Primate Monocytes - CD14, CD16 - Ziegler-Heitbrock


Optimization of monocyte gating to quantify monocyte subsets for the diagnosis of chronic myelomonocytic leukemia.


BACKGROUND: The presence of >94% classical monocytes (MO1, CD14++/CD16-) in peripheral blood (PB) has an excellent performance for the diagnosis of chronic myelomonocytic leukemia (CMML). However, the monocyte gating strategy is not well defined. The objective of the study was to compare monocyte gating strategies and propose an optimal one. METHODS: This is a prospective, single center study assessing monocyte subsets in PB. First, we compared monocyte subsets using 13 monocyte gating strategies in 10 samples. Then we developed our own 10 color tube and tested it on 124 patients (normal white blood cell counts, reactive monocytosis, CMML and a spectrum of other myeloid malignancies). Both conventional and computational (FlowSOM) analyses were used. RESULTS: Comparing different monocyte gating strategies, small but significant differences in %MO1 and percentually large differences in %MO3 (nonclassical monocytes) were found, suggesting that the monocyte gating strategy can impact monocyte subset quantification. Then, we designed a 10-color tube for this purpose (CD45/CD33/CD14/CD16/CD64/CD86/CD300/CD2/CD66c/CD56) and applied it to 124 patients. This tube allowed proper monocyte gating even in highly abnormal PB. Computational analysis found a higher %MO1 and lower %MO3 compared to conventional analysis. However, differences between conventional and computational analysis in both MO1 and MO3 were globally consistent and only minimal differences were observed when comparing the ranking of patients according to %MO1 or %MO3 obtained with the conventional versus the computational approach. CONCLUSIONS: The choice of monocyte gating strategy appears relevant for the monocyte subset distribution test. Our 10-color proposal allowed satisfactory monocyte gating even in highly abnormal PB. Computational analysis seems promising to increase reproducibility in monocyte subset quantification.

Authors: Jurado R, Huguet M, Xicoy B, Cabezon M, Jimenez-Ponce A, Quintela D, De La Fuente C, Raya M, Vinets E, Junca J, Julià-Torras J, Zamora L, Oriol A, Navarro JT, Calvo X, Sorigue M,
Journal: Cytometry B Clin Cytom;2022Nov30. doi:10.1002/cyto.b.22106
Year: 2022
PubMed: PMID: 36448679 (Go to PubMed)