Current recommendations for diagnosing myelodysplastic syndromes endorse flow cytometry as an informative tool. Most flow cytometry protocols focus on the analysis of progenitor cells and the ...evaluation of the maturing myelomonocytic lineage. However, one of the most frequently observed features of myelodysplastic syndromes is anemia, which may be associated with dyserythropoiesis. Therefore, analysis of changes in flow cytometry features of nucleated erythroid cells may complement current flow cytometry tools. The multicenter study within the IMDSFlow Working Group, reported herein, focused on defining flow cytometry parameters that enable discrimination of dyserythropoiesis associated with myelodysplastic syndromes from non-clonal cytopenias. Data from a learning cohort were compared between myelodysplasia and controls, and results were validated in a separate cohort. The learning cohort comprised 245 myelodysplasia cases, 290 pathological, and 142 normal controls; the validation cohort comprised 129 myelodysplasia cases, 153 pathological, and 49 normal controls. Multivariate logistic regression analysis performed in the learning cohort revealed that analysis of expression of CD36 and CD71 (expressed as coefficient of variation), in combination with CD71 fluorescence intensity and the percentage of CD117
erythroid progenitors provided the best discrimination between myelodysplastic syndromes and non-clonal cytopenias (specificity 90%; 95% confidence interval: 84-94%). The high specificity of this marker set was confirmed in the validation cohort (92%; 95% confidence interval: 86-97%). This erythroid flow cytometry marker combination may improve the evaluation of cytopenic cases with suspected myelodysplasia, particularly when combined with flow cytometry assessment of the myelomonocytic lineage.
Diagnostic criteria for juvenile myelomonocytic leukemia (JMML) are currently well defined, however in some patients diagnosis still remains a challenge. Flow cytometry is a well established tool for ...diagnosis and follow-up of hematological malignancies, nevertheless it is not routinely used for JMML diagnosis. Herewith, we characterized the CD34+ hematopoietic precursor cells collected from 31 children with JMML using a combination of standardized EuroFlow antibody panels to assess the ability to discriminate JMML cells from normal/reactive bone marrow cell as controls (n=29) or from cells of children with other hematological diseases mimicking JMML (n=9). CD34+ precursors in JMML showed markedly reduced B-cell and erythroid-committed precursors compared to controls, whereas monocytic and CD7+ lymphoid precursors were significantly expanded. Moreover, aberrant immunophenotypes were consistently present in CD34+ precursors in JMML, while they were virtually absent in controls. Multivariate logistic regression analysis showed that combined assessment of the number of CD34+CD7+ lymphoid precursors and CD34+ aberrant precursors or erythroid precursors had a great potential in discriminating JMMLs versus controls. Importantly our scoring model allowed highly efficient discrimination of truly JMML versus patients with JMML-like diseases. In conclusion, we show for the first time that CD34+ precursors from JMML patients display a unique immunophenotypic profile which might contribute to a fast and accurate diagnosis of JMML worldwide by applying an easy to standardize single eight-color antibody combination.
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.
During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and ...label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.
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.
We investigated the distribution of different subsets of monocytes (Mo) in blood and BM of newly-diagnosed untreated MGUS (
= 23), SMM (
= 14) and MM (
= 99) patients vs. healthy donors (HD;
= 107), in parallel to a large panel of cytokines and bone-associated serum biomarkers.
Our results showed normal production of monocyte precursors and classical Mo (cMo) in MGUS, while decreased in SMM and MM (
≤ 0.02), in association with lower blood counts of recently-produced CD62L
cMo in SMM (
= 0.004) and of all subsets of (CD62L
, CD62L
and FcεRI
) cMo in MM (
≤ 0.02). In contrast, intermediate and end-stage non-classical Mo were increased in BM of MGUS (
≤ 0.03), SMM (
≤ 0.03) and MM (
≤ 0.002), while normal (MGUS and SMM) or decreased (MM;
= 0.01) in blood. In parallel, increased serum levels of interleukin (IL)1β were observed in MGUS (
= 0.007) and SMM (
= 0.01), higher concentrations of serum IL8 were found in SMM (
= 0.01) and MM (
= 0.002), and higher serum IL6 (
= 0.002), RANKL (
= 0.01) and bone alkaline phosphatase (BALP) levels (
= 0.01) with decreased counts of FcεRI
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 IL1β 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 (
= 0.01) decreased blood counts of immunomodulatory FcεRI
cMo-, typical of MM presenting with bone lesions.
These results provide new insight into the pathogenesis of plasma cell neoplasms and the potential role of FcεRI
cMo in normal bone homeostasis.
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.
Aberrant CD117 expression is associated with a favorable outcome in multiple myeloma. We analyzed 106 patients with symptomatic multiple myeloma (n=50), smoldering multiple myeloma (n=38) and ...monoclonal gammopathy of undetermined significance (n=18) to elucidate biological features of CD117(+) versus CD117(-) monoclonal gammopathies. CD117(+) (mono)clonal plasma cells were detected in 30% symptomatic multiple myeloma, 45% smoldering multiple myeloma and 72% monoclonal gammopathy of undetermined significance patients. CD117 expression was associated with higher percentages of normal bone marrow plasma cells, CD117(+) myeloid precursors and CD38(+) B lymphocytes in all monoclonal gammopathies. Conversely, the number of bone marrow CD34(+) myeloid cells and peripheral blood neutrophils was reduced among CD117(+) multiple myeloma but not monoclonal gammopathy of undetermined significance patients. CD117 expression by (mono)clonal plasma cells is associated with uniquely altered patterns of production of hematopoietic bone marrow cells with decreased peripheral blood neutrophil counts and persistence of normal residual bone marrow plasma cells.
Background Despite the fact that a great majority (>90%) of patients with systemic mastocytosis (SM) carry a common genetic lesion, the D816V KIT mutation, little is known regarding the molecular and ...biological pathways underlying the clinical heterogeneity of the disease. Objective We sought to analyze the gene expression profile (GEP) of bone marrow mast cells (BMMCs) in patients with SM and its association with distinct clinical variants of the disease. Methods GEP analyses were performed by using DNA-oligonucleotide microarrays in highly purified BMMCs from patients with SM carrying the D816V KIT mutation (n = 26) classified according to the diagnostic subtype of SM versus normal/reactive BMMCs (n = 7). Validation of GEP results was performed with flow cytometry in the same set of samples and in an independent cohort of 176 subjects. Results Overall, 758 transcripts were significantly deregulated in patients with SM, with a common GEP (n = 398 genes) for all subvariants of SM analyzed. These were characterized by upregulation of genes involved in the innate and inflammatory immune response, including interferon-induced genes and genes involved in cellular responses to viral antigens, together with complement inhibitory molecules and genes involved in lipid metabolism and protein processing. Interestingly, aggressive SM additionally showed deregulation of apoptosis and cell cycle–related genes, whereas patients with indolent SM displayed increased expression of adhesion-related molecules. Conclusion BMMCs from patients with different clinical subtypes of SM display distinct GEPs, which might reflect new targetable pathways involved in the pathogenesis of the disease.
Multiparameter flow cytometric analysis of bone marrow and peripheral blood cells has proven to be of help in the diagnostic workup of myelodysplastic syndromes. However, the usefulness of flow ...cytometry for the detection of megakaryocytic and platelet dysplasia has not yet been investigated. The aim of this pilot study was to evaluate by flow cytometry the diagnostic and prognostic value of platelet dysplasia in myelodysplastic syndromes.
We investigated the pattern of expression of distinct surface glycoproteins on peripheral blood platelets from a series of 44 myelodysplastic syndrome patients, 20 healthy subjects and 19 patients with platelet alterations associated to disease conditions other than myelodysplastic syndromes. Quantitative expression of CD31, CD34, CD36, CD41a, CD41b, CD42a, CD42b and CD61 glycoproteins together with the PAC-1, CD62-P, fibrinogen and CD63 platelet activation-associated markers and platelet light scatter properties were systematically evaluated.
Overall, flow cytometry identified multiple immunophenotypic abnormalities on platelets of myelodysplastic syndrome patients, including altered light scatter characteristics, over-and under expression of specific platelet glycoproteins and asynchronous expression of CD34; decreased expression of CD36 (n = 5), CD42a (n = 1) and CD61 (n = 2), together with reactivity for CD34 (n = 1) were only observed among myelodysplastic syndrome cases, while other alterations were also found in other platelet disorders. Based on the overall platelet alterations detected for each patient, an immunophenotypic score was built which identified a subgroup of myelodysplastic syndrome patients with a high rate of moderate to severe alterations (score>1.5; n = 16) who more frequently showed thrombocytopenia, megakaryocytic dysplasia and high-risk disease, together with a shorter overall survival.
Our results show the presence of altered phenotypes by flow cytometry on platelets from around half of the myelodysplastic syndrome patients studied. If confirmed in larger series of patients, these findings may help refine the diagnostic and prognostic assessment of this group of disorders.
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