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    The expression pattern of common antigens including cytoplasmic kappa/lambda ratio (cyKLR) was evaluated by flow cytometric immunophenotyping (FCMI) to explore their relevance in discriminating normal and aberrant plasma cells (NPC and APC, respectively) across spectrum of plasma cell proliferative disorders (PCPD). In this prospective analysis, 791 samples from PCPD (treatment naive = 455; partially treated = 336) were evaluated for expression of CD38, CD138, CD45, CD19, CD56, CD27, CD81, CD117, Cy-kappa, and Cy-lambda using FCMI. Amongst the entire cohort, 20.7% (n = 164) samples displayed only APC, 21% (n = 165) only NPC and 58% (n = 462) showed coexistence of NPC and APC. Using pattern-based recognition (PBR) for three common patterns (CD19 vs. CD56; CD27 vs. CD56 and CD19 vs. CD27), APC was separable from NPC in 93% samples. In 6.5% samples, the gating markers contributed in APC-NPC differentiation and in the remaining 0.5% CD117 and CD81 proved useful. Clonality assessment was found to be crucial to label plasma cell compartment as completely normal or aberrant in 42% cases with either all NPC or all APC. Sixty one out of 462 cases (13%) revealed cyKLR within normal reference range and in these cases; abnormal cyKLR was demonstrable only after gating APC separately based on PBR. Fair discrimination between NPC and APC is achievable in all PCPD samples using eight markers (Gating: CD38, CD138, CD45; PBR:CD19, CD56, CD27; clonality: Cy-kappa and Cy-lambda). Thus, combined assessment of clonality and immunophenotypic aberrancies is required for accurate, reliable and precise assessment of NPC and APC compartments in PCPD. © 2022 International Clinical Cytometry Society.

    Citation

    Nupur Das, Meetu Dahiya, Ritu Gupta, Sandeep Rai, Saroj Singh, Vijay K Prajapati, Lalit Kumar, Atul Sharma, Ranjit K Sahoo, Ajay Gogia. Flow cytometric immunophenotyping of plasma cells across the spectrum of plasma cell proliferative disorders: A fresh insight with pattern-based recognition. Cytometry. Part B, Clinical cytometry. 2022 Jul;102(4):292-302

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    PMID: 35212134

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