challenged against other techniques such as molecular biology, cytogenetics or FCM. Another series of factors against standard cytology are related to the marked tendency for automation, with a continuous pressure to decrease the number of technicians and biologists in medical laboratories. This evolution progressively renders very difficult integration of the traditional microscopic review of blood smears in the process of reporting clinical results for an increasing number of laboratories. Microscope leukocyte differential needs expertise and regular cross training for performance of these tests, is labour costing and time consuming, and cannot be easily and automatically handled for quality control and traceability procedures. These series of factors emphasise the need for development and implementation of new laboratory corner stone techniques for diagnosis of hematological disorders (27). In 1988, Terstappen et al. proposed an alternate method for blood and bone marrow differential by FCM (2,28). Since 942 Improved WBC Differential by FCM

10 the report of this concept, very few publications have suggested replacing standard cytology by FCM for differential WBC counting (7 9). However, FCM has been used to enumerate numerous circulating cell types, such as monocytes (8,29), basophils (9), neutrophils and immature granulocytes (10), CD4/CD8 T-lymphocytes subpopulations, NK cells, precursor cells (30,31). FCM can undoubtedly be used as a cell counter (32). Usefulness of FCM in diagnosis of hematological disorders is well established (18,19). FCM can be used to handle minimal residual disease in acute leukaemia, highlighting the accuracy and the specificity of this technique (32,33). It is of note that WBC differential methods by FCM have been developed in veterinary biology. The most apparent advantage is the fact that the operator can be trained in few days compared with the extensive training required for individuals performing manual bone marrow differentials (34). Recently, Finn et al. showed the superiority of FCM in counting lymphocytes and monocytes in samples from pediatric patients (35). Therefore, analysis of the literature leads to the conclusion that WBC differential by FCM is theoretically feasible. The recent emergence of new multicolor flow cytometers at the beginning of this century raised the question of FCM WBC differential in one single tube combination as a technological challenge. For the first time, exploiting the whole potential of a new generation of flow cytometer, including its software possibilities, we have developed a unique combination of 6 markers/5 colors to enumerate circulating WBC types. With this 5 colors single tube combination, we prove for the first time that the concept of WBC differential by FCM developed by Terstappen and Loken in 1988 (28) is feasible, and provide reliable biological information. The antibodies that we used are very well known commercial antibodies already used for diagnosis, for which cellular reactivity is well documented in the literature (Table 1). The originality of our method resides in the combination of these 6 markers, and in our gating strategy. On the basis of the known FCM characteristics of targeted cell types, we have developed a completely new progressive gating strategy with both orientating and specific gates. Except for basophils, our results show that FCM was as good as standard cytology in detection of numerical abnormalities of standard WBC types. Detection and counting of basophils by standard cytology are rather imprecise explaining why the strength of the link between FCM and cytology was lower than for the other types (9). Recognition of abnormal circulating blast cells or immature granulocytes was nearly as good as microscope examination of blood smears, with the advantage of quantifying precisely the levels of circulating immature cells with FCM. Depending on the setting of the thresholds, FCM was more sensitive than cytology in detection of circulating blasts and immature granulocytes. FCM allowed to immediately presume the lineage of abnormal circulating precursor cells. The 5 colors single tube combination allowed to give a first informative and relevant indication on the nature of in all cases of lymphoproliferative disease with leukemic phase and in all cases of reactive lymphocytosis. For patients without known hematological disorder, FCM identified a group of patients with inflammatory syndrome (acute bacterial infection, heart failure, cancer, systemic disease, etc) with enhanced count of CD16pos monocytes. CD16pos monocytes, which expansion has been first described in sepsis (36), are found in nearly all inflammatory diseases (22). These monocytes secrete high levels of TNF-a and are believed to be precursors of dendritic cells (37,38), highlighting the putative clinical interest of this new cell parameter. To date, up to 20 different cell subsets can be detected in normal peripheral blood, including lymphocyte subsets, granulocyte and monocyte subsets, dendritic cell sub-populations, circulating precursors and immature cells, and very rare events such as circulating plasma cells and endothelial cells. Today, none of the commercially available flow cytometer is able to enumerate all these populations in one single combination of markers. Thus, FCM counting of circulating blood cell subpopulations is tightly dependant on the combination of markers and the gating strategy. Our first objective was to detect and quantify at least the same abnormalities than standard cytology, and our second objective to bring supplementary interesting information regarding the diagnosis of these abnormalities. Our combination is probably not the only one FCM solution allowing such extended WBC differential, and further studies will be needed to define the best combination and the best gating strategy. Mainly, our description of the different lymphocyte subsets is poor, since we deliberately did not use the CD3 marker, and we missed CD4pos and CD8pos T-lymphocyte subsets. Also, we used the CD2pos/CD16pos criteria to estimate the cytotoxic compartment, being unable to discriminate between T and NK cytotoxic lymphocytes and ignoring the fact that some NK cells may be CD2 negative and/or predominantly express the CD56 marker. But our results demonstrate that, in one single combination of markers, FCM is a technological alternative that can replace standard cytology, giving a precise information on standard WBC subsets and a precise quantification of abnormal circulating blood cells, whatever their lineage. FCM was better than hematology analyzer in the resolution of cytological abnormalities, being close to microscope cytology. FCM labellings, and acquisition can be automated. FCM systematically gives a quantitative reliable result and FMC is well adapted to computerised quality controls and traceability. Recently, a software procedure for detection and quantification of leukemic phases of B-cell disorders by FCM has been proposed (6), demonstrating the feasibility of automated analysis of FCM results. Thus, our results bring a new breakthrough in the view of automated strategies for routine diagnosis of hematological disorders. The question is now to define the optimal place of FCM in WBC differential, as a first line counter to screen any blood sample or just behind the standard electronic WBC counter to reduce the rates of manual reviews of peripheral blood smears and to increase the efficiency of generating WBC differentials. FCM could then become very useful to help the cytologist in reviewing selectively abnormal blood smears in routine hematology laboratory, cytology bringing additional qualitative recognition of morphological abnormalities such as villous lymphocytes, fea- Cytometry Part A 71A: ,

11 tures of plasma cell differentiation, presence of nucleoli, decondensed chromatin or Auer rods of blast cells, absence of granules in neutrophils or pseudopelger cells, or presence of nuclear bodies or punctuations or parasites in erythrocytes. ACKNOWLEDGMENTS UMR CNRS 6101 is laboratoire labellise Ligue Nationale contre le Cancer. We are grateful to Beckman Coulter Company for supplying reagents. We thank Mr Ronald Paul, Research and Development, Beckman Coulter, Miami, FL, USA, and Mr Antoine Pacheco, Beckman Coulter, Villepinte, France for helpful technical discussion. LITERATURE CITED 1. Novis DA, Walsh M, Wilkinson D, St Louis M, Ben-Ezra J. Laboratory productivity and the rate of manual peripheral blood smear review: A College of American Pathologists Q-Probes study of 95, 141 complete blood count determinations performed in 263 institutions. Arch Pathol Lab Med 2006;130: Terstappen LW, Shah VO, Conrad MP, Recktenwald D, Loken MR. 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