410 research outputs found

    A Genome-wide screen identifies frequently methylated genes in haematological and epithelial cancers

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    <p>Abstract</p> <p>Background</p> <p>Genetic as well as epigenetic alterations are a hallmark of both epithelial and haematological malignancies. High throughput screens are required to identify epigenetic markers that can be useful for diagnostic and prognostic purposes across malignancies.</p> <p>Results</p> <p>Here we report for the first time the use of the MIRA assay (methylated CpG island recovery assay) in combination with genome-wide CpG island arrays to identify epigenetic molecular markers in childhood acute lymphoblastic leukemia (ALL) on a genome-wide scale. We identified 30 genes demonstrating methylation frequencies of ≥25% in childhood ALL, nine genes showed significantly different methylation frequencies in B vs T-ALL. For majority of the genes expression could be restored in methylated leukemia lines after treatment with 5-azaDC. Forty-four percent of the genes represent targets of the polycomb complex. In chronic myeloid leukemia (CML) two of the genes, (<it>TFAP2A </it>and <it>EBF2)</it>, demonstrated increased methylation in blast crisis compared to chronic phase (P < 0.05). Furthermore hypermethylation of an autophagy related gene <it>ATG16L2 </it>was associated with poorer prognosis in terms of molecular response to Imatinib treatment. Lastly we demonstrated that ten of these genes were also frequently methylated in common epithelial cancers.</p> <p>Conclusion</p> <p>In summary we have identified a large number of genes showing frequent methylation in childhood ALL, methylation status of two of these genes is associated with advanced disease in CML and methylation status of another gene is associated with prognosis. In addition a subset of these genes may act as epigenetic markers across hematological malignancies as well as common epithelial cancers.</p

    Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

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    The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac
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