Primate Monocytes - CD14, CD16 - Ziegler-Heitbrock


Real world implementation of flow cytometric monocyte subset partitioning for distinguishing chronic myelomonocytic leukaemia from other causes of monocytosis.


Monocyte subset partitioning by flow cytometry may be a useful tool in distinguishing chronic myelomonocytic leukaemia (CMML) from other causes of monocytosis, however there has been varying success in real world implementation. Additionally, current assays require an individual tube for analysis despite significant overlap in antibodies used in routine T and NK cell analysis. The objective of this study was to validate a flow cytometry assay for the enumeration of monocyte subsets in our community-based laboratory and compare this to a hybrid panel allowing analysis of monocytes, T cells and NK cells in a single tube. Monocyte subset analysis was performed on peripheral blood samples of patients with monocytosis at the time of bone marrow biopsy or transient monocytosis in the setting of bacteraemia. Cut-offs of >94% classical and <1.13% non-classical monocytes for distinguishing CMML were assessed. Classical monocytes were significantly higher, and non-classical monocytes significantly lower in CMML compared to other causes of monocytosis. The sensitivity and specificity of >94% classical monocytes were 73% [95% confidence interval (CI) 43-90%] and 89% (95% CI 75-96%) regardless of which panel was used. Non-classical monocytes of <1.13% had a sensitivity and specificity of 82% (95% CI 52-97%) and 83% (95% CI 68-92%) with the monocyte panel and 55% (95% CI 28-78%) and 89% (95% CI 75-96%) using the hybrid panel. We have found the estimation of the classical monocyte subset to be the most robust and repeatable variation of this assay with sensitivity and specificity that is clinically useful. A hybrid panel may provide an effective approach to implementing monocyte subsets into practice.

Authors: Barge L, Gooch M, Hendle M, Simleit E.
Journal: Pathology . 2023 Oct;55(6):827-834. doi: 10.1016/j.pathol.2023.05.006. Epub 2023 Jul 16.
Year: 2023
PubMed: PMID: 37541805 (Go to PubMed)