ORIGINAL PAPER
The significance of the classical monocyte subpopulation in chronic myelomonocytic leukemia: a single-center experience
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Department of Hematology, Cellular Therapies, and Internal Medicine, Wroclaw Medical University, Wrocław, Poland
Submission date: 2025-04-27
Final revision date: 2025-09-06
Acceptance date: 2025-09-15
Online publication date: 2026-02-09
Corresponding author
Justyna Rybka
Department of Hematology, Cellular Therapies, and Internal Medicine, Wroclaw Medical University, Wrocław, Poland
KEYWORDS
ABSTRACT
Introduction:
Chronic myelomonocytic leukemia (CMML) is a myelodysplastic/ myeloproliferative neoplasm. In 2022, updated diagnostic classifications for CMML were introduced by the International Consensus Classification (ICC) and World Health Organization (WHO). Monocytes are subdivided into three populations: classical (MO1), intermediate (MO2), and non-classical (MO3). One of the newly established diagnostic criteria for CMML is an increase in the MO1 fraction to ≥ 94%, as determined by multiparametric flow cytometry (MFC). This parameter has been shown to be a highly sensitive and specific marker that can rapidly and accurately differentiate CMML from other conditions.
Material and Methods:
At the Department of Hematology, Cellular Therapies, and Internal Medicine, University Clinical Hospital in Wrocław, we evaluated the distribution of monocytes and their subpopulations using MFC in 27 patients with newly diagnosed CMML, classified according to the updated WHO criteria.
Results:
The criterion of an MO1 fraction ≥ 94% was fulfilled in 22 patients (81.5%).
Conclusions:
Our findings are consistent with previously published data and support the utility of this method as a reliable tool for both initial screening and longitudinal monitoring of CMML.
REFERENCES (22)
1.
Patnaik MM, Lasho T (2020): Evidence-based minireview: Myelodysplastic syndrome/myeloproliferative neoplasm overlap syndromes: A focused review. Hematology 2020: 460-464.
2.
Prakash S, Arber DA, Bueso-Ramos C, et al. (2022): Advances in myelodysplastic/myeloproliferative neoplasms. Virchows Arch 482: 69-83.
3.
Khoury JD, Solary E, Abla O, et al. (2022): The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and histiocytic/dendritic neoplasms. Leukemia 36: 1703-1719.
4.
Pizzi M, Gurrieri C, Orazi A (2023): What’s new in the classification, diagnosis and therapy of myeloid leukemias. Hemato 4: 112-134.
5.
Arber DA, Orazi A, Hasserjian RP, et al. (2022): International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: Integrating morphologic, clinical, and genomic data. Blood 140: 1200-1228.
6.
Ziegler-Heitbrock L, Ancuta P, Crowe S, et al. (2010): Nomenclature of monocytes and dendritic cells in blood. Blood 116: e74-80.
7.
Selimoglu-Buet D, Wagner-Ballon O, Saada V, et al. (2015): Characteristic repartition of monocyte subsets as a diagnostic signature of chronic myelomonocytic leukemia. Blood 125: 3618-3626.
8.
Talati C, Zhang L, Shaheen G, et al. (2017): Monocyte subset analysis accurately distinguishes CMML from MDS and is associated with a favorable MDS prognosis. Blood 129: 1881-1883.
9.
Tarfi S, Harrivel V, Dumezy F, et al. (2017): Multicentric validation of the “monocyte assay” for chronic myelomonocytic leukemia diagnosis by flow cytometry. Blood (ASH Annual Meeting Abstracts) 130 (Suppl): 4273.
10.
Pophali PA, Timm MM, Mangaonkar AA, et al. (2019): Practical limitations of monocyte subset repartitioning by multiparametric flow cytometry in chronic myelomonocytic leukemia. Blood Cancer J 9: 65.
11.
Patnaik MM, Zeidan AM, Padron E, et al. (2022): Differences in classification schemata for myelodysplastic/myeloproliferative overlap neoplasms. Leukemia 36: 2934-2938.
12.
Hwang SM, Ahn H, Jeon S, et al. (2021): Monocyte subsets to differentiate chronic myelomonocytic leukemia from reactive monocytosis. J Clin Lab Anal 35: e23576.
13.
Patel AA, Zhang Y, Fullerton JN, et al. (2017): The fate and lifespan of human monocyte subsets in steady state and systemic inflammation. J Exp Med 214: 1913-1923.
14.
Fingerle-Rowson G, Angstwurm M, Andreesen R, Ziegler-Heitbrock HW (1998): Selective depletion of CD14+ CD16+ monocytes by glucocorticoid therapy. Clin Exp Immunol 112: 501-506.
15.
Heimbeck I, Hofer TPJ, Eder C, et al. (2010): Standardized single-platform assay for human monocyte subpopulations: Lower CD14+CD16++ monocytes in females. Cytometry A 77: 823-830.
16.
Zahid MF, Barraco D, Lasho TL, et al. (2017): Spectrum of autoimmune diseases and systemic inflammatory syndromes in patients with chronic myelomonocytic leukemia. Leuk Lymphoma 58: 1488-1493.
17.
Selimoglu-Buet D, Badaoui B, Benayoun E, et al. (2017): Accumulation of classical monocytes defines a subgroup of MDS that frequently evolves into CMML. Blood 130: 832-835.
18.
Tarfi S, Badaoui B, Freynet N, et al. (2020): Disappearance of slan-positive non-classical monocytes for diagnosis of chronic myelomonocytic leukemia with an associated inflammatory state. Haematologica 105: e147-e152.
19.
Tarfi S, Kern W, Goulas E, et al. (2024): Technical, gating and interpretation recommendations for the partitioning of circulating monocyte subsets assessed by flow cytometry. Cytometry B Clin Cytom 106: 203-215.
20.
Barge L, Gooch M, Hendle M, Simleit E (2023): Real world implementation of flow cytometric monocyte subset partitioning for distinguishing chronic myelomonocytic leukaemia from other causes of monocytosis. Pathology 55: 827-834.
21.
Liu Y, Tariq H, Fu L, et al. (2025): Usefulness of flow cytometry monocyte partitioning in the diagnosis of chronic myelomonocytic leukemia in a real-world setting. Cancers (Basel) 17: 1229.
22.
Jurado R, Huguet M, Xicoy B, et al. (2023): Optimization of monocyte gating to quantify monocyte subsets for the diagnosis of chronic myelomonocytic leukemia. Cytometry B Clin Cytom 104: 319-330.