A subscription to JoVE is required to view this content. Sign in or start your free trial.

In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

The MDS diagnosis is difficult in the absence of morphological criteria or non-informative cytogenetics. MFC could help refine the MDS diagnostic process. To become useful for clinical practice, the MFC analysis must be based on parameters with sufficient specificity and sensitivity, and data should be reproducible between different operators.

Abstract

A working group initiated within the French Cytometry Association (AFC) was developed in order to harmonize the application of multiparameter flow cytometry (MFC) for myeloid disease diagnosis in France. The protocol presented here was agreed-upon and applied between September 2013 and November 2015 in six French diagnostic laboratories (University Hospitals of Saint-Etienne, Grenoble, Clermont-Ferrand, Nice, and Lille and Institut Paoli-Calmettes in Marseille) and allowed the standardization of bone marrow sample preparation and data acquisition. Three maturation databases were developed for neutrophil, monocytic, and erythroid lineages with bone marrow from "healthy" donor individuals (individuals without any evidence of a hematopoietic disease). A robust method of analysis for each myeloid lineage should be applicable for routine diagnostic use. New cases can be analyzed in the same manner and compared against the usual databases. Thus, quantitative and qualitative phenotypic abnormalities can be identified and those above 2SD compared with data of normal bone marrow samples should be considered indicative of pathology. The major limitation is the higher variability between the data achieved using the monoclonal antibodies obtained with the methods based on hybridoma technologies and currently used in clinical diagnosis. Setting criteria for technical validation of the data acquired may help improve the utility of MFC for MDS diagnostics. The establishment of these criteria requires analysis against a database. The reduction of investigator subjectivity in data analysis is an important advantage of this method.

Introduction

In the absence of phenotypic markers specific to the dysplastic changes occurring in myeloid cells during MDS initiation and progression, a new approach has been proposed in recent years based on the evaluation of the maturation pathways (altered expression of myeloid antigens during the production of mature myeloid cells) or of the abnormal distribution of different cell types within bone marrow (BM) cell compartments1,2.

This article presents a new method for standardized application of MFC in order to detect dysplastic changes in BM myeloid cell compartments related to myelodysplastic syndromes (MDS) or other myeloid hematological diseases. This study also shows the utility of using maturation databases for MFC data analysis.

Standardization of the sample preparation procedure, data acquisition, and analysis using the databases would allow the identification of the most relevant phenotypic abnormalities related to dysplastic changes in BM myeloid cells. Therefore, statistically selected subsets based on well-labeled and well-recognized formats (Automatic Population Separator (APS) diagrams, histograms, and dot plots) are required for developing an analysis strategy that can be used in subsequent analysis rounds. The discovery of robust phenotypic abnormalities in MDS would ease the diagnosis in cases with or without minimal morphological dysplasia and without cytogenetic aberrancies. Identification of discriminatory parameters allowing for the reduction of immunophenotypic panels may simplify the current scores2, permitting their applicability in clinical pathology laboratories.

This method limits the subjective interpretations of cytometry data, as have been signaled in MDS diagnosis3. This step is a prerequisite for the development of automated tools for processing and analyzing flow data4.

MDS comprises a heterogeneous group of clonal hematopoietic stem cell (HSC) disorders in which the spliceosome mutations cooperate with specific epigenetic modifiers to yield the MDS phenotype. It is now known that, along with HSC mutations, other mechanisms are involved in MDS pathophysiology, such as aberrant immune-mediated inflammation and interactions between malignant HSCs and the stromal microenvironment of the BM. However, these mechanisms remain poorly understood. The wide clinical and biological heterogeneity of MDS makes the diagnosis and selection of the optimal therapy a challenge. In the last decade, multiple studies have shown that MFC is often more sensitive in detecting dysplasia2 than morphology, but technical and economic constraints make this technique difficult to standardize, with results often depending on the experience of the interpreter3. In addition, it is unclear how MFC can tip the balance toward MDS in cases with or without minimal morphological dysplasia and in the absence of cytogenetic anomalies, or in borderline cases such as hypocellular MDS, with a low blast count, from other non-clonal BM disorders such as bone marrow failure (i.e., aplastic anemia). It also remains difficult to differentiate borderline cases of MDS with an excess of blasts from acute myeloid leukemia (AML). For all these reasons, the clinical guidelines do not integrate MFC testing into the MDS final diagnosis. In 2011, the US National Comprehensive Cancer Network (NCCN) recommended MFC for the estimation of the percentage of CD34+ cells, detection of paroxysmal nocturnal hemoglobinuria clones, and presence of cytotoxic T-cell clones in hypocellular MDS5. These two latter situations also involve a therapeutic goal because clinical data have shown a good response of these patients to immunosuppressive therapy6. The 2017 NCCN guidelines, citing the International Working Group (IWG) recommendations, listed aberrant immunophenotyping detection by MFC among the co-criteria for MDS diagnosis, but without making any specifications6. In addition, the recently published WHO classification stipulates that MFC findings alone are not sufficient to establish a primary diagnosis of MDS in the absence of conclusive morphological and/or cytogenetic data7. However, MFC can be used as an additional test showing the dysregulation of myeloid cell maturation patterns and quantifying the "distance from normal" for a patient at a specific time in the disease course.

This method is applicable at clinical laboratories interested in the evaluation of dysplasia in BM myeloid cells using MFC immunophenotyping, in order to refine the diagnosis in MDS or other myeloid disorders with dysplastic abnormalities.

Protocol

The protocol listed below has been approved by the "Comité de Protection des Personnes" (Independant Ethics Committee) Sud-Est 1 from University Hospital of Saint-Etienne, France.

1. Cytometer Settings

NOTE: The cytometer settings were performed according to France Flow recommendations, in accordance with EuroFlow Procedure "EuroFlow Standard Operating Protocol (SOP) for Instrument Setup and Compensation (https://www.euroflow.org/usr/pub/protocols.php).

  1. Monthly instrument setup
    1. Turn on the cytometer. Ensure that all fluid levels are appropriate and open Diva 6.1.3. Perform fluidics startup: in the menu bar, select 'Cytometer | Fluidics Startup'. Click 'OK' when prompted. Allow the cytometer to warm up for at least 30 min.
    2. Performance check - CST beads
      NOTE: For this step, prepare 12 75 mm polystyrene tube, CST beads and sheath fluid (see Table of Materials).
      1. Label a 12 x 75 mm2 polystyrene tube 'CST'. Mix the provided bead vial by gentle inversion or very gentle vortexing. Add to the labeled tube: 0.35 mL of Sheath Fluid and 1 drop of CST beads. Vortex the tube gently and proceed to acquisition. Store the tube for up to 8 h at 2-25 °C in the dark if not acquiring immediately.
      2. Perform the performance check: in the menu bar, select 'Cytometer | CST'.
      3. In the 'Setup' tab of the CST module: confirm the Canto II as in the default 4-2H-2V configuration and also confirm that a baseline created using the current lot of CST beads exists for this configuration. If a baseline does not exist, refer to the CST Beads IFU. Confirm that this baseline has not expired: under 'Setup Control', select 'Check Performance' from the drop-down menu.
      4. Check 'Load tube manually' and click 'Run'. Confirm the lot number displayed. Gently vortex the diluted beads prepared above and when prompted, load the diluted beads and click 'OK'.
      5. When the performance check is complete, verify that Cytometer Performance passed. Click 'View Report'. Re-run the performance check if the results did not pass. Save the Report in PDF format with the Performance Tracking Report Date.
    3. Adjust 'Fluorescent PMT voltages' with Rainbow Beads (Table of Materials).
      ​NOTE: The target values are stipulated in the Euroflow Standard Operating Procedure (SOP) entitled "20180302_7th_Peak_Target_Values_Rainbow_Beads". This SOP is available on Euroflow site (www.euroflow.org; in the public area; Protocols tab).
      1. Create a new experiment via 'Monthly Instrument Setup Date | Specimen'.
      2. ', choose the optical parameters and fluorochromes corresponding to the tubes concerned (FITC, PE, PerCPCy5.5, PE-Cy7, APC, APC-H7, V450, V500), and check the desired acquisition parameters (Log, A, H and / or W). Apply current CST settings (right click on 'Cytometer Settings' of the Experiment). Set the threshold for FSC parameter at 10,000.
      3. On the cytometer, turn the compensation off while setting fluorescence PMT voltages for Target MFI setting; for this purpose, go in the 'Inspector', navigate to the 'Compensation' tab. Disable compensation by unchecking 'Enable Compensation' option.
      4. Create a worksheet 'Target MFI' with all necessary dot plots (n = 2; FSC versus SSC, FITC versus PE), histograms (n = 8; one histogram for each fluorescence detector) and statistics showing the reference peak values (MFI and CV) for each fluorescence channel.
      5. Dilute 1 drop of 8-peak Rainbow beads calibration particles in 1 mL of distilled water and vortex before use. Acquire without recording the 8-peak Rainbow beads solution at 'LOW' flow rate. Store the tube for up to 8 h at 2-25 ˚C in the dark if not acquiring immediately.
      6. Gate singlet beads 'Population P1' in the FSC versus SSC bivariate dot plot and the 8th or 7th peak in the FITC versus PE bivariate dot plot (the brightest peak or the next one downwards, as it's stipulated in the Euroflow document entitled "20180302_7th_Peak_Target_Values_Rainbow_Beads") and name this gate Population P2.
      7. Continue the acquisition of the 8-peaks Rainbow bead suspension and adjust PMT voltages in all fluorescence channels to reach target MFI values according the Euroflow document "20180302_7th_Peak_Target_Values_Rainbow_Beads".
      8. Once Target MFI values for the 8th or 7th Peak are reached, record the Target MFI achieved and the corresponding final PMT values. Acquire 5,000 events and record the data.
        NOTE: That PMT values must be used below in step 1.2.3 (Performance Check - Confirmation of PMT Values with Rainbow Beads).
      9. Record these values making a print screen with Worksheet 'Target MFI' and instrument settings and save as .jpg picture.
        NOTE: When a "New" tube is created, sometimes the PMT values vary unexpectedly. For this, a double checking of PMT is essential. Compare each time the PMT values to your notes, double check that 'Target MFI' values and PMT values are correct!
      10. Save the 'Application Settings'. In the Browser, right-click on 'Cytometer Settings'. From the drop-down menu, select 'Application Settings', and save. Click 'OK'. If prompted, click Yes to maintain the threshold values.
        NOTE: Save the Application Settings using the default name. Do NOT rename the settings.
    4. Adjust the 'FCS' and 'SSC voltages' with lysed washed blood (LWB).
      ​NOTE: For this step, 50 µL of a peripheral blood (PB) sample from a healthy volunteer, lysing solution (Table of Materials) and washing buffer are needed.
      1. Pipets 50 µL of PB into a tube. Add 2 mL of freshly diluted lysing solution. Mix gently and incubate for 10 min at RT.
      2. Centrifuge for 5 min at 540 x g.
      3. Aspirate the supernatant without disturbing the cell pellet, leaving approximately 50 µL residual volume in the tube. Mix gently and add 2 mL of filtered wash solution.
      4. Centrifuge for 5 min at 540 x g.
      5. Repeat one more time the steps 1.1.4.3–1.1.4.4.
      6. Add 250 µL of filtered washing buffer and mix gently.
      7. In the Experiment created for Rainbow Beads acquisition, create a new 'Specimen | New Worksheet': draw a bi-parametric SSC-A / FSC-A graph.
      8. Acquire the cells, gate the lymphocytes in a FSC versus SSC bivariate dot plot and adjust FSC and SSC voltages to reach the following mean target values for the gated lymphocyte population: FSC: 55,000 (range 50,000–60,000) and SSC: 13,000 (range 11,000 –15,000).
      9. Acquire and record the data with about 10,000 events. Verify the mean FSC and SSC target values for gated lymphocytes. Readjust FSC and SSC voltage if necessary.
      10. Print screen and store the print of the target channel values that are obtained.
    5. Fluorescence compensation settings.
      NOTE: The single-stained compensation controls must be set after the Target MFI settings and FSC/SSC settings have been established. For this step, a PB from a healthy volunteer, Compensation Particles (Table of Materials), lysing solution and washing buffer are needed. The list of fluorochrome-conjugated antibody reagents used to setup the fluorescence compensation matrices and their reference populations are listed in the Table 1.
      1. Label one tube per reagent to be used in setting up fluorescence compensation (FITC, PE, PerCPCy5.5, APC, V450, V500, PECy7 - CD117, APC-H7 - CD10, APC-H7 - CD14 and APC-H7 - CD71) and a "blank/unstained" tube.
      2. Pipet 50 µL of PB into each tube or 1 drop of "negative"Compensation Particles + 1 drop of "positive" Compensation Particles in the compensation control tubes indicated above in Table 1.
      3. Add appropriate amount of the antibody reagent to the tube. Add filtered washing buffer to reach a final volume of 100 µL per tube and mix gently. Incubate for 15 min at RT, protected from light.
      4. Add 2 mL of freshly diluted lysing solution only in the tubes with the cells and mix gently. Incubate for 10 min at RT, protected from light.
      5. Centrifuge for 5 min at 540 x g.
      6. Aspirate the supernatant without disturbing the cell pellet leaving approximately 50 µL residual volume in each tube. Mix gently. Add 2 mL of filtered washing buffer.
      7. Centrifuge 5 min at 540 x g.
      8. Aspirate the supernatant without disturbing the cell pellet leaving approximately 50 µL residual volume in each tube. Add filtered washing buffer to reach a final volume of 250 µL per tube and mix gently.
      9. Create Compensation Controls.
        1. From the menu bar, select Experiment created for Rainbow Beads acquisition. Create a new 'Specimen | Compensation Setup | Create Compensation Controls'.
        2. In the resulting dialog box, select the 'Include separate unstained control tube/well' checkbox. Create generic (not label-specific) compensation controls for FITC, PE, PerCPCy5.5, APC, HV450, HV500. Create label-specific compensation controls for PE-Cy7- CD117, APC-H7 - CD10, APC-H7 - CD14 and APC-H7 - CD71. Click 'OK'.
