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Occurrence of phenotypic abnormalities in CD34þ hematopoietic progenitor and precursor cells (HPC) and their major B-cell and nonlymphoid compartments has been frequently reported in myelodysplastic syndromes (MDS). Here, we analyze for the first time the numerical and phenotypic abnormalities of different maturation-associated subsets of bone marrow (BM) CD34þ HPC from 50 newly diagnosed MDS patients in comparison to normal/reactive BM (n ¼ 29). Our results confirm the existence of heterogeneously altered phenotypes among CD34 þ HPC from MDS and indicate that such variability depends both on the relative distribution of the different subsets of CD34 þ HPC committed into the different myeloid and B-lymphoid compartments, and their immunophenotype (for example, higher reactivity for CD117 and CD13 and lower expression of CyMPO, CD64 and CD65 on CD34 þ immature and neutrophil precursors), a clear association existing between the accumulation of CD34 þ HPC and that of immature CD34 þ HPC. Interestingly, expansion of erythroidand neutrophil-lineage CD34 þ cells is detected in low-grade MDS at the expense of CD34 þ plasmacytoid dendritic cell and B-cell precursors, while expansion of immature CD34 þ precursors occurs in high-grade MDS. On the basis of the number and severity of the phenotypic abnormalities detected, a scoring system is proposed that efficiently discriminates between normal/reactive and MDS CD34 þ HPC, the mean score significantly increasing from low-to high-grade MDS.

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A heterogeneous spectrum of immunophenotypic abnormalities have been reported in myelodysplastic syndromes (MDS). However, most studies are restricted to the analysis of CD341 cells and/or other major subsets of CD34 2 cells, frequently not exploring the diagnostic and prognostic impact of immunophenotyping.Methods: We propose for the first time an immunophenotypic score (IS) based on the altered distribution and immunophenotypic features of maturing/mature compartments of bone marrow (BM) hematopoietic cells in 56 patients with MDS that could contribute to a refined diagnosis and prognostic evaluation of the disease.Results: Although MDS-associated phenotypes were detected in reactive BM, the overall immunophenotypic profile of BM cells allowed an efficient discrimination between MDS and both normal and reactive BM, once the number and degree of severity of the abnormalities detected per patient were simultaneously considered in the proposed IS. Interestingly, increasingly higher IS were found among patients with MDS showing adverse prognostic factors and in low-versus high-grade cases. The most informative prognostic factors included the number of CD34 1 cells, presence of aberrant CD34 2 /CD117 1 precursors, decreased mature neutrophils and CD34 2 erythroid precursors, and increased numbers of CD36 2/lo erythroid precursors; in addition, the IS was an independent prognostic factor for overall survival.Conclusions: Assessment of immunophenotypic abnormalities of maturing/mature BM cells allows an efficient discrimination between MDS and both normal and reactive BM, once the number and degree of severity of the abnormalities detected are simultaneously scored. Interestingly, progressively higher IS were found among patients with MDS with adverse prognostic features and shorter overall survival.

C urrent 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.

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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.

Conclusion: Overall, these results provide a detailed map GPI-AP expression during normal hematopoietic differentiation, which could serve as a basis for the identification and characterization of changes occurring in PNH. q