Review Article. Cytometry Part B (Clinical Cytometry) 72B: (2007)

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1 Cytometry Part B (Clinical Cytometry) 72B: (2007) Review Article Identification and Quantification of High Fluorescence-Stained Lymphocytes as Antibody Synthesizing/Secreting Cells Using the Automated Routine Hematology Analyzer XE-2100 J. Linssen, 1 * V. Jennissen, 2 J. Hildmann, 3 E. Reisinger, 2 J. Schindler, 2 G. Malchau, 2 A. Nierhaus, 4 and K. Wielckens 2 1 Sysmex Europe GmbH, Norderstedt, Germany 2 Institute for Clinical Chemistry and Haematology of the University of Cologne, Germany 3 Becton-Dickinson Biosciences, Heidelberg, Germany 4 Department of Critical Care, University of Eppendorf, Hamburg, Germany Objectives: The aim of this study was to classify and quantify the high fluorescence lymphocytes area (HFL-count) from the SYSMEX XE-2100 leucocyte differential channel as antibody-synthesizing or -secreting cells (ASC, plasma cells or lymphoplasmacytoid cells) in reactive diseases. To unequivocally identify the HFL cells, all possibly eligible cell populations have been investigated: activated B-lymphocytes, activated T-lymphocytes, large granular lymphocytes (LGL), activated monocytes, and immature granulocytes. Methods: In total, 85 patients were analyzed on the XE-2100 and compared with the automated image analysis system Cellavision Diffmaster 96 based on artificial neural network and immunophenotyping method with the BD FACSCalibur TM. Results: Reproducibility tests for HFL demonstrated a mean coefficient of variation of 13.9% for very low results and 1.5% for high results. The linearity data showed a good correlation (R 2 = 0.99) between expected and measured HFL. The comparison with possibly eligible cell populations showed no significant correlation between activated monocytes and immature granulocytes, with most immature granulocytes (promyelocyte I or II), natural killer cells or LGLs, activated T-lymphocytes, and sub-t-lymphocytes populations. However, for activated B-lymphocytes an excellent significant correlation with the peripheral blood smear, and the immunophenotyping method has been found with R 2 = 0.900, P < and R 2 = 0.897, P < 0.001, respectively. The slope of 1.1 and intercept of minus 5 cells/ml of the regression equation between HFL-count and ASC (smear) do indicate an excellent quantification of the HFL-count, as well. Conclusion: The fully automated SYSMEX XE-2100 HFL-count identifies and quantifies the ASC cells (activated B-lymphocytes) with high precision and reliability in patients without hematology system diseases, thus providing a potential screening and monitoring tool for any patient with suspected infection. Additional studies are required to comprehend in more detail the full clinical utility of an HFL (ASC) count as a potential diagnostic indicator of inflammation, infection, or sepsis. q 2007 Clinical Cytometry Society Key terms: high fluorescence lymphocytes (HFL); antibody synthesizing cells (ASC); activated B-lymphocytes; SYSMEX XE-2100; BD FACSCalibur TM ; cellavision DIFF-Master DM96 INTRODUCTION Fluorescence Flow Cytometry The XE-2100 (Sysmex Corporation, Kobe, Japan), an automated hematology analyzer, is a modern sophisticated cell analysis system performing leukocyte differential analysis by fluorescence staining combined with scat- Grant sponsor: Sysmex Europe, Norderstedt, Germany. *Correspondence to: J. Linssen, Scientific Department, Sysmex Europe GmbH, Bornbarch 1, Norderstedt, Germany. Linssen.jo@sysmex-europe.com Received 27 April 2006; Revision 28 August 2006; Accepted 30 August 2006 Published online 31 January 2007 in Wiley InterScience (www. interscience.wiley.com). DOI: /cyto.b q 2007 Clinical Cytometry Society

2 158 LINSSEN ET AL. FIG. 1. HFL are displayed as purple dot plots (as are lymphocytes). IGs are displayed as blue dot plots obtainable from the data-browser screen of the XE-IG Master. Results of an absolute HFL count as well as the HFL percentage are shown in the research screen. The IG count (IG no.) as well as IG percentage (IG%) are reported as extended differential parameters. Mono indicates monocytes; Lymph stands for lymphocytes; Neutr for neutrophils; Eos for eosinophils. tered light intensity (1). The combination of side scatter (inner complexity of the cell), forward scatter (size of the cell), and fluorescence intensity (RNA content) of nucleated cells describes both a concise and precise image of each detected peripheral blood cell. Fluorescence flow cytometry enhances analytical possibilities beyond the normal five-part differential by providing excellent cluster resolution and separation of abnormal blood cells. A nucleated red blood cell count and immature granulocyte count (IG) is part of an extended differential on the XE-2100 with the potential to improve the diagnostic usefulness of the routine fivepart differential, which can be reported directly for all