        3. In a new worksheet, create a bi-parametric SSC-A / FSC-A graph and draw a gate on lymphocytes (P1) and the histogram corresponding to the fluorochrome that will be detected in each tube and draw a P2 gate for the positive peak. Display the hierarchy (right click on a graph and select 'Show Population Hierarchy') to visualize the number of events in P2, except for the Unstained Control tube.
        4. In the Browser, expand the Compensation Controls specimen.
        5. Vortex the unstained cells, prepared above, for 3–5 s. Install the prepared unstained cells on the cytometer. Adjust the flow rate to 'Medium' and click 'Acquire Data'. In the FSC-A vs SSC-A dot plot, adjust the P1 gate to fully encompass the lymphocyte population. Right-click on the P1 gate. Select 'Apply to all compensation control'.
        6. From the 'Acquisition' Dashboard, click 'Record Data' to acquire 5,000 events. For all the single-color stained control cells, verify that the P2 interval gate encompasses the positive population.
        7. For the PE-Cy7 and APCH7 tubes, add a P3 interval gate to the histogram and ensure that it encompasses the negative population, and that the P2 encompasses the positive population.
        8. Calculate Compensation. From the menu bar, select 'Experiment | Compensation Setup | Calculate Compensation'. Name the compensation matrix: 'Compensations date'. Select 'Link and Save'.
        9. Save the compensation matrix in the Catalog Application Settings: click on 'Cytometer Settings | Application settings | Save', name compensation matrix 'Compensation date' and click 'OK'.
        10. In the Browser, click on 'Cytometer Settings'. In the Inspector, navigate to the 'Compensation' tab. Click Print in the lower right corner.
          NOTE: This information can also be retrieved from the catalog.
        11. Control of the compensation matrix.
          1. Mix in one tube all the single stained tube (APCH7 of choice).
          2. Create a new Experiment named 'Compensation verification date', add new Specimen, click right on the 'Cytometer Settings' of this experiment and choose 'Link | Unlink | Application Setting' saved in the step 1.1.3.10. Acquire 50,000 events from this tube with the new settings.
          3. Apply a new Global Worksheet. Create 1 dot plot FSC-A/SSC-A and draw a gate to visualize the lymphocytes and n x (n-1)/ 2 other plots focused on the lymphocytes gate to visualize two-by-two parameters.
  2. Daily Instrument setup
    1. Turn on the cytometer. Ensure that all fluid levels are appropriate and open Diva 6.1.3. Perform fluidics startup: in the menu bar, select 'Cytometer | Fluidics Startup'. Click 'OK' when prompted. Allow the cytometer to warm up for at least 30 min.
    2. Performance Check - CST Beads: repeat the steps 1.1.2.1–1.1.2.5.
    3. Performance Check - Confirmation of PMT Values with Rainbow Beads.
      1. Label a polystyrene tube as 'Rainbow Beads' and check that the lot number is the one in use. Thoroughly mix the Rainbow Bead vial. Prepare the Rainbow Beads, add 1 drop of Rainbow Beads to 1 mL of deionized or distilled water. Protect from light.
        NOTE: Proceed to acquisition or store the tube at 2-8 ˚C until acquisition.
      2. Create a new Experiment: 'Rainbow Beads Date'.
      3. Link the compensations: right click on 'Cytometer Settings', select 'Link Setup', select the appropriate compensation matrix created in step 1.1.5.9.9 and select 'Overwrite'.
      4. Unlink compensation: right click on 'Cytometer Settings', select 'Unlink from the previously linked setup' and click 'OK'.
      5. Apply 'Application Settings': right click on 'Cytometer Settings', select 'Application Settings', apply the setting created in step 1.1.3.10 during the Monthly Setup and select 'Keep the compensation value'.
      6. Deselect 'Enable compensation'.
      7. Create a new Specimen in the Experiment with worksheet template for Rainbow Beads. Acquire the tube in 'LOW' acquisition.
      8. During the beads acquisition, adjust the P1 gate to include only the singlet bead population. Adjust the P2 gate on the FITC-A / PE-A dot plot to include only the singlet bead population. Record 10,000 events.
      9. Check that the MFI and the CV values obtained for P2 population are in the pre-defined targets of the protocol. Otherwise, wash the cytometer and start the operation again. Save the report as PDF format.

