Flow cytometric monocyte repartition demonstrates overlap between chronic myelomonocytic leukaemia and myeloid neoplasms with monocytosis

Usefulness of Flow Cytometry Monocyte Partitioning in the Diagnosis of Chronic Myelomonocytic Leukemia in a Real-World Setting

BACKGROUND

Based on CD14/CD16 expression, monocytes can be divided into the following three functionally distinct subsets: classical (MO1, CD14++/CD16-), intermediate (MO2, CD14+/CD16+) and non-classical (MO3, CD14dim/CD16-). An expanded MO1 subset (cutoff, ≥94%) was found to be predictive of CMML. However, the utility of this test in routine practice has important limitations, with some reporting low sensitivity or a lack of correlation. Here, we sought to evaluate the practical usefulness of this test by using our routine antibody panel and a new gating strategy.

METHODS

Our study included 56 peripheral blood (PB) and 69 bone marrow (BM) samples. The PB cohort included 20 patients with CMML, 21 with no myeloid neoplasms (non-MN) and 15 with other myeloid neoplasms (non-CMML-MN). The BM cohort included 25 CMML, 16 non-MN and 28 non-CMML-MN cases. Taking advantage of an existing 8-color myelomonocytic tube routinely used in our lab, we conducted a retrospective monocyte subset analysis using a new sequential gating strategy.

RESULTS

The assay was able to distinguish CMML from non-CMML cases with high sensitivity (90.0%) and specificity (88.9%) in blood samples using a cutoff value of MO1 > 94%. For BM samples, a reduced MO3 < 1.24% was more closely associated with CMML with a sensitivity of 96.0% and a specificity of 79.5%. A side-by-side comparison of our assay with the original "monocyte assay" showed strong agreement.

CONCLUSIONS

Our study demonstrates the utility of a practical and robust approach for monocyte subset analysis in the diagnosis of CMML.

Technical, gating and interpretation recommendations for the partitioning of circulating monocyte subsets assessed by flow cytometry

The monocyte subset partitioning by flow cytometry, known as "monocyte assay," is now integrated into the new classifications as a supporting criterion for CMML diagnosis, if a relative accumulation of classical monocytes above 94% of total circulating monocytes is observed. Here we provide clinical flow cytometry laboratories with technical support adapted for the most commonly used cytometers. Step-by-step explanations of the gating strategy developed on whole peripheral blood are presented while underlining the most common difficulties. In a second part, interpretation recommendations of circulating monocyte partitioning from the dedicated French working group "CytHem-LMMC" are shared as well as the main pitfalls, including false positive and false negative cases. The particular flow-defined inflammatory profile is described and the usefulness of the nonclassical monocyte specific marker, namely slan, highlighted. Examples of reporting to the physician with frequent situations encountered when using the monocyte assay are also presented.

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.