52 research outputs found

    Silencing and Un-silencing of Tetracycline-Controlled Genes in Neurons

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    To identify the underlying reason for the controversial performance of tetracycline (Tet)-controlled regulated gene expression in mammalian neurons, we investigated each of the three components that comprise the Tet inducible systems, namely tetracyclines as inducers, tetracycline-transactivator (tTA) and reverse tTA (rtTA), and tTA-responsive promoters (Ptets). We have discovered that stably integrated Ptet becomes functionally silenced in the majority of neurons when it is inactive during development. Ptet silencing can be avoided when it is either not integrated in the genome or stably-integrated with basal activity. Moreover, long-term, high transactivator levels in neurons can often overcome integration-induced Ptet gene silencing, possibly by inducing promoter accessibility

    The 5th edition of the World Health Organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms

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    The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions

    Implications of TP53 allelic state for genome stability, clinical presentation and outcomes in myelodysplastic syndromes

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    Tumor protein p53 (TP53) is the most frequently mutated gene in cancer1,2. In patients with myelodysplastic syndromes (MDS), TP53 mutations are associated with high-risk disease3,4, rapid transformation to acute myeloid leukemia (AML)5, resistance to conventional therapies6–8 and dismal outcomes9. Consistent with the tumor-suppressive role of TP53, patients harbor both mono- and biallelic mutations10. However, the biological and clinical implications of TP53 allelic state have not been fully investigated in MDS or any other cancer type. We analyzed 3,324 patients with MDS for TP53 mutations and allelic imbalances and delineated two subsets of patients with distinct phenotypes and outcomes. One-third of TP53-mutated patients had monoallelic mutations whereas two-thirds had multiple hits (multi-hit) consistent with biallelic targeting. Established associations with complex karyotype, few co-occurring mutations, high-risk presentation and poor outcomes were specific to multi-hit patients only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System (IPSS-R)11. Surprisingly, monoallelic patients did not differ from TP53 wild-type patients in outcomes and response to therapy. This study shows that consideration of TP53 allelic state is critical for diagnostic and prognostic precision in MDS as well as in future correlative studies of treatment response

    CARMENES: high-resolution spectra and precise radial velocities in the red and infrared

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    SPIE Astronomical Telescopes + Instrumentation (2018, Austin, Texas, United States

    Improving Prognostic Modeling in Myelodysplastic Syndromes

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    Myelodysplastic syndromes (MDSs) are a heterogeneous group of disorders characterized by the accumulation of complex genetic alterations that drive disease pathogenesis and outcome. Several prognostic models have been developed over the last two decades to risk stratify patients with MDS. These models mainly used clinical variables including blast percentage, cytopenias, cytogenetics, transfusion dependency, and age. Recently, somatic mutations in specific genes have been shown to impact overall survival in MDS and can be incorporated into established prognostic models to improve their predictive abilities. Here, we review the advantages and disadvantages of established prognostic models in MDS and the impact of emerging data regarding the incorporation of somatic mutations in risk stratification
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