analyzed samples (1,2). Beside the IG, there is a distinct separation of an abnormal cell population with high fluorescence intensity above the monocyte and lymphocyte region. This is used for flagging of atypical lymphocytes. They are detected by their characteristically high fluorescence intensity, reflecting a high RNA content. In the present study, it was to prove that the fluorescence RNA-stain method on XE-2100 can classify and quantify the atypical lymphocytes region in activated B- lymphocytes, synthesizing clone-specific antibodies, the plasma cells, or the lymphoplasmocytoid cells. Figure 1 displays the leukocyte differential scattergram of the XE (left to right) from a normal patient sample, a patient sample containing IG, and a patient sample containing both IG and high fluorescence lymphocytes (HFL). Cell Biology Plasma cells or lymphoplasmacytoid cells are the terminally differentiated, nonproliferating effector cells of the B-cell lineage and sole producers of antibodies. Hence they represent both components of the adaptive human immune system being crucial for effective immune response in reactive diseases. They decisively support adequate immune response to microbial pathogens with the needed specificity and rapidity. Plasma cells can be found in bone marrow as so-called long-life plasma cells; but they are rarely seen in peripheral blood of normal healthy individuals. For this reason, the presence of plasma cells in a patient blood sample indicates an immune response as a result of infections. B cell generation is starting in the bone marrow. Hematopoietic stem cells initially differentiate to naive B cells (Fig. 2. The development is continued in the spleen (3,4). Some B-cells, the B 1 cells, develop a unique cellsurface phenotype and self-renewing capacity, mainly responsible for the production of natural IgM without antigen or T-cell stimulation. They provide the first line of antibody defence against pathogens. Those antibodysecreting or synthesizing cells (ASC) are predominantly found in the peritoneal and pleural cavities and the gut lamina propria (IgA antibodies). They are not found as ASC in blood circulation. A relatively small proportion of conventional B cells (B 2 cells) remain in the splenic marginal-zone as naive noncirculating marginal-zone B cells (4,5). The largest part of the B 2 cell population matures into continuously circulating (spleen lymph node bone marrow) long-lived follicular B cells. The first B-cell effector function in response to antigens is the differentiation of marginal-zone B cells into plasma cells. Without T-cell interaction, marginal-zone B cells recognize antigens independently within a few hours of immunization. With the T-cell independent antigen, they move to the red pulp of the spleen proliferating from plasmablasts to IgM ASC, with no class-switch possibilities and populate through the efferent lymph to the blood distant sites. Another effector function is when follicular B cells encounter antigen and receive T-cell help. T-cell help for B cells occurs in secondary lymphoid tissues providing an ideal microenvironment for T cells and B cells to interact with each other and with other cell types such as dendritic cells (DC) (4,6 8). Here B cells form dynamic conjugates with T cells, receive cognate T-cell help, and differentiate along one of two possible pathways (9): (a) an

3 IDENTIFICATION AND QUANTIFICATION OF HIGH FLUORESCENCE-STAINED LYMPHOCYTES 159 FIG. 2. Model summarizing development, generation, maintenance, and function of ASC cells (plasma cells). B cells develop from pluripotent stem cells to naive B cells in the bone marrow. Naive B cells that exit the bone marrow continue their development in the spleen. A small proportion home to the marginalzone to become marginal-zone B-cells (MZ), and a higher extent form the long-lived circulated naive follicular B cells (FO). The spleen is also required for the generation and maintenance of B 1 cells. They are responsible for the production of natural IgM and for secretion of IgA in the gut. The first B cells to respond to a foreign antigen without help of T-cell (T I ¼ T-cell independent antigen) by differentiating into plasma cells are marginal-zone B cells (day 1). After antigen presentation (T D ¼ T cell dependent antigen) from active DCs to T helper cells (T H ), some active follicular B cells also differentiate supported by activated T H cells into extrafollicular plasma cells (within week 1). Both are IgM antibody-producers with no possibility to class-switch. After encountering antigen and receiving T-cell help, some follicular B cells form a germinal centre and proliferate and differentiate (between day 10 and day 14) to class-switch plasma cells (IgG, IgA, or IgE) or memory cells (MC). extrafollicular pathway giving rise to short-lived plasma cells and (b) a follicular pathway giving rise to germinal centers. In the extrafollicular pathway, antigen-specific B cells migrate to the red pulp of the spleen or into the lymph nodes, then to the medullary cords and differentiate into short-lived, no class-switch possibility-igm ASC (first week). In the follicular pathway, small numbers of antigen-specific B cells (plasma-blasts) seed the follicles giving rise to germinal centers in which high-affinity memory B cells and long-lived, class-switch (IgG, IgA, or IgE) ASC develop (second week). Particularly, the IgM ASC from the extrafollicular pathway (independent antigen mantel-zone B-cell stimulation and dependent antigen follicular B cells stimulation) can traffic through the efferent lymph to the blood to populate distant sites (9,10). The concentration and the ratio of ASC in peripheral blood can be useful for clinical diagnosis and therapeutic monitoring in many diseases. ASC measured as HFL from a routine hematology analyzer could provide valuable information about the stage of an infectious disease where the acute phase is characterized by elevated neu-

4 160 LINSSEN ET AL. trophilic granulocytes and IGs and the healing phase is characterized by elevated ASC, or to differentiated between acute phase response to either infection or inflammation (inflammation shows no ASC). In sepsis patient, ASC could provide valuable information in differentiation between hyperinflammation and immune paralysis or to differentiate between the rapid T-cell independent antigen response and the slower T-cell dependent antigen response. Further, ASCs are also frequently detected as plasma cells in myeloma/plasmocytoma, lymphoplasmacytic lymphoma (immunocytoma, Morbus Waledenström), and in diffuse, large B-cell lymphoma (immunoblastoma). Accordingly, count and classification of ASC in plasma cells or lymphoplasmacytoid cells can be helpful for detecting and monitoring such malignant diseases. ASC enumeration is conventionally done by means of peripheral blood film morphology with light microscopy. However, this manual method is laborious as well as imprecise because of the low number of cells counted and interobserver variability. Small ASC percentage numbers, i.e. in neutrophilic acute phase response, are often missed in a standard 100-cell differential count. Flow cytometry with monoclonal antibodies is unsuitable as a screening test. The procedure is not automated. It is expensive and time-consuming. This study compared the HFL-count on XE-2100 with the immunophenotyping flow cytometry method and the digital 400 cell automated image analysis system with preclassification. Basic performance in terms of reproducibility and linearity has also been carried out for the XE HFL-count. clustering by the system is possible). Consequently, such obviously marked samples had to be excluded from the study. Principle of HFL Counting by the Hematology Analyzer XE-2100 HFL and leukocyte differential parameters were measured with the XE HFLs are differentiated from the lymphocyte population by their high fluorescence and low side scatter intensity in the XE-2100 leukocyte differential channel (Fig. 1). After chemical lysis of erythrocytes and preparation of leukocytes, the fluorescence polymethine dye reacts with the ribonucleic acid of the leukocytes, and the flow cytometry unit detects and classifies the respective cells by side scatter and side fluorescence. They are reported as percentage of the total leukocyte count and as an absolute count in the research screen as research parameter \OTHERS." MATERIALS AND METHODS Blood Samples All blood samples were routine patient samples anticoagulated with K 3 EDTA. All samples were retrospectiveverified and ensured that all patient samples were from patients without hematology system diseases (AML, ALL, NHL). In total, 85 patient samples were processed on the XE-2100 without any preparation and, immediately after sampling, two separate blood films were prepared by the automated SYSMEX slide preparation and stain unit SP-100, using the May Grünwald Giemsa staining. A manual cell leukocyte differential count was then performed by the automated image analysis system Cellavision Diffmaster (DM96) (11). The same samples were further analyzed with the BD FACSCalibur TM after whole blood staining by application of monoclonal antibodies. Twenty patients had a negative HFL count (HFL ¼ 0/ ml blood) and 65 patients showed a positive HFL count of up to 600 cells/ml (0.2 10% of total WBC count). Specimens from patients with hematological system disease (AML, ALL, NHL) in general show up with a \blast flag," while suppressing the \atypical lymphocyte flag" with an indication of the unreliability of the HFL count (population is colored in grey and no automated FIG. 3. Morphologically cell classification in May-Grünwald stain and 1000 magnification with the Cellavision DM96. Cell classification in five pathological groups: (A) IGs,(B) activated monocytes, (C) LGL, (D) activated T-lymphocytes, and (E) activated B-lymphocytes.

