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. 2025 Jan 1;17(1):e2025002.
doi: 10.4084/MJHID.2025.002. eCollection 2025.

Integration of CD200, CD43 and ROR1 in Multiparameter Flow Cytometry (MFC) Routine Panels for the Differential Diagnosis of B-cell lymphoproliferative Disorders (B-LPDs)

Affiliations

Integration of CD200, CD43 and ROR1 in Multiparameter Flow Cytometry (MFC) Routine Panels for the Differential Diagnosis of B-cell lymphoproliferative Disorders (B-LPDs)

Alessandro Laganà et al. Mediterr J Hematol Infect Dis. .

Abstract

Background: Clonal mature B-cell lymphoproliferative disorders (B-LPDs) are a heterogeneous group of neoplasia characterized by the proliferation of mature B lymphocytes in the peripheral blood, bone marrow and/or lymphoid tissues. B-LPDs classification into different subtypes and their diagnosis is based on a multiparametric approach. However, accurate diagnosis may be challenging, especially in cases of ambiguous interpretation. Multiparameter flow cytometry (MFC) represents an extensively used technique to detect the presence of different cellular lines in immunology and hematology. MFC results provide an essential contribution to the B-LPDs diagnostic process, even more so considering that panels are constantly integrating novel markers to improve diagnostic accuracy.

Objectives: The aim was to evaluate the contributing role of MFC routinary studies by analyzing the expression and the mean fluorescence intensity (MFI) of CD200, ROR1, and CD43 in various B-LPDs to evaluate their usefulness in the differential diagnosis of these diseases.

Methods: We retrospectively evaluated 2615 consecutive cases of newly collected samples (mostly from patients with lymphocytosis) analyzed by MFC carried out in the B-LPD diagnostic process referred to the Division of Hematology of the Sapienza University of Rome. We compared the results of CD200, ROR1, and CD43 expression percentage and their MFI between different subtypes of B-LPDs.

Results: In chronic lymphocytic leukemia (CLL), CD200, ROR1, and CD43 were always expressed with bright intensity. CLL samples presented high CD200 expression and MFI [CD200%, mean: 100 (range, 24-100); positivity rate: 100%; MFI, median = 125 (range, 10-1200)] statistically higher than mantle cell lymphoma (MCL) (p<0.001), which is usually negative for CD200, and variant hairy cell leukemia (vHCL, according to 2022 ICC) (p<0.001), but comparable with classic HCL (cHCL) (p>0.9). ROR1 resulted expressed in all CLL [ROR1%, mean: 100 (range, 52-100), positivity rate: 100%; MFI, median=50 (range, 10-202)] and MCL cases with comparable MFI (p>0.9). CD43 expression and MFI were significantly higher in CLL [CD43%, mean 99 (range, 59-100); positivity rate: 100%; MFI, median = 130 (range, 41-980)] than in MCL, vHCL, cHCL, and all the others mature B-cell neoplasia (p<0.001). CD200 and CD43 expression and MFI were significantly higher in cHCL compared to vHCL. Among the other mature B-cell neoplasia, CD200 was variably expressed in follicular lymphoma (FL), marginal zone lymphoma (MZL), diffuse large B-cell lymphoma (DLBCL), and lymphoplasmacytic lymphoma (LPL). ROR1 and CD43 presented a very low expression percentage in this latter group, being mostly negative. Persistent polyclonal B-cell lymphocytosis (PPBL) resulted in uniformly positive for CD200 and negative for ROR1 and CD43.

Conclusions: Our data suggest that evaluating CD200, ROR1, and CD43 antigens and their intensity of expression, along with commonly used markers in MFC routine panels for B-LPDs, might be extremely useful for prompt diagnostic evaluation in the differential diagnosis of these diseases.

Keywords: Antibody panels for standardized flow cytometry; B-cell lymphoproliferative disorders (B-LPDs); CD200; CD43; Multiparameter flow cytometry (MFC); ROR1; Routine multiparameter flow cytometry panel.

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Conflict of interest statement

Competing interests: The authors declare no conflict of Interest.

Figures

Figure 1
Figure 1
Representative plots of the flow gating strategies used in the detection of healthy cases and in the differential diagnosis of B-LPDs subtype. B cells were gated within the total CD45+ leukocyte population, then CD20+ cells were identified. Examples of differential CD200, ROR1 and CD43 expression in CLL, MCL, MZL clonal B cells and comparison with healthy cohort polyclonal B lymphocytes. B lymphocytes are depicted in red, T lymphocytes are depicted in blue, residual granulocytes are in green, and residual monocytes are in yellow. B-LPDs = B-Cell Lymphoproliferative Disorders; CLL = Chronic lymphocytic Leukemia; MCL = Mantle Cell Lymphoma; MZL = Marginal Zone Lymphoma.
Figure 2
Figure 2
Cohort distribution flowchart. Patient flowchart reports the total number of patients included in a preliminary evaluation and the number of patients excluded from the analysis due to selection criteria. Of the 436 patients excluded, 244 exhibited a clonal immunophenotype consistent with mature B-cell lymphoma, but a histological exam was not available; 192 had histological results showing a mature B-cell lymphoma not further classified (NOS). IF, Immunophenotype analysis; DLBCL, Diffuse Large B-Cell Lymphoma; PPBL, Persistent Polyclonal B-cells Expansion; cHCL, Classical Hairy Cell Leukemia; vHCL, Variant Hairy Cell Leukemia; CLL, Chronic Lymphocytic Leukemia; MCL, Mantle Cell Lymphoma; FL, Follicular Lymphoma; MZL, Marginal Zone Lymphoma; non-CLL/SLL-type MBL, non-Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma-type Monoclonal B-cell Lymphocytosis; CLL/SLL type-MBL, Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma type-Monoclonal B-cell Lymphocytosis; LPL, Lymphoplasmacytic Lymphoma; SLL/CLL, Small Lymphocytic Lymphoma; BL, Burkitt lymphoma.
Figure 3
Figure 3
Set of boxplots displaying the expression levels of CD200, ROR1, and CD43 in the different B-LPDs. The x-axis across all plots represents the various B-LPDs. The top row of boxplots shows the percentage expression of CD200, ROR1, and CD43, while the bottom row shows their Mean Fluorescence Intensity (MFI). Each boxplot illustrates the range, median, and outliers of these markers within the different disease groups, providing comparative insights into the expression levels of these biomarkers across the various B-LPDs.

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