Studies on the actin-binding protein HS1 in platelets

<p>Abstract</p> <p>Background</p> <p>The platelet cytoskeleton mediates the dramatic change in platelet morphology that takes place upon activation and stabilizes thrombus formation. The Arp2/3 complex plays a vital role in these processes, providing the protrusive force for lamellipodia formation. The Arp2/3 complex is highly regulated by a number of actin-binding proteins including the haematopoietic-specific protein HS1 and its homologue cortactin. The present study investigates the role of HS1 in platelets using HS1^-/-mice.</p> <p>Results</p> <p>The present results demonstrate that HS1 is not required for platelet activation, shape change or aggregation. Platelets from HS1^-/-mice spread normally on a variety of adhesion proteins and have normal F-actin and Arp2/3 complex distributions. Clot retraction, an actin-dependent process, is also normal in these mice. Platelet aggregation and secretion is indistinguishable between knock out and littermates and there is no increase in bleeding using the tail bleeding assay.</p> <p>Conclusion</p> <p>This study concludes that HS1 does not play a major role in platelet function. It is possible that a role for HS1 is masked by the presence of cortactin.</p

Repercussion of megakaryocyte-specific Gata1 Loss on megakaryopoiesis and the hematopoietic precursor compartment

During hematopoiesis, transcriptional programs are essential for the commitment and differentiation of progenitors into the different blood lineages. GATA1 is a transcription factor expressed in several hematopoietic lineages and essential for proper erythropoiesis and megakaryopoiesis. Megakaryocyte-specific genes, such as GP1BA, are known to be directly regulated by GATA1. Mutations in GATA1 can lead to dyserythropoietic anemia and pseudo gray-platelet syndrome. Selective loss of Gata1 expression in adult mice results in macrothrombocytopenia with platelet dysfunction, characterized by an excess of immature megakaryocytes. To specifically analyze the impact of Gata1 loss in mature committed megakaryocytes, we generated Gata1-Lox|Pf4-Cre mice (Gata1cKOMK). Consistent with previous findings, Gata1cKOMK mice are macrothrombocytopenic with platelet dysfunction. Supporting this notion we demonstrate that Gata1 regulates directly the transcription of Syk, a tyrosine kinase that functions downstream of Clec2 and GPVI receptors in megakaryocytes and platelets. Furthermore, we show that Gata1cKOMK mice display an additional aberrant megakaryocyte differentiation stage. Interestingly, these mice present a misbalance of the multipotent progenitor compartment and the erythroid lineage, which translates into compensatory stress erythropoiesis and splenomegaly. Despite the severe thrombocytopenia, Gata1cKOMK mice display a mild reduction of TPO plasma levels, and Gata1cK-OMK megakaryocytes show a mild increase in Pf4 mRNA levels; such a misbalance might be behind the general hematopoietic defects observed, affecting locally normal TPO and Pf4 levels at hematopoietic stem cell niches. © 2016 Meinders et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

DNA methylation-based classification of central nervous system tumours

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challengingwith substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology