Ontology type: schema:ScholarlyArticle
2018-03
AUTHORSDavid Capper, David T. W. Jones, Martin Sill, Volker Hovestadt, Daniel Schrimpf, Dominik Sturm, Christian Koelsche, Felix Sahm, Lukas Chavez, David E. Reuss, Annekathrin Kratz, Annika K. Wefers, Kristin Huang, Kristian W. Pajtler, Leonille Schweizer, Damian Stichel, Adriana Olar, Nils W. Engel, Kerstin Lindenberg, Patrick N. Harter, Anne K. Braczynski, Karl H. Plate, Hildegard Dohmen, Boyan K. Garvalov, Roland Coras, Annett Hölsken, Ekkehard Hewer, Melanie Bewerunge-Hudler, Matthias Schick, Roger Fischer, Rudi Beschorner, Jens Schittenhelm, Ori Staszewski, Khalida Wani, Pascale Varlet, Melanie Pages, Petra Temming, Dietmar Lohmann, Florian Selt, Hendrik Witt, Till Milde, Olaf Witt, Eleonora Aronica, Felice Giangaspero, Elisabeth Rushing, Wolfram Scheurlen, Christoph Geisenberger, Fausto J. Rodriguez, Albert Becker, Matthias Preusser, Christine Haberler, Rolf Bjerkvig, Jane Cryan, Michael Farrell, Martina Deckert, Jürgen Hench, Stephan Frank, Jonathan Serrano, Kasthuri Kannan, Aristotelis Tsirigos, Wolfgang Brück, Silvia Hofer, Stefanie Brehmer, Marcel Seiz-Rosenhagen, Daniel Hänggi, