Simple Summary Flow cytometry allows detailed characterization of large numbers of cells and plays an important role in the diagnosis of acute myeloid leukemia. To facilitate analysis of... Show moreSimple Summary Flow cytometry allows detailed characterization of large numbers of cells and plays an important role in the diagnosis of acute myeloid leukemia. To facilitate analysis of flowcytometric data, reference databases of normal bone marrow samples and samples from acute myeloid leukemia patients, together with new software tools, are required. We here report on the building of a large database of acute myeloid leukemia patients (n = 1142) and 22 normal samples. We report on the quality assessment procedure used and its validation, discuss potential pitfalls, and provide possible solutions for avoiding such flaws in the construction of other databases. Our data show that obtaining and collecting reproducible flow cytometric data over time and across centers is feasible, but also that strict quality assessment remains crucial, even when standardized protocols for staining and instrument settings are being used in a multicenter setting. Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis. Show less
Brouwer, N.; Matarraz, S.; Nierkens, S.; Hofmans, M.; Novakova, M.; Costa, E.S. da; ... ; EuroFlow Consortium 2022
Simple Summary: Acute megakaryoblastic leukemia (AMKL) is a rare and heterogeneous subtype of acute myeloid leukemia (AML). We show that such patients can be identified by flowcytometric... Show moreSimple Summary: Acute megakaryoblastic leukemia (AMKL) is a rare and heterogeneous subtype of acute myeloid leukemia (AML). We show that such patients can be identified by flowcytometric immunophenotyping using the standardized EuroFlow panel. AMKL patients show a unique immunophenotypic profile, and among AMKL patients, various subgroups can be distinguished. Acute megakaryoblastic leukemia (AMKL) is a rare and heterogeneous subtype of acute myeloid leukemia (AML). We evaluated the immunophenotypic profile of 72 AMKL and 114 non-AMKL AML patients using the EuroFlow AML panel. Univariate and multivariate/multidimensional analyses were performed to identify most relevant markers contributing to the diagnosis of AMKL. AMKL patients were subdivided into transient abnormal myelopoiesis (TAM), myeloid leukemia associated with Down syndrome (ML-DS), AML-not otherwise specified with megakaryocytic differentiation (NOS-AMKL), and AMKL-other patients (AML patients with other WHO classification but with flowcytometric features of megakaryocytic differentiation). Flowcytometric analysis showed good discrimination between AMKL and non-AMKL patients based on differential expression of, in particular, CD42a.CD61, CD41, CD42b, HLADR, CD15 and CD13. Combining CD42a.CD61 (positive) and CD13 (negative) resulted in a sensitivity of 71% and a specificity of 99%. Within AMKL patients, TAM and ML-DS patients showed higher frequencies of immature CD34+/CD117+ leukemic cells as compared to NOS-AMKL and AMKL-Other patients. In addition, ML-DS patients showed a significantly higher expression of CD33, CD11b, CD38 and CD7 as compared to the other three subgroups, allowing for good distinction of these patients. Overall, our data show that the EuroFlow AML panel allows for straightforward diagnosis of AMKL and that ML-DS is associated with a unique immunophenotypic profile. Show less
Simple SummaryWe investigated the distribution of different subsets of monocytes (Mo) in blood and bone marrow (BM) of newly-diagnosed untreated monoclonal gammopathy of undetermined significance ... Show moreSimple SummaryWe investigated the distribution of different subsets of monocytes (Mo) in blood and bone marrow (BM) of newly-diagnosed untreated monoclonal gammopathy of undetermined significance (MGUS), smoldering (SMM) and active multiple myeloma (MM), and its relationship with immune/bone serum-marker profiles. Our results showed decreased production of BM Mo with decreased counts of classical Mo (cMo) in BM and blood of SMM and MM, but not MGUS. Conversely, intermediate and non-classical Mo were significantly increased in MGUS, SMM and MM BM. In parallel, increased levels of interleukin (IL)1 beta were observed in a fraction of MGUS and SMM, while increased serum IL8 was characteristic of SMM and MM, and higher serum IL6, RANKL and bone alkaline phosphatase concentrations, together with decreased counts of Fc epsilon RI(+)cMo, were restricted to MM presenting with bone lesions. These results provide new insights in the pathogenesis of plasma cell neoplasms and the potential role of Fc epsilon RI(+)cMo in normal bone homeostasis.Background. Monocyte/macrophages have been shown to be altered in monoclonal gammopathy of undetermined significance (MGUS), smoldering (SMM) and active multiple myeloma (MM), with an impact on the disruption of the homeostasis of the normal bone marrow (BM) microenvironment. Methods: We investigated the distribution of different subsets of monocytes (Mo) in blood and BM of newly-diagnosed untreated MGUS (n = 23), SMM (n = 14) and MM (n = 99) patients vs. healthy donors (HD; n = 107), in parallel to a large panel of cytokines and bone-associated serum biomarkers. Results: Our results showed normal production of monocyte precursors and classical Mo (cMo) in MGUS, while decreased in SMM and MM (p <= 0.02), in association with lower blood counts of recently-produced CD62L(+) cMo in SMM (p = 0.004) and of all subsets of (CD62L(+), CD62L(-) and Fc epsilon RI+) cMo in MM (p <= 0.02). In contrast, intermediate and end-stage non-classical Mo were increased in BM of MGUS (p <= 0.03), SMM (p <= 0.03) and MM (p <= 0.002), while normal (MGUS and SMM) or decreased (MM; p = 0.01) in blood. In parallel, increased serum levels of interleukin (IL)1 beta were observed in MGUS (p = 0.007) and SMM (p = 0.01), higher concentrations of serum IL8 were found in SMM (p = 0.01) and MM (p = 0.002), and higher serum IL6 (p = 0.002), RANKL (p = 0.01) and bone alkaline phosphatase (BALP) levels (p = 0.01) with decreased counts of Fc epsilon RI+ cMo, were restricted to MM presenting with osteolytic lesions. This translated into three distinct immune/bone profiles: (1) normal (typical of HD and most MGUS cases); (2) senescent-like (increased IL1 beta and/or IL8, found in a minority of MGUS, most SMM and few MM cases with no bone lesions); and (3) pro-inflammatory-high serum IL6, RANKL and BALP with significantly (p = 0.01) decreased blood counts of immunomodulatory Fc epsilon RI+ cMo-, typical of MM presenting with bone lesions. Conclusions: These results provide new insight into the pathogenesis of plasma cell neoplasms and the potential role of Fc epsilon RI+ cMo in normal bone homeostasis. Show less
Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and... Show morePrecise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB,n = 41) and bone marrow (BM;n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r(2) > 0.95 for all cell types in PB andr(2) > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a "sample-in and result-out" approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures. Show less
Flow cytometry immunophenotyping is essential for diagnosis, classification and monitoring of clonal hematopoietic diseases, particularly of hematological malignancies and primary... Show moreFlow cytometry immunophenotyping is essential for diagnosis, classification and monitoring of clonal hematopoietic diseases, particularly of hematological malignancies and primary immunodeficiencies. Optimal use of immunophenotyping for these purposes requires detailed knowledge about the phenotypic patterns of normal hematopoietic cells.In the past few decades, flow cytometry has benefited from technological developments allowing simultaneous analysis of multiple antigen stainings with >= 3-35 distinct fluorochrome-conjugated antibodies for increasingly higher numbers of cells. These advances have contributed to expand our knowledge about the phenotypic differentiation profiles of normal hematopoietic cells, from uncommitted CD34(+) precursors in the bone marrow (BM) and peripheral blood (PB), to the several hundreds of populations of circulating myeloid and (B and T) lymphoid cells identified so far. Detailed dissection of the normal phenotypic profiles of hematopoietic cells has settled the basis for identification of aberrant phenotypes on leukemia and lymphoma cells. Thus, it has contributed to: i) more sensitive identification of leukemia/lymphoma cells (especially when represented at low frequencies in a sample), and ii) more accurate classification of hematological malignancies. In this manuscript, we review the major phenotypic features of hematopoietic cells, from the more immature BM CD34(+) precursors committed to the myeloid and lymphoid lineages toward mature hematopoietic cells circulating in PB (e.g. neutrophils, monocytes, basophils, eosinophils, dendritic cells, erythroid cells, and B- and T-cells) and those homing to other tissues (e.g. plasma cells, mast cells). Show less
Damasceno, D.; Teodosio, C.; Bossche, W.B.L. van den; Perez-Andres, M.; Arriba-Mendez, S.; Munoz-Bellvis, L.; ... ; TiMaScan Study Grp 2019
Severe hemorrhagic events occur in a significant fraction of acute promyelocytic leukemia patients, either at presentation and/or early after starting therapy, leading to treatment failure and... Show moreSevere hemorrhagic events occur in a significant fraction of acute promyelocytic leukemia patients, either at presentation and/or early after starting therapy, leading to treatment failure and early deaths. However, identification of independent predictors for high-risk of severe bleeding at diagnosis, remains a challenge. Here, we investigated the immunophenotype of bone marrow leukemic cells from 109 newly diagnosed acute promyelocytic leukemia patients, particularly focusing on the identification of basophil-related features, and their potential association with severe bleeding episodes and patient overall survival. From all phenotypes investigated on leukemic cells, expression of the CD203c and/or CD22 basophil-associated markers showed the strongest association with the occurrence and severity of bleeding (p <= 0.007); moreover, aberrant expression of CD7, coexpression of CD34(+)/CD7(+) and lack of CD71 was also more frequently found among patients with (mild and severe) bleeding at baseline and/or after starting treatment (p <= 0.009). Multivariate analysis showed that CD203c expression (hazard ratio: 26.4; p = 0.003) and older age (hazard ratio: 5.4; p = 0.03) were the best independent predictors for cumulative incidence of severe bleeding after starting therapy. In addition, CD203c expression on leukemic cells (hazard ratio: 4.4; p = 0.01), low fibrinogen levels (hazard ratio: 8.8; p = 0.001), older age (hazard ratio: 9.0; p = 0.002), and high leukocyte count (hazard ratio: 5.6; p = 0.02) were the most informative independent predictors for overall survival. In summary, our results show that the presence of basophil-associated phenotypic characteristics on leukemic cells from acute promyelocytic leukemia patients at diagnosis is a powerful independent predictor for severe bleeding and overall survival, which might contribute in the future to (early) risk-adapted therapy decisions. Show less