5 IDENTIFICATION AND QUANTIFICATION OF HIGH FLUORESCENCE-STAINED LYMPHOCYTES 161 FIG. 4. Total leukocytes differential count with the immunophenotyping flow cytometry method on the BD FACSCalibur. Manual Differential Count with Automated Image Analysis System DM96 The 400-cell leukocyte differential count according to NCCLS (11) was performed with the standardized automated image analysis system DM96 with preclassification (from CellaVision AB, Sweden) (12). After automated preclassification in segmented neutrophils, monocytes, lymphocytes, eosinophils, and basophils, white blood cells were manually classified (Fig. 3) in IGs (metamyelocytes, myelocytes, and promyelocytes I and II), activated monocytes (macrophages), natural killer cells (NK cells, large granular lymphocytes), activated T-lymphocytes (cytotoxic T-lymphocyte, chemotaxis cells (13) [shape change], large basophilic blast-like cells [immunoblasts]), and activated B-lymphocytes (plasma cells and lymphoplasmacytoid cells) (14,15). Flow Cytometry Immunophenotyping Analysis with the BD FACSCalibur Flow cytometry analysis was performed on a BD FACS- Calibur system. FSC, SSC, and four-color fluorescence signals were determined for each cell and stored in listmode data files in FCS 2.0 format. The data files were acquired and analyzed by a multitube and multistep gating procedure using BD MultiSET TM 1.1.2, BD CellQuest Pro a software, and BD DIVA TM In a first tube, total leukocytes were differentiated in neutrophils, monocytes, lymphocytes, eosinophils, and basophils by using SSC, FSC-H, HLA-DR FITC, CD123 PE, CD45 PerCP-Cy5.5, and CD14 APC. Monocytes are defined as CD14 high /SSC int,lymphocytes are defined as CD45 high /SSC low /NOT monocytes, basophils are defined as CD123 high /anti-hla DR neg, eosinophils are

6 162 LINSSEN ET AL. Table 1 Reproducibility HFL Results for 10 Repeat Analyses of Two Patient Samples Sample no. Mean (ml) SD (ml) CV (%) 1 66 (*1% of WBC) (*10% of WBC) defined as cells with high side scatter fluorescence and high auto fluorescence appearing as FL1-FL4 intermediate high (SSC high /FL1-FL4 int ), and neutrophils are defined as SSC int-high /NOT (lymphocyte OR monocyte OR basophil OR eosinophil) (Fig. 4). In a second and a third tube, total lymphocytes were differentiated in B-lymphocytes, T-lymphocytes, and NKlymphocytes by using BD Multiset IMK Kit (16). One tube was used for the determination of T-lymphocyte subpopulations (T helper-lymphocytes and T-suppressor lymphocytes) with CD3 FITC, CD8 PE, CD45 PerCP, and CD4 APC. The second tube was used the for differentiation of B-lymphocytes, T-lymphocytes, cytotoxic T-lymphocytes (CTLs), and NK-lymphocytes with CD3 FITC, CD16 þ 56 PE, CD45 PerCP, and CD19 APC, according to manufacturer s preparation and analysis instructions. In a fourth tube, total lymphocytes were differentiated in total B-Lymphocytes, SSC high and SSC low B-Lymphocytes, cytoplasmic IgM (cyigm), and CD138 plasma cells (17) by using surface and intracellular staining of CD138 FITC, anti- IgM PE, CD45 PerCP Cy5.5, and CD14 APC (to exclude contamination of monocytes in the lymphocyte gate). The percentage of all cell types was calculated as a proportion of all leukocyte events. The absolute count of all cell types per ml blood was calculated from the total leukocyte count of the XE Statistical Analysis Linear regression analysis and Pearson product moment correlation coefficient was performed with Sigma- CHART 1. Serial dilution of sample with a high HFL count. Stat for Windows version 2.03 statistical software. Statistically significant correlations were defined at a P-level of <0.05. RESULTS HFL Count Reproducibility Reproducibility was quantified by performing 10 consecutive measurements on two different blood samples. The samples selected had a high and a low value, respectively. The coefficients of variation (CV) demonstrated good results for both