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Updated: Jul 7, 2025

Flow Cytometric Characterization of Murine B Cell Development
Published on: January 22, 2021
Multiparametric Flow Cytometry in the Evaluation of Plasma Cell Proliferative Disorders: Current Paradigms for
Ritu Gupta1, Dragan Jevremovic2, Smith J Mathew3
1Department of Laboratory Oncology, Dr. BRAIRCH, AIIMS, New Delhi, India; Department of Hematology, Mayo Clinic, Rochester, MN.
Abstract:
Diagnosis of plasma cell proliferative disorders (PCPDs) is primarily based on the demonstration of monoclonal protein (M-Protein) in blood and/ or urine which often precedes clinical manifestations of the disease. The basic pathophysiology behind the M-protein presence is the proliferation of clonal plasma cells (PCs) in bone marrow or extramedullary sites and is assessed using cytomorphology and immunophenotyping. The role of multiparametric flow cytometry (MFC) for PC identification is technically the most valuable tool in this context as it characterizes as well as quantifies the clonal PCs based on differential expression of various immunophenotypic (IPT) markers. From a diagnostic perspective, MFC is critical in the definite identification of the clonal PCs and delineates benign and borderline entities at one end of the spectrum (MGUS, SMM) with lower clonal PC% and, malignant diseases at the other end (MM and PCL) with higher clonal PC fraction. The role of MFC in assessment of measurable residual disease (MRD) and monitoring of progression in MM and various PCPDs has been validated in multiple clinical studies and is probably one of the most promising tools for predicting treatment outcomes. Furthermore, MFC also plays a crucial role in disease prognostication based on specific IPT profiles. An additional role of MFC in the current clinical scenario is the evaluation of tumor microenvironment based on immune cell repertoire, which is reflecting encouraging results across. Thus, in the current review we concisely describe the role of MFC as a reliable and essential modality in PCPDs, from diagnosis to prediction of treatment outcome and disease monitoring.
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