Background: T-cell immunoglobulin mucin-3 (TIM3) has recently been described as an acute myeloid leukemia (AML) stem cell antigen expressed on leukemic myeloblasts, but not on normal hematopoietic stem cells. TIM3 is also expressed by monocytes, natural killer cells, and several T cell subsets; however, normal myeloblasts have not been well-characterized or compared to AML. A specific flow cytometric marker capable of separating leukemic myeloblasts from non-neoplastic myeloblasts would be diagnostically useful, especially in the post-chemotherapy setting.Methods: TIM3 myeloblast expression was assessed in 69 bone marrow and/or peripheral blood specimens, including 27 AML and 42 non-neoplastic cases (20 with a recent history of chemotherapy). TIM3 median fluorescence intensity (MFI) was evaluated within myeloblast, monocyte, T cell, and natural killer cell populations.Results: The median percentage of myeloblasts positive for TIM3 was lower in non-neoplastic specimens without a history of recent chemotherapy (50.3%) as compared to AML (71.4%), but not significantly different as compared to non-leukemic myeloblasts in the post-chemotherapy setting (72.4%). Mean myeloblast TIM3 MFI was higher in AML myeloblasts and non-leukemic myeloblasts in the postchemotherapy setting as compared to non-neoplastic myeloblasts in cases lacking a history of chemotherapy. Mean monocyte, natural killer cell, and T-cell TIM3 MFI remained relatively constant in varied clinical settings.Conclusions: We confirm that leukemic myeloblasts overexpress TIM3 as compared to non-neoplastic controls; however, high levels of expression may also be seen among non-leukemic myeloblasts in the post-chemotherapy setting. This overlap limits the diagnostic utility of TIM3 as a specific marker of neoplasia.

Background: Although many clinical laboratories are adopting higher color flow cytometric assays, the approach to optimizing panel design and data analysis is often traditional and subjective. In order to address the question "What is the best flow cytometric strategy to reliably distinguish germinal center B-cell lymphoma (GC-L) from lymphoid hyperplasia (GC-H)?" we applied a computational tool that identifies target populations correlated with a desired outcome, in this case diagnosis. Design: Cases of GC-H and GC-L with a germinal center phenotype, evaluated by flow cytometric immunophenotyping using CD45, CD20, kappa, lambda, CD19, CD5, CD10, CD38, were analyzed with flowType and RchyOptimyx to construct cellular hierarchies that best distinguished the two diagnostic groups. Results: The population CD5-CD19+CD10+CD38- had the highest predictive power. Manual reanalysis confirmed significantly higher CD10+/CD38-B-cells in GC-L (median 12.44%, range 0.74 - 63.29, n=52) than GC-H (median 0.24%, 0.03 - 4.49, n=48, p=0.0001), but was not entirely specific. Difficulties encountered using this computational approach included the presence of CD10+ granulocytes, continuously variable B-cell expression of CD38, more variable intensity antigen staining in GC-L and inability to assess the contribution of light chain restriction. Conclusion: Computational analysis with construction of cellular hierarchies related to diagnosis helped guide manual analysis of high dimensional flow cytometric data. This approach highlighted the diagnostic utility of CD38 expression in the evaluation of B-cells with a CD10+ GC phenotype. In contrast to computational analysis of non-neoplastic cell populations, evaluation of neoplastic cells must be able to take into consideration increased variability in antigen expression. © 2013 Clinical Cytometry Society.

Background: Although many clinical laboratories are adopting higher color flow cytometric assays, the approach to optimizing panel design and data analysis is often traditional and subjective. In order to address the question "What is the best flow cytometric strategy to reliably distinguish germinal center B-cell lymphoma (GC-L) from germinal center hyperplasia (GC-H)?" we applied a computational tool that identifies target populations correlated with a desired outcome, in this case diagnosis.Design: Cases of GC-H and GC-L evaluated by flow cytometric immunophenotyping using CD45, CD20, kappa, lambda, CD19, CD5, CD10, CD38, were analyzed with flowType and RchyOptimyx to construct cellular hierarchies that best distinguished the two diagnostic groups.Results: The population CD52CD191CD101CD382 had the highest predictive power. Manual reanalysis confirmed significantly higher CD101/CD382B-cells in GC-L (median 12.44%, range 0.74-63.29, n 5 52) than GC-H (median 0.24%, 0.03-4.49, n 5 48, P 5 0.0001), but was not entirely specific. Difficulties encountered using this computational approach included the presence of CD101 granulocytes, continuously variable B-cell expression of CD38, more variable intensity antigen staining in GC-L and inability to assess the contribution of light chain restriction.Conclusion: Computational analysis with construction of cellular hierarchies related to diagnosis helped guide manual analysis of high dimensional flow cytometric data. This approach highlighted the diagnostic utility of CD38 expression in the evaluation of B-cells with a CD101 GC phenotype. In contrast to computational analysis of non-neoplastic cell populations, evaluation of neoplastic cells must be able to take into consideration increased variability in antigen expression. V C 2013 International Clinical

Establishing the diagnosis of myelodysplastic syndrome (MDS) can be diffi cult and requires a multiparametric approach, with correlation of the clinical, morphologic and genetic features. Although MDS is characterized by dysplastic changes in the myeloid, erythroid or megakaryocytic lineages, some cases may lack overt morphologic dysplasia (i.e. involve less than 10% of cells within a lineage). However, if a MDS-related cytogenetic abnormality is identifi ed, the 2008 World Health Organization criteria permit a MDS diagnosis to be established [1]. In addition, other factors (vitamin/ nutritional defi ciency, toxic/metabolic factors, infections, etc.) can contribute to morphologic dysplasia, complicating the diagnostic interpretation. Detection of a clonal abnormality by cytogenetic studies may be helpful in this clinical context; however, a clonal abnormality is identifi ed in only about half of MDS cases [2].Flow cytometry is an additional ancillary tool that can add value to the diagnostic evaluation [3]. When focused on the CD34 ϩ myeloblast compartment, prior studies have identifi ed altered levels of antigen expression, aberrant expression of lymphoid markers or asynchronous expression of mature myelomonocytic antigens as diagnostically useful [4]. However, these aberrancies may not be present in all cases, necessitating a search for additional markers.T-cell immunoglobulin mucin-3 (TIM3) is a recently described acute myeloid leukemia (AML) stem cell antigen which has been shown to be overexpressed on leukemic stem cells (LSCs) as well as most leukemic blasts, but has not been well characterized in non-leukemic myeloblasts or MDS [5]. We evaluated 60 bone marrow and one peripheral blood samples in order to evaluate the diagnostic utility of TIM3 fl ow cytometric expression in separating non-neoplastic and MDS myeloblast populations.Th e study cohort consisted of 17 untreated cases of MDS (four refractory anemia with excess blasts-2, two refractory anemia with excess blasts-1, one MDS-unclassifi able, four refractory cytopenia with multilineage dysplasia, two refractory anemia and four therapy-related MDS), three cases of MDS with ongoing treatment within the last 2 months (with decitabine, azacitidine or induction chemotherapy), 22 non-neoplastic cases (15 with a history of non-MDS related cytopenias, and seven negative staging bone marrows for lymphoma) and 19 negative cases with post-AML chemotherapy with a history of cytopenias but no evidence of residual AML. Most of the cases from the latter two categories also served as controls for a previous study evaluating myeloblast TIM3 expression in AML [6]. TIM3 myeloblast expression was evaluated in a similar manner to that previously reported, using an eight-color fl ow cytometry panel: CD14 -fl uorescein isothiocyanate (FITC), TIM3 -phycoerythrin (PE), CD117 -peridinin -chlorophyll protein complex (PerCP)-Cy5, CD13 ϩ CD33 -PE-Cy7, CD34 -allophycocyanin (APC), CD3 -APC-H7, CD56 -V450, CD45 -V500 [6].Here we report that TIM3 is underexpressed in untreated MDS....