samples (Table 1). HFL Count Linearity A sample with a high HFL count (590/mL) has been diluted with phosphate buffered saline in levels of 100, 80, 50, 20, 10, and 5%. Linearity data showed good correlation between expected and measured HFL values for all diluted steps (Chart 1). Comparison of XE-2100 Differentiation with Immunophenotyping Flow Cytometry and Manual Reference Count Table 2 displays the correlation coefficients and slopes from the five-part differential counts between XE-2100, FACSCalibur, and DM96 from all 85 patients. Table 2 Correlation of Leukocyte Differential Counts Between XE-2100/BD FACSCalibur/DM96 Cells per ml Intercept Slope R P XE-2100 versus FACSCalibur Neutrophils <0.001 Lymphocytes <0.001 Monocytes <0.001 Eosinophils <0.001 Basophils <0.001 XE-2100 versus Cellavision DM96 Neutrophils <0.001 Lymphocytes <0.001 Monocytes <0.001 Eosinophils <0.001 Basophils <0.001 FACSCalibur versus Cellavision DM96 Neutrophils <0.001 Lymphocytes <0.001 Monocytes <0.001 Eosinophils <0.001 Basophils <0.001

7 IDENTIFICATION AND QUANTIFICATION OF HIGH FLUORESCENCE-STAINED LYMPHOCYTES CHART 2. Linear regression between absolute lymphocyte count on XE-2100 and BD FACSCalibur. The solid line represents the regression line, dashed lines represent the prediction and confidence intervals. Correlation with flow cytometry and manual differentiation was good for all cell populations, except the basophil count from the manual method. The manual basophil count demonstrates superiority of the precision of automated counts over the manual method (18). The correlation for basophils between XE-2100 and BD FACSCalibur demonstrated good results (R 2 ¼ 0.651). The correlation for basophils between XE-2100 and manual method, and between BD FACSCalibur and manual method resulted in R 2 ¼ and R 2 ¼ 0.442, respectively. Chart 2 shows excellent correlation between the total absolute lymphocyte count on XE-2100 (with HFL population) and the absolute lymphocyte count on BD FACS- Calibur. Identification and Quantification of the HFL Area To unequivocally identify the HFL cells, a total of 85 patients was investigated for all possibly eligible cell populations by comparing the HFL count with the 163 immunophenotyping flow cytometry method on the BD FACSCalibur and the digital 400 cell-automated image analysis system DM96. The analyzed cell populations were the nonlymphocyte cell population; the activated monocytes (macrophages) and IGs (metamyelocytes myelocytes promyelocytes I and II) and the lymphocyte subpopulation; the NK cells (large granular lymphocytes), activated T-lymphocytes, and activated B-lymphocytes. Comparison of XE-2100 HFL-count with activated monocytes and IGs from manual microscopic automated image analysis system DM96. The peripheral blood samples were analyzed on the XE-2100 instrument and compared with the peripheral blood smear, and analyzed on the DM96 with preclassification (five-part differential). Monocytes were manually differentiated further in nonactive and activated monocytes, characterized as monocytes with vacuolization and shape change as the so-called macrophage. IGs were manually classified in metamyelocytes, myelocytes, and promyelocytes. The linear regression displayed in Table 3 shows no statistically significant (P > 0.05) correlation (R 2 ¼ 0.002) between HFL and activated monocytes. Also, the total IG or isolated promyelocytes show no correlation with the HFL count. (R 2 ¼ 0.031, P > 0.05, respectively. R 2 ¼ 0.007, P > 0.05). Comparison of XE-2100 HFL-count with different lymphocyte subpopulations analyzed with the automated image analysis system DM96 and the immunophenotyping flow cytometry method on the BD FACSCalibur. The peripheral blood samples have been analyzed on the XE-2100 instrument and the HFL-counts were compared to the different lymphocyte subpopulations analyzed on the peripheral blood smear and the immunophenotyping