Comprehensive molecular and clinical characterization of NUP98 fusions in pediatric acute myeloid leukemia

NUP98 fusions comprise a family of rare recurrent alterations in AML, associated with adverse outcomes. In order to define the underlying biology and clinical implications of this family of fusions, we performed comprehensive transcriptome, epigenome, and immunophenotypic profiling of 2,235 children and young adults with AML and identified 160 NUP98 rearrangements (7.2%), including 108 NUP98-NSD1 (4.8%), 32 NUP98-KDM5A (1.4%) and 20 NUP98-X cases (0.9%) with 13 different fusion partners. Fusion partners defined disease characteristics and biology; patients with NUP98-NSD1 or NUP98-KDM5A had distinct immunophenotypic, transcriptomic, and epigenomic profiles. Unlike the two most prevalent NUP98 fusions, NUP98-X variants are typically not cryptic. Furthermore, NUP98-X cases are associated with WT1 mutations, and have epigenomic profiles that resemble either NUP98-NSD1 or NUP98-KDM5A. Cooperating FLT3-ITD and WT1 mutations define NUP98-NSD1, and chromosome 13 aberrations are highly enriched in NUP98-KDM5A. Importantly, we demonstrate that NUP98 fusions portend dismal overall survival, with the noteworthy exception of patients bearing abnormal chromosome 13 (clinicaltrials gov. Identifiers: NCT00002798, NCT00070174, NCT00372593, NCT01371981).</p

Antibodies against viral nucleo-, phospho-, and X protein contribute to serological diagnosis of fatal Borna disease virus 1 infections

Borna disease virus 1 (BoDV-1) causes rare but often fatal encephalitis in humans. Late diagnosis prohibits an experimental therapeutic approach. Here, we report a recent case of fatal BoDV-1 infection diagnosed on day 12 after hospitalization by detection of BoDV-1 RNA in the cerebrospinal fluid. In a retrospective analysis, we detect BoDV-1 RNA 1 day after hospital admission when the cell count in the cerebrospinal fluid is still normal. We develop a new ELISA using recombinant BoDV-1 nucleoprotein, phosphoprotein, and accessory protein X to detect seroconversion on day 12. Antibody responses are also shown in seven previously confirmed cases. The individual BoDV-1 antibody profiles show variability, but the usage of three different BoDV-1 antigens results in a more sensitive diagnostic tool. Our findings demonstrate that early detection of BoDV-1 RNA in cerebrospinal fluid and the presence of antibodies against at least two different viral antigens contribute to BoDV-1 diagnosis. Physicians in endemic regions should consider BoDV-1 infection in cases of unclear encephalopathy and initiate appropriate diagnostics at an early stage

ARTICLE Immunophenotypic analysis of erythroid dysplasia in myelodysplastic syndromes. A report from the IMDSFlow working group © Ferrata Storti Foundation

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

Multiparameter flow cytometry in the evaluation of myelodysplasia: Analytical issues: Recommendations from the European LeukemiaNet/International Myelodysplastic Syndrome Flow Cytometry Working Group

Multiparameter flow cytometry (MFC) is one of the essential ancillary methods in bone marrow (BM) investigation of patients with cytopenia and suspected myelodysplastic syndrome (MDS). MFC can also be applied in the follow-up of MDS patients undergoing treatment. This document summarizes recommendations from the International/European Leukemia Net Working Group for Flow Cytometry in Myelodysplastic Syndromes (ELN iMDS Flow) on the analytical issues in MFC for the diagnostic work-up of MDS. Recommendations for the analysis of several BM cell subsets such as myeloid precursors, maturing granulocytic and monocytic components and erythropoiesis are given. A core set of 17 markers identified as independently related to a cytomorphologic diagnosis of myelodysplasia is suggested as mandatory for MFC evaluation of BM in a patient with cytopenia. A myeloid precursor cell (CD34+CD19−) count >3% should be considered immunophenotypically indicative of myelodysplasia. However, MFC results should always be evaluated as part of an integrated hematopathology work-up. Looking forward, several machine-learning-based analytical tools of interest should be applied in parallel to conventional analytical methods to investigate their usefulness in integrated diagnostics, risk stratification, and potentially even in the evaluation of response to therapy, based on MFC data. In addition, compiling large uniform datasets is desirable, as most of the machine-learning-based methods tend to perform better with larger numbers of investigated samples, especially in such a heterogeneous disease as MDS