A probabilistic approach for the evaluation of minimal residual disease by multiparameter flow cytometry in leukemic B-cell chronic lymphoproliferative disorders

Authors

  • C.E. Pedreira,

    1. Faculty of Medicine and COPPE-PEE Engineering Graduate Program, UFRJ/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
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  • E.S. Costa,

    1. Instituto de Pediatria e Puericultura Martagão Gesteira/IPPMG and Departamento de Clínica Médica, UFRJ/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
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  • J. Almeida,

    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
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  • C. Fernandez,

    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
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  • S. Quijano,

    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
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  • J. Flores,

    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
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  • S. Barrena,

    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
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  • Q. Lecrevisse,

    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
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  • J.J.M. Van Dongen,

    1. Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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  • A. Orfao

    Corresponding author
    1. Cytometry Service, Department of Medicine and Cancer Research Center (IBMCC, University of Salamanca-CSIC), University of Salamanca, Salamanca, Spain
    • Centro de Investigación del Cáncer, Paseo de la Universidad de Coimbra, s/n, Campus Miguel de Unamuno, 37007 Salamanca, Spain
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  • Conflict of Interest: Cytognos S.L. is a part of the UE-supported EuroFlow Research Consortium and has implemented some of the algorithms described in the present study, in its proprietary software INFINICYT; Cytognos S.L. has a contract license of several patents owned by the University of Salamanca, of which A Orfao, CE Pedreira, and ES Costa are inventors. Other authors declare no competing financial interests.

Abstract

Multiparameter flow cytometry has become an essential tool for monitoring response to therapy in hematological malignancies, including B-cell chronic lymphoproliferative disorders (B-CLPD). However, depending on the expertise of the operator minimal residual disease (MRD) can be misidentified, given that data analysis is based on the definition of expert-based bidimensional plots, where an operator selects the subpopulations of interest. Here, we propose and evaluate a probabilistic approach based on pattern classification tools and the Bayes theorem, for automated analysis of flow cytometry data from a group of 50 B-CLPD versus normal peripheral blood B-cells under MRD conditions, with the aim of reducing operator-associated subjectivity. The proposed approach provided a tool for MRD detection in B-CLPD by flow cytometry with a sensitivity of ≤8 × 10−5 (median of ≤2 × 10−7). Furthermore, in 86% of B-CLPD cases tested, no events corresponding to normal B-cells were wrongly identified as belonging to the neoplastic B-cell population at a level of ≤10−7. Thus, this approach based on the search for minimal numbers of neoplastic B-cells similar to those detected at diagnosis could potentially be applied with both a high sensitivity and specificity to investigate for the presence of MRD in virtually all B-CLPD. Further studies evaluating its efficiency in larger series of patients, where reactive conditions and non-neoplastic disorders are also included, are required to confirm these results. © 2008 International Society for Advancement of Cytometry

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