flow cytometry method on the BD FACSCalibur: NK-lymphocytes, T-lymphocytes, and B-lymphocytes (Table 4). NK-lymphocytes were classified microscopically as large granular lymphocytes (LGL) and immunophenotypically as CD16 þ þ CD56 þ and CD3 cells. T-lymphocytes were differentiated microscopically in activated T-lymphocytes defined as large lymphocytes (except plasma cells) with ample grey-blue cytoplasm or with azurophilic granules (CTL) or with increased basophilic staining of the cytoplasmic periphery with loose chromatin and nucleoli (Immunoblasts) and lymphocytes with chemotaxis (shape change). Immunophenotypically, T-lymphocytes are classified in CD4 þ (helper cells) and Table 3 Linear Regression Between HFL-Count and Activated Monocytes and IG HFL # versus activated monocytes # (DM96) HFL # versus total IG # (DM96) HFL # versus promyelocytes # (DM96) # ¼ absolute cell count/ml blood. Regression equation R P HFL # ¼ þ ( act. Mono #) HFL # ¼ þ (0.153 IG #) HFL # ¼ þ (0.427 Prom. #)

8 164 LINSSEN ET AL. Table 4 Linear Regression Between XE-2100 HFL and Lymphocyte Subpopulations Analyzed from Peripheral Blood Smears and Immunophenotyping with the BD FACSCalibur Flow Cytometer Regression equation R P Natural killer lymphocytes (NK-cells) XE-2100 versus FACSCalibur HFL # versus NK cells # (FACS) HFL # ¼ þ ( NK # ) XE-2100 versus DM 96 HFL # versus LGL # (DM96) HFL # ¼ þ ( LGL#) DM 96 versus FACSCalibur LGL # (DM96) versus NK (FACS) # LGL # ¼ þ (0.688 NK #) <0.001 T-lymphocytes XE-2100 versus DM 96 HFL # versus activated T-lymph # (DM96) HFL # ¼ þ ( Act T #) HFL # versus CTL # (DM96) HFL # ¼ þ (0.187 CTL #) HFL # versus chemotaxis # (DM96) HFL # ¼ þ (0.144 Chemot #) HFL # versus large lymph # (DM96) HFL # ¼ þ ( large lym #) XE-2100 versus FACSCalibur HFL # versus total T cells # (FACS) HFL # ¼ þ ( Tot T-cell #) HFL # versus CD4 þ cells # (FACS) HFL # ¼ þ ( CD4 þ #) HFL # versus CD8 þ cells # (FACS) HFL # ¼ þ ( CD8 þ #) HFL # versus CTL cells # (FACS) HFL # ¼ þ (0.131 CTL #) FACSCalibur versus DM 96 CD8 þ cells # (FACS) versus activated CD8 þ # ¼ þ (1.134 Act T #) <0.001 T-lymph # (DM96) CTL (FACS) # versus CTL # (DM96) CTL # ¼ þ (0.899 CTL #) <0.001 CD4 þ cells # (FACS) versus activated CD4 þ # ¼ þ (2.224 Act T #) T-lymph # (DM96) B-lymphocytes B-cells: XE-2100 versus DM 96 HFL # versus activated B-lymphocytes # (DM96) HFL # ¼ þ (1.127 Act B # ) <0.001 HFL # versus plasma cells # (DM96) HFL # ¼ þ (1.247 plasma cell #) <0.001 B-cells: XE-2100 versus FACSCalibur HFL # versus total B-cells (CD19þ) # (FACS) HFL # ¼ þ (0.338 Tot B-cell # ) <0.001 HFL # versus ASC # (FACS) HFL # ¼ þ (1.518 ASC #) <0.001 B-cells: FACSCalibur versus DM 96 ASC # (FACS) versus activated B # (DM96) ASC # ¼ þ (0.610 act B #) <0.001 Total B cells # (FACS) versus activated B # (DM96) Tot B-cell # ¼ þ (1.046 act B #) <0.001 # ¼ absolute cell count/ml blood. CD8 þ (suppressor cells), and CTLs as CD16 þ, CD56 þ, and CD3 þ cells. B-lymphocytes are classified microscopically in activated B-lymphocytes defined as plasma cells or lymphoplasmacytoid cells, both being ASC. Immunophenotypically, the B- lymphocytes are classified as activated B-lymphocytes, with CD19 þ,ssc high,increaseofcyigmandcd138 þ. The linear regressions between HFL, DM96, and BD FACSCalibur for the lymphocyte subpopulations NKcells, T-lymphocytes, and B-lymphocytes are displayed in Table 4. The lymphocyte subpopulation NK-cells shows no statistically significant correlation with the HFL count. Total NK-cells determined on FACSCalibur (CD16 þ þ CD56 þ and CD3 cells) result in a correlation R 2 ¼ and P > The LGL, morphologically defined as active NK cells, shows no significant correlation (R 2 ¼ 0.002, P > 0.05) either. As expected, LGL cells from the peripheral blood smear yield a poor but significant correlation (R 2 ¼ 0.314, P < 0.001) with the total NKcells on the FACSCalibur. The T-lymphocyte subpopulations show no