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CC BY-NC-ND 4.0 · J Lab Physicians 2023; 15(03): 392-398
DOI: 10.1055/s-0043-1761204
Original Article

Immunophenotypic Profile of Multiple Myeloma: A Tertiary Care Centre Experience

Asish Rath 
1   Department of Hematology, All India Institute of Medical Sciences, New Delhi, India
,
Tribikram Panda
1   Department of Hematology, All India Institute of Medical Sciences, New Delhi, India
,
Jasmita Dass
1   Department of Hematology, All India Institute of Medical Sciences, New Delhi, India
,
Tulika Seth
1   Department of Hematology, All India Institute of Medical Sciences, New Delhi, India
,
Manoranjan Mahapatra
1   Department of Hematology, All India Institute of Medical Sciences, New Delhi, India
,
Seema Tyagi
1   Department of Hematology, All India Institute of Medical Sciences, New Delhi, India
› Author Affiliations Funding None.
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Abstract

Background Immunophenotyping and enumeration of plasma cells (PCs) by flow cytometry are deemed to be prognostically significant. However, PCs enumeration by flow cytometry is challenging owing to discrepancy with morphology and PCs loss during sample processing. Enumeration and differentiation of abnormal plasma cells (APCs) and normal plasma cells (NPCs) is difficult because abnormal antigen expression can be seen in subsets of NPCs. This is particularly true when a limited panel of antibodies are relied upon.

Aims and purpose To study the immunophenotypic profile of newly diagnosed multiple myeloma (MM) cases by flow cytometry and evaluate the sensitivities and specificities of individual antigens and combinations.

Methods We studied immunophenotype of PCs in newly diagnosed MM cases (n = 48) and control cases (n = 10) by a 6-color, 3-tube flow cytometry panel. The sensitivities and specificities of antigens in MM were evaluated and compared with control cases.

Results Majority of MM cases (n = 43) had < 3% NPCs. CD19 was the most sensitive (100%) and CD81 was the most specific marker (100%) for differentiating APCs from NPCs. CD38 MFI came out as a useful marker for APCs identification. In combination, CD19 and CD81 had a higher sensitivity and specificity to detect APCs.

Conclusion NPCs may show aberrant antigen expression. A combination of multiple markers including CD81 and CD38 MFI should be used for accurate APC detection.

Keywords

multiple myeloma - immunophenotype - flow cytometry - CD38MFI

Ethical Standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.


Ethical Approval

The study is approved by institute ethics committee with reference number IECPG-293/29.05.2019.


Informed Consent

Informed consent was obtained from all individual participants included in the study.


Publication Consent

Consent for publication was obtained for every individual person's data included in the study.


Data Availability

The datasets generated and analyzed during this study are available from the corresponding author on reasonable request.


Authors Contributions

A.R. processed the samples, analyzed the flow cytometry data, and wrote the manuscript. S.T. conceptualized and designed the study, analyzed the data, and wrote the manuscript. J.D. reviewed the morphology and analyzed the data. T.S. and M.M. reviewed the data and provided the clinical information.




Publication History

Article published online:
30 January 2023

© 2023. The Indian Association of Laboratory Physicians. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • References

  • 1 McKenna R, Kyle R, Kuehl W. Plasma cell neoplasms. In: WHO classification of tumours of haematopoietic and lymphoid tissues. revised 4th ed. 2017 Lyon; IACR:241–58
    Google Scholar
  • 2 Rajkumar SV, Dimopoulos MA, Palumbo A. et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol 2014; 15 (12) e538-e548
    CrossrefPubMedGoogle Scholar
  • 3 Jelinek T, Bezdekova R, Zatopkova M. et al. Current applications of multiparameter flow cytometry in plasma cell disorders. Blood Cancer J 2017; 7 (10) e617-e617
    CrossrefPubMedGoogle Scholar
  • 4 San Miguel JF, Almeida J, Mateo G. et al. Immunophenotypic evaluation of the plasma cell compartment in multiple myeloma: a tool for comparing the efficacy of different treatment strategies and predicting outcome. Blood 2002; 99 (05) 1853-1856
    CrossrefPubMedGoogle Scholar
  • 5 Sezer O, Heider U, Zavrski I, Possinger K. Differentiation of monoclonal gammopathy of undetermined significance and multiple myeloma using flow cytometric characteristics of plasma cells. Haematologica 2001; 86 (08) 837-843
    PubMedGoogle Scholar
  • 6 Pérez-Persona E, Vidriales M-B, Mateo G. et al. New criteria to identify risk of progression in monoclonal gammopathy of uncertain significance and smoldering multiple myeloma based on multiparameter flow cytometry analysis of bone marrow plasma cells. Blood 2007; 110 (07) 2586-2592
    CrossrefPubMedGoogle Scholar
  • 7 Paiva B, Vidriales M-B, Mateo G. et al; GEM (Grupo Español de MM)/PETHEMA (Programa para el Estudio de la Terapéutica en Hemopatías Malignas) Cooperative Study Groups. The persistence of immunophenotypically normal residual bone marrow plasma cells at diagnosis identifies a good prognostic subgroup of symptomatic multiple myeloma patients. Blood 2009; 114 (20) 4369-4372
    CrossrefPubMedGoogle Scholar
  • 8 Kumar S, Kimlinger T, Morice W. Immunophenotyping in multiple myeloma and related plasma cell disorders. Best Pract Res Clin Haematol 2010; 23 (03) 433-451
    CrossrefPubMedGoogle Scholar
  • 9 Tembhare PR, Yuan CM, Venzon D. et al. Flow cytometric differentiation of abnormal and normal plasma cells in the bone marrow in patients with multiple myeloma and its precursor diseases. Leuk Res 2014; 38 (03) 371-376
    CrossrefPubMedGoogle Scholar
  • 10 Perez-Andres M, Santiago M, Almeida J, Mateo G, Porwit-Macdonald A, Bjorklund E, Valet G, Kraan J, Gratama J, D'Hautcourt JL, Merle-Beral H. Immunophenotypic approach to the identification and Journal of Biological Regulators and Homeostatic Agents. 2004
    PubMedGoogle Scholar
  • 11 Rawstron AC, Orfao A, Beksac M. et al; European Myeloma Network. Report of the European Myeloma Network on multiparametric flow cytometry in multiple myeloma and related disorders. Haematologica 2008; 93 (03) 431-438
    CrossrefPubMedGoogle Scholar
  • 12 Nadav L, Katz BZ, Baron S. et al. Diverse niches within multiple myeloma bone marrow aspirates affect plasma cell enumeration. Br J Haematol 2006; 133 (05) 530-532
    CrossrefPubMedGoogle Scholar
  • 13 Manasanch EE, Salem DA, Yuan CM. et al. Flow cytometric sensitivity and characteristics of plasma cells in patients with multiple myeloma or its precursor disease: influence of biopsy site and anticoagulation method. Leuk Lymphoma 2015; 56 (05) 1416-1424
    CrossrefPubMedGoogle Scholar
  • 14 Lu J, Li C, Huang Y, Zhang J. Comparison of cell morphology and flow cytometry in the diagnosis of multiple myeloma. J Cancer Ther 2020; 11 (11) 731-737
    CrossrefGoogle Scholar
  • 15 Bacher U, Haferlach T, Kern W, Alpermann T, Schnittger S, Haferlach C. Correlation of cytomorphology, immunophenotyping, and interphase fluorescence in situ hybridization in 381 patients with monoclonal gammopathy of undetermined significance and 301 patients with plasma cell myeloma. Cancer Genet Cytogenet 2010; 203 (02) 169-175
    CrossrefPubMedGoogle Scholar
  • 16 Tran DN, Smith SABC, Brown DA. et al. Polychromatic flow cytometry is more sensitive than microscopy in detecting small monoclonal plasma cell populations. Cytometry B Clin Cytom 2017; 92 (02) 136-144
    CrossrefPubMedGoogle Scholar
  • 17 Kalina T, Flores-Montero J, van der Velden VHJ. et al; EuroFlow Consortium (EU-FP6, LSHB-CT-2006-018708). EuroFlow standardization of flow cytometer instrument settings and immunophenotyping protocols. Leukemia 2012; 26 (09) 1986-2010
    CrossrefPubMedGoogle Scholar
  • 18 Chatterjee G, Gujral S, Subramanian PG, Tembhare PR. Clinical relevance of multicolour flow cytometry in plasma cell disorders. Indian J Hematol Blood Transfus 2017; 33 (03) 303-315
    CrossrefPubMedGoogle Scholar
  • 19 Ocqueteau M, Orfao A, Almeida J. et al. Immunophenotypic characterization of plasma cells from monoclonal gammopathy of undetermined significance patients. Implications for the differential diagnosis between MGUS and multiple myeloma. Am J Pathol 1998; 152 (06) 1655-1665
    PubMedGoogle Scholar
  • 20 Paiva B, Almeida J, Pérez-Andrés M. et al. Utility of flow cytometry immunophenotyping in multiple myeloma and other clonal plasma cell-related disorders. Cytometry B Clin Cytom 2010; 78 (04) 239-252
    CrossrefPubMedGoogle Scholar
  • 21 Peceliunas V, Janiulioniene A, Matuzeviciene R, Griskevicius L. Six color flow cytometry detects plasma cells expressing aberrant immunophenotype in bone marrow of healthy donors. Cytometry B Clin Cytom 2011; 80 (05) 318-323
    CrossrefPubMedGoogle Scholar
  • 22 Pojero F, Flores-Montero J, Sanoja L. et al; EuroFlow group. Utility of CD54, CD229, and CD319 for the identification of plasma cells in patients with clonal plasma cell diseases. Cytometry B Clin Cytom 2016; 90 (01) 91-100
    CrossrefPubMedGoogle Scholar