2. BM Sample Preparation

NOTE: Perform the cell washing protocol just before the staining procedure.

  1. Pipette 600 µL of primary sample into a 15 mL centrifuge tube.
  2. Add 10 mL of washing buffer (PBS + 0.5% BSA [>98% pure BSA] + 0.09% NaN3 filtered solution, pH 7.4). Mix the cell suspension well using a pipette.
  3. Centrifuge for 5 min at 540 x g (wash 1). Discard the supernatant without disturbing the cell pellet.
  4. Repeat steps 2.2–2.3 (wash 2).
  5. Suspend the cell pellet in 400 µL of washing buffer.
  6. Staining of backbone markers. Transfer the entire volume of the backbone antibodies to a polypropylene tube for FACS analysis, identified with the patient data and the "backbone". Add 350 µL of washed sample (the volume of the washed sample required to fill all the tubes on the panel). Mix well using a pipette.
    NOTE: Calculate the total volume of backbone antibodies for surface membrane staining (as shown in Table 2).
  7. Pipette equal amounts of the sample-backbone mix into 3 polypropylene tubes for FACS analysis, identified with the patient data and "tube number 1" to "tube number 3". If necessary, use washing buffer to reach a final volume of 200 µL per tube.
    CAUTION: Be careful not to leave any trace of the sample on the walls of the tubes; otherwise, these cells will not be stained. If necessary, vortex the cells and centrifuge the tube.
  8. In each tube, add the appropriate volume of antibodies directed against cell surface markers (except for the backbone markers), as specified in Table 2. Mix well using a pipette. Incubate for 30 min at RT protected from light.
  9. Add 2 mL of lysing solution. Mix well using a pipette. Incubate for 10 min at RT protected from light.
  10. Centrifuge for 5 min at 540 x g. Discard the supernatant without disturbing the cell pellet, leaving approximately 50 µL residual volume in each tube. Mix well using a pipette.
  11. Add 2 mL of washing buffer to the cell pellet. Mix well using a pipette.
  12. Repeat steps 2.10–2.11 (wash 2).
  13. Centrifuge for 5 min at 540 x g. Discard the supernatant without disturbing the cell pellet and re-suspend the cell pellet in 200 µL of PBS. Mix well using a pipette.
  14. Acquire the cells, preferably, immediately after staining or store at 4 °C, protected from light, for no more than 1 h until measured in the flow cytometer.

3. Data Acquisition

  1. Open a New Experiment in Diva software and rename it according to the name, type of sample and date.
  2. Create a new Specimen containing 3 tubes. Specify in the Experiment Layout the antibodies used in each tube.
  3. Click right on the 'Cytometer Settings', choose 'Application Settings' and apply the values obtained in Monthly Setup (step 1.1.3.10).
  4. Open a new Global Worksheet and create the dot plots: SSC-A/ FSC-A, SSC-A/ CD45-HV500-A, SSC-A/ FITC-A, SSC-A/ PE-A, SSC-A/ CD34-PerCP-Cy5.5, SSC-A/ CD117-PECy7-A, SSC-A/ APC-A, SSC-A/ APCH7-A, SSC-A/ HLA-DR-HV450-A. In the SSC-A/FSC-A dot plot, create a gate to select singlet cells. In the SSC-A/CD45-BV500-A dot plot, create gates to select 4 populations: granulocytes, monocytes, blasts, and lymphocytes. Project these populations in the dot plots created previously.
  5. Create a new Global Worksheet for compensation control as described in step 1.1.5.9.11.3.
  6. Acquire the tube in 'MEDIUM' acquisition and record 500,000 events/tube. After technical validation (evaluation of compensation and the proper staining), export the data as FCS3.0 files.

4. Data Analysis

NOTE: To construct the normal BM databases were used files from healthy donors and from individuals without any evidence for a hematopoietic disease as follows 11 from 18 files for the Neutrophils_NM database, 10 from 18 files for Monocytes_NM database and 14 from 18 files for NRC_NM database. The files discarded showed various technical problems, as presented in the Representative Results section. The files were individually analyzed using the Infinicyt software (Table of Materials), conforming to the various strategies depicted in Figure 1A(1-3) for neutrophil lineage (Profile Neutrophils_Maturation.inp), Figure 2A for monocyte lineage (Profile Monocytes_Maturation.inp), and Figure 3A(1-2) for erythroid cell lineage (Profile NRC_Maturation.inp).

  1. Strategy of analysis for neutrophils - Neutrophils_NM database construction
    1. Identify CD34+ neutrophil-committed blasts using an intersection of seven gates, allowing the selection of CD34+ CD117+ HLADR+low CD10- CD13+ CD11b- events (Figure 1A.1). Assign these events to the 'Neutrophil' tab in the Population Hierarchy Tree and thereafter uncheck this tab in order to remove these cells (depicted in blue) from the display of the remaining events (gray).
    2. Isolate the CD117+ CD34- CD13+ CD11b- HLADR+low neutrophil precursors using an intersection of six gates as depicted in Figure 1A(2) and assign them to the 'Neutrophil' tab.
    3. Identify more mature neutrophils using an intersection of four gates, allowing for the discrimination of CD45dim SSCint-hi CD117- HLADR-cells and their assignment to the 'Neutrophil' tab.
    4. Uncheck the remaining events, keeping only the neutrophils visible, then export this population by clicking 'File | Export' and verifying that all the required parameters are checked and save the data as FCS files.
    5. In a merged file consisting of all exported FCS files, perform a quality check by evaluating the intensity of expression of markers for each subpopulation. Using APS plots with medians for each file and SD curves for each subpopulation shown, remove the cases outside the 2SD curves (see details in the Representative Results section) (Figure 1B).
    6. In the resulting composed file with "Neutrophils" visible, draw the Maturation Pathway on an APS diagram (Figure 1C left) and save as a .cyt file.
      NOTE: A comparison Maturation Diagram allows the visualization of all parameters from all files included in the Neutrophils_NM database represented against the normalized database. The diagram presented in Figure 2C, right side, shows that all files included in the Neutrophils_NM database (n=11) fit in 2 SD compared with median of the group.
  2. Strategy of analysis for monocytes - Monocytes_NM database construction
    1. Identify the monocytic lineage cells (CD117+/- CD64+hi HLADR+hi) using an intersection of four gates (Figure 2A). Assign these events to the 'Monocytic' tab in the Population Hierarchy Tree.
    2. Uncheck the remaining events, keeping only the monocytic cells visible, then export this population by clicking 'File | Export' and verifying that all the required parameters are checked and save the data as FCS files.
    3. In a merged file consisting of all exported FCS files, perform a quality check by evaluating the intensity of expression of markers for each subpopulation, then remove the cases outside the 2SD curves (details in Representative Results section) (Figure 2B).
    4. In the resulting file with "Monocytic" cells visible, draw the Maturation Pathway on the APS diagram (Figure 2C left) and save this as a .cyt file.
      ​NOTE: A comparison Maturation Diagram allows the visualization of all parameters from all files included in the Monocytes_NM database represented against the normalized database. The diagram presented in Figure 2C, right side, shows that all files included in the Monocytes_NM database (n=10) fit in 2 SD compared with the median of the group.
  3. Strategy of analysis for nucleated red cells (NRCs) - NRC_NM database construction
    1. Identify CD34+ erythroid committed blasts using an intersection of seven gates that allow the selection of CD34+ CD117+ HLADR+low CD105+ CD33- CD36+ CD71+ events (Figure 3A(1)). Assign these events to the "NRC" tab in the Population Hierarchy Tree and then uncheck this tab in order to remove these cells (depicted in red) from the display of the remaining events (gray).
    2. Identify more mature NRCs using an intersection of four gates that allow the discrimination of CD45-/+dim SSClow CD36+hi CD71+hi CD105+/-cells. Assign these events to the "NRC" tab (Figure 3A(2)). The platelets (CD36+hi SSClow cells) must be removed from the NRC population (Figure 3A(2)).
    3. Uncheck the remaining events, keeping only the NRC cells visible, then export this population by clicking 'File | Export' and verifying that all the required parameters are checked and save the data as FCS files.
    4. In a merged file consisting of all exported FCS files, perform a quality check by evaluating the intensity of expression of markers for each subpopulation, followed by the removal of the cases outside the 2SD curves (see details in Representative Results section) (Figure 3B).
    5. In the resulting file with "NRC" cells visible, draw the Maturation Pathway on the APS diagram (Figure 3C, left) and save this as a .cyt file.
      ​NOTE: A comparison Maturation Diagram allows the visualization of all parameters from all files included in the NRC_NM database represented against the normalized database. The diagram presented in Figure 3C, right side, shows that all files included in the NRC_NM database (n = 14) fit in 2 SD compared with median of the group.
  4. Evaluation of maturation in BM myeloid compartments using the Maturation Databases
    1. Open the .cyt file corresponding to the lineage of interest (i.e., Neutrophils_NM_GMFF.cyt for neutrophil lineage, Monocytes_NM_GMFF.cyt for monocytic lineage, and NRCs_NM_GMFF.cyt for erythroid lineage).
    2. Right-click on 'Maturation' tab below the tab corresponding to the lineage of interest ('Neutrophils | Monocytic| NRC') and save the Maturation to Maturation Database.
    3. Open a new FCS file and perform analysis as explained previously (step 4.1.1–4.1.3 for Neutrophils, step 4.2.1 for Monocytic cells, and step 4.3.1–4.3.2 for NRC).
    4. Draw the maturation pathway for the population of interest.
    5. Open the corresponding database in the 'Tools' tab (Database Analysis) and compare the population to be analyzed with the corresponding Maturation Database. Check the data for compatibility with the available database: complete compatibility (green triangle); partial compatibility, in most cases discrepancies in the name of the parameters (yellow triangle); and incompatibility (red triangle).
    6. If the data are compatibles or partial compatibles, the software creates the 'Normalized Maturation Differences' diagram. To visualize the 'Parameter Band Maturation Differences', open a new diagram in 'Diagram' tab, click 'Maturation' and choose how many parameters to be displayed, click 'OK' and the diagram appear. With right click in the diagram; changes can be made in Data Visualization, Database Visualization and Maturation Diagram Visualization.
    7. To visualize the significance of the differences between the new file and data included in the database, configure a zoom (right-click on 'Normalized Maturation Differences' and apply 'Zoom').

