BackgroundThe 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.MethodsThis 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.ResultsComparing 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.ConclusionsThe 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.

Background High‐quality data on bone marrow involvement (BMI) assessed by flow cytometry (FC) in follicular lymphoma (FL) is lacking. Aims We set up a prospective protocol with a 10‐color tube and acquisition of 500.000 leukocytes on a Nav flow cytometer for evaluation of BMI in FL by FC. Materials and methods FC was compared with a combination of histopathology and IGH gene rearrangement, which were considered the gold standard. We also compared BMI by FC with PET. Results Fifty‐two patients were included (median 67 years, 54% female). BMI by FC was seen in 35 (67%), with a median involvement of 1.2% (interquartile range: 0.3%–7%) of leukocytes. Comparison with the gold standard revealed two false negatives and two false positives (potentially true involvement undetected by the gold standard). BMI by PET was seen in 14/46 (30%). Immunophenotype of FL in the bone marrow was highly heterogeneous. The most common phenotypic abnormality was dim expression of CD19 (>0.5 log loss in 30% of patients). CD10 was negative in 13 (37%) and incompletely positive (overlap with the negative population) in a further 8 (28%) while entirely positive only in 14 (48%). Other abnormalities (loss of CD20, gain or loss of CD79b, expression of CD43, and substantial loss of CD45) were rare. Computational analysis by means of FlowSOM confirmed the heterogeneous phenotype, with FL from different patients clustering in unrelated metaclusters. Conclusion BMI by FL was frequent and immunophenotype was heterogeneous. However, this protocol enabled detection of FL in bone marrow in the vast majority of patients with bone marrow involvement by the gold standard.

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