Development of an unbiased, semi-automated approach for classifying plasma cell immunophenotype following multicolor flow cytometry of bone marrow aspirates

Abstract

Background: Despite increased usage of multiparameter flow cytometry (MFC) to assess diagnosis, prognosis, and therapeutic efficacy (minimal residual disease, MRD) in plasma cell neoplasms (PCNs), standardization of methodology and data analysis is suboptimal. We investigated the utility of using the mean and median fluorescence intensities (FI) obtained from MFC to objectively describe parameters that distinguish plasma cell (PC) phenotypes. Methods: In this retrospective study, flow cytometry results from bone marrow aspirate specimens from 570 patients referred to the Myeloma Institute at UAMS were evaluated. Mean and median FI data were obtained from 8-color MFC of non-neoplastic, malignant, and mixed PC populations using antibodies to CD38, CD138, CD19, CD20, CD27, CD45, CD56, and CD81. Results: Of 570 cases, 252 cases showed only non-neoplastic PCs, 168 showed only malignant PCs, and 150 showed mixed PC populations. Statistical analysis of median FI data for each CD marker showed no difference in expression intensity on non-neoplastic and malignant PCs, between pure and mixed PC populations. ROC analysis of the median FI of CD expression in non-neoplastic and malignant PCs was used to develop an algorithm to convert quantitative FI values to qualitative assessments including “negative,” “positive,” “dim,” and “heterogeneous” expression. Conclusions: FI data derived from 8-color MFC can be used to define marker expression on PCs. Translation of FI data from Infinicyt software to an Excel worksheet streamlines workflow and eliminates transcriptional errors when generating flow reports. © 2018 International Clinical Cytometry Society.