Results

The 54 BM samples harvested in K-EDTA anticoagulant were included in the study. The MFC data were analyzed in the absence of any information about the patients. Retrospective study showed that the BM samples were from 7 healthy donors (5 males and 2 females with a median age of 47.4 [35-48], 11 individuals with no evidence of a hematopoietic disease (8 males and 3 females with a median age of 57.9 [35-72]) and 36 cases with various pathological conditions: 1 case with anemia and low creat...

Discussion

The quality of BM aspirate could impact on the final results. The hemodilution of the BM aspirate could distort the distribution of cells in different stages of maturation due to the absence of progenitors or precursors cells. Probably employing a bulk lysing method may help in normalization of BM aspirates for hemodilution in flow cytometric analyses. In addition, the critical steps for the evaluation of BM myeloid dysplasia by flow-cytometry are the sample processing and staining, data acquisition, and interpretation

Disclosures

The authors declare that they have no competing financial interests. The Flow-Cytometry Department, Hematology Laboratory at the University Hospital of Saint-Etienne is a member of EuroFlow Consortium.

Acknowledgements

The antibodies used in this study were provided by BD Biosciences. The authors would like to thank their colleague, Dr. Pascale Flandrin-Gresta, from the Department of Molecular Biology, Hematology laboratory, University Hospital of Saint-Etienne, France, who provided expertise for interpretation of NGS data for the second MDS case. The authors are thankful for the clinician hematologists for their interest and involvement in this study and for the patients and healthy donors for their agreement to participate in this study. The authors would also like to thank the "Les Amis de Rémi" Foundation for financial support for publication.

Materials

NameCompanyCatalog NumberComments
BD FACSCanto II flow-cytometerBD Biosciences, CA, USASN: V338963013363-laser, 4-2-2 configuration, Filters and mirrors details: https://www.bdbiosciences.com/documents/BD_FACSCanto_II_FilterGuide.pdf
Awel C48-R CentrifugeAWEL Industries, FRSN: 910120016; Model No: 320002001low speed centrifuges; capacity 60 FACS tubes
Pipetts of 10µl and 200µl
Pasteur pipettes
15 mL Falcon tubes
polypropylene tube for FACS
Mouse Anti-Human HLA-DRBD Biosciences, CA, USA655874clone L243
Mouse BALB/c IgG2a, κ
Fluorochrome Horizon V450
(Ex max 404 nm/
Em max 448 nm)
Mouse Anti-Human CD45BD Biosciences, CA, USA560777clone HI30
Mouse IgG1, κ
Fluorochrome Horizon V500 (Ex max 415 nm/
Em max 500 nm)
Mouse Anti-Human CD16BD Biosciences, CA, USA656146clone CLB/fcGran1 Mouse BALB/c IgG2a, κ
Fluorochrome FITC
(Ex max 494 nm/
Em max 520 nm)
Mouse Anti-Human CD13BD Biosciences, CA, USA347406clone L138
Mouse BALB/c X C57BL/6 IgG1, κ
Fluorochrome PE
(Ex max 496 nm/
Em max 578 nm)
Mouse Anti-Human CD34BD Biosciences, CA, USA347222clone 8G12
Mouse BALB/c IgG1, κ
Fluorochrome PerCP-Cy5.5
(Ex max 482 nm/
Em max 678 nm)
Mouse Anti-Human CD117BD Biosciences, CA, USA339217clone 104D2
Mouse BALB/c IgG1
Fluorochrome PE-Cy7
(Ex max 496 nm/
Em max 785 nm)
Mouse Anti-Human CD11bBD Biosciences, CA, USA333143clone D12
Mouse BALB/c IgG2a, κ
D12, Fluorochrome APC
(Ex max 650 nm/
Em max 660nm
Mouse Anti-Human CD10BD Biosciences, CA, USA646783clone HI10A
Mouse BALB/c IgG1, κ
Fluorochrome APC-H7
(Ex max 496 nm/
Em max 785nm)
Mouse Anti-Human CD35BD Biosciences, CA, USA555452clone E11
Mouse IgG1, κ
Fluorochrome FITC
(Ex max 494 nm/
Em max 520 nm)
Mouse Anti-Human CD64BD Biosciences, CA, USA644385clone 10.1
Mouse BALB/c IgG1, κ
Fluorochrome PE
(Ex max 496 nm/
Em max 578 nm)
Mouse Anti-Human CD300eImmunostepIREM2A-T100clone UP-H2
Mouse BALB/c IgG1, k
Fluorochrome APC
(Ex max 496 nm/
Em max 578 nm)
Mouse Anti-Human CD14BD Biosciences, CA, USA641394clone MoP9
Mouse BALB/c IgG2b, κ
Fluorochrome APC-H7
(Ex max 496 nm/
Em max 785nm)
Mouse Anti-Human CD36BD Biosciences, CA, USA656151clone CLB-IVC7
Mouse IgG1, κ
Fluorochrome FITC
(Ex max 494 nm/
Em max 520 nm)
Mouse Anti-Human CD105BD Biosciences, CA, USA560839clone 266
Mouse BALB/c IgG1, κ
Fluorochrome PE
(Ex max 496 nm/
Em max 578 nm)
Mouse Anti-Human CD33345800clone P67.6
Mouse BALB/c IgG1, κ
Fluorochrome APC
(Ex max 496 nm/
Em max 578 nm)
Mouse Anti-Human CD71BD Biosciences, CA, USA655408clone M-A712
Mouse BALB/c IgG2a, κ
Fluorochrome APC-H7
(Ex max 496 nm/
Em max 785nm)
Lysing Solution 10X Concentrate (IVD)BD Biosciences, CA, USA349202
FACSFlow Sheath FluidBD Biosciences, CA, USA342003
FACSDiva CS&T IVD beadsBD Biosciences, CA, USA656046
RAINBOW CALIBRATION PARTICLES, 8 PEAKSCytognos, Salamanca, SpainSPH-RCP-30-5Alots EAB01, EAC01, EAD05, EAE01, EAF01, EAG01, EAH01, EAI01, EAJ01, EAK01
Compensation Particles Multicolor CompBeads(CE/IVD)BD Biosciences, CA, USAref. #51-90-9001229 + #51-90-9001291
Diva software versions 6.1.2 and 6.1.3BD Biosciences, CA, USA
Phosphate buffered saline tabletsR&D Systems, Minneapolis, USA5564
Bovine serum albumin (BSA)Sigma-Aldrich, FranceA9647
Sodium azide 99%Sigma-Aldrich, France199931
Infinicyt software version 1.8.0.eCytognos, Salamanca, Spain