statistically significant correlation with the HFL count, except a poor significant correlation for CD4 cells (R 2 ¼ 0.053, P ¼ 0.041). The total T-lymphocytes, T-suppressor (CD8), and the CTLs, respectively, result in values of R 2 ¼ 0.046, R 2 ¼ 0.011, and R 2 ¼ 0.026, respectively, all with P-values >0.05. The activated T-lymphocytes were defined in the peripheral blood smear as CTLs, cells displaying chemotaxis, and large lymphoid cells (excluding plasma cells). The respective correlations reveal values of R 2 ¼ 0.032, R 2 ¼ 0.067, and R 2 ¼ 0.000, respectively, all with P-values of >0.05. As expected CTL cells from the peripheral blood smear yield a significant correlation (R 2 ¼ 0.494, P < 0.001) with the CD16 þ, CD56 þ, and CD3 þ CTLcells. Total CD8 þ cells showed excellent and significant correlation (R 2 ¼ 0.814, P < 0.001) with the total activated T-lymphocyte count (CTLs, cells displaying chemotaxis and large lymphoid cells) from the peripheral blood smear. Activated B-lymphocytes defined in the peripheral blood smear as plasma cells plus lymphoplasmacytoid cells and, ASC defined as CD19 þ, SSC high, increase of cyigm and CD138 þ resulted in an excellent correlation with HFL each. Correlation coefficients were R 2 ¼ (with P < 0.001) and R 2 ¼ (with P < 0.001), respectively. Correlation of HFL with only plasma-cells (the morphologically defined type) is good with R 2 ¼

9 IDENTIFICATION AND QUANTIFICATION OF HIGH FLUORESCENCE-STAINED LYMPHOCYTES 165 FIG. 5. Example from a surgery patient, 7 and 10 days after surgery; ASC count from XE-2100 (¼HFL) and ASC count from BD FACSCalibur on day 7 (ASC-HFL ¼ 60/mL and ASC-FACS ¼ 80/mL) and on day 10 after increase of the ASC count (HFL ¼ 270/mL and ASC-FACS ¼ 280/mL). The smear confirmed results of increased ASC (ASC-smear ¼ 240/mL) However, combination of both (as shown before) as ASCs or activated B-lymphocytes showed the most convincing correlation. DISCUSSION The presence of ASC in patient blood sample indicates an immune response (in reactive diseases) as a result of infection. The concentration of ASC in peripheral blood may significantly support diagnosis and follow-up of inflammation and infectious diseases. Counting of ASC and subdivision in plasma cells or lymphoplasmacytoid cells is usually done by means of light-microscopic peripheral blood film morphology. However, this manual method is time-consuming, labor intensive, and frequently imprecise because of the small numbers of cells and the interobserver variability. Identification and quantification of the HFL, the atypical lymphocytes region from the XE-2100 leukocyte differential channel, as ASC has the advantage of high precision due to the high number of cells counted and its entire process automation meeting time and quality requirements. The HFL count from the XE-2100 leukocyte differential channel demonstrated excellent reproducibility in low-count and highcount samples. The linearity data showed good correlation between expected and measured HFL. To prove that in case of reactive diseases the cells clustered in the HFL area are ASC, besides immune flow cytometry and peripheral blood smear ASC analysis, the eligible cell populations in reactive diseases, as there are activated monocytes, IGs, NK lymphocytes, activated T- lymphocytes, and T-subpopulations, have been comparatively analyzed, as well. Comparison with the manual blood smear showed that there was no significant correlation between HFL and activated monocytes or macrophages, and total IGs or isolated promyelocytes. There was no correlation between HFL and the NK cells, the so-called non-t-non- B-lymphocytes, in the peripheral blood smear. There was no significant correlation visible with the LGL and FACS analyses either. Poor but significant correlation between NK-cells from immunophenotyping and LGLs from the manual blood smear was obvious. The different T-cell subpopulations and the activated T-lymphocytes defined in the peripheral blood smear showed no correlation, with the HFL-count on the XE-

10 166 LINSSEN ET AL analyser. In contrast to CD4þ (T-Helper cells), the total CD8 þ cells showed excellent and significant correlation with the total activated T-lymphocytes from the peripheral blood smear, and thus confirmed the accuracy of the total activated T-lymphocytes classification defined as all abnormal lymphocytes excluding plasma cells and lymphoplasmocytoid cells. The HFL-count showed good correlation with all B- lymphocytes. It also correlates significantly with sub-blymphocytes. Excellent correlation was obtained with activated B-lymphocytes as ASC from the peripheral blood smear as well as from the immunophenotyping method. As well, correlation of HFL with plasma-cells (morphologically defined) only is good. Combining both ASC showed by far the most convincing correlation. The correlation of HFL with the ASC immunophenotyping method (defined as positive for CD19 and SSC high and increased cytoplasm IgM and upregulated CD138 þ ) showed a very good result, equally. Overall, there was excellent and significant correlation between both comparison methods for ASC, the peripheral blood smear, and immunophenotyping. Figure 5 displays the potential usefulness of such superior correlation and reliable quantification in clinical routine by an example of a patient. There was a comparable initial count (7 days after surgery) for ASC from both XE-2100-HFL and from immunophenotyping with CD19, SSC, cy IgM, and CD138. A second measurement 3 days later resulted in substantially increased ASC counts for both methods (HFL from XE-2100 and ASC from BD FACSCalibur). The ASC count from DM96 confirmed the automated results. In conclusion, the results deliver evidence that the high HFL-count from an automated routine hematology analyser (XE-2100) is identified and quantified as ASC. An elevated count is an indication for an immune response to infectious disease. Lymphoproliferative disorders or other systemic diseases that would also show signals in the HFL area have to be excluded, since in such clinical settings the analyzer will not discriminate a distinct HFL population. Such obvious samples are markedly flagged and therefore exempted in this study. During infectious diseases, the peripheral blood plasma-cell concentration (ASC) is not always elevated despite of high Ig values. This is due to antigen presentation by antigen presenting cells (i.e. DC) happening predominantly in local lymph nodes. Consequently, the presence of ASC in peripheral blood is mirroring the early response of the innate immune system to T-independent antigen by marginal-zone lymphocytes being activated and differentiated to plasma cells in the spleen; or a later reaction through both the T-independent or the T-dependent pathway to circulated antigens as observed in sepsis. This provides new possibilities for a fast and reliable screening and monitoring of intensive care SIRS patients with suspect of a local infection or even sepsis. A distinct differentiation between T-independent antigen response and T-cell supported immune response is obvious by measuring the HFL (¼ASC) concentration in peripheral blood of patients concerned. Further clinical studies are necessary to evaluate the entire usefulness of automated ASC measurement as screening assay for infectious diseases in clinical settings. Generally accepted reference values have yet to be established. Once the automated ASC count has been proven its value and, is established in clinical medicine as well as, accepted by physicians in clinical routine, reevaluation of results by visual microscopy will not be necessary for blood samples from reactive diseases containing ASC (while IP messages are absent or other particularities denoting decreased reliability). 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