References

  1. Orfao, A., Ortuño, F., de Santiago, M., Lopez, A., San Miguel, J. Immunophenotyping of Acute Leukemias and Myelodysplastic Syndromes. Cytometry Part A. 58, 62-71 (2004).
  2. Porwit, A., 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 (IMDSFlow). Leukemia. 28 (9), 1793-1798 (2014).
  3. Westers, M. T., et al. Implementation of flow cytometry in the diagnostic work-up of myelodysplastic syndromes in a multicenter approach: Report from the Dutch Working Party on Flow Cytometry in MDS. Leukemia Research. 36, 422-430 (2012).
  4. Meehan, S., et al. AutoGate: automating analysis of flow cytometry data. Immunologic Research. 58, 218-223 (2014).
  5. Greenberg, P. L., et al. NCCN Clinical Practice Guidelines in Oncology: myelodysplastic syndromes. Journal of the National Comprehensive Cancer Network. 9, 30-56 (2011).
  6. Greenberg, P. L., et al. Myelodysplastic Syndromes, Version 2.2017, Clinical Practice Guidelines in Oncology. Journal of the National Comprehensive Cancer Network. 15, (2017).
  7. Swerdlow, S. H., et al. . WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. Revised 4th Edition. (2), 86-128 (2017).
  8. . https://lists.purdue.edu/pipermail/cytometry/2009-March/036889.html Available from: https://lists.purdue.edu/pipermail/cytometry/2009-March/036889.html (2018)
  9. . . Composition of EuroFlow panels and technical information on reagents Version 1.5. , (2017).
  10. . . EuroFlow Standard Operating Procedure (SOP) for sample preparation and staining Version 1.2.1. , (2015).
  11. Kalina, T., et al. EuroFlow standardization of flow cytometer instrument settings and immunophenotyping protocols. Leukemia. 26, 1986-2010 (2012).
  12. van Dongen, J. J. M., et al. EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia. 26, 1908-1975 (2012).
  13. Matarraz, S. Introduction to the Diagnosis and Classification of Monocytic-Lineage Leukemias by Flow Cytometry. Cytometry Part B (Clinical Cytometry). 92 (3), 218-227 (2015).
  14. Westers, M. T. Immunophenotypic analysis of erythroid dysplasia in myelodysplastic syndromes. A report from the IMDSFlow working group). Haematologica. 102, 308-319 (2017).
  15. Shen, Q., et al. Flow cytometry immunophenotypic findings in chronic myelomonocytic leukemia and its utility in monitoring treatment response. European Journal of Haematology. 95, 168-176 (2015).

Reprints and Permissions

Request permission to reuse the text or figures of this JoVE article

Request Permission

Explore More Articles

Flow CytometryBone MarrowMyeloid Cell MaturationMyelodysplasiaHematological DiseasesCell Surface MarkersCell LineagesQuantificationData AnalysisFlow Cytometer

This article has been published

Video Coming Soon

JoVE Logo

Privacy

Terms of Use

Policies

Research

Education

ABOUT JoVE

Copyright © 2025 MyJoVE Corporation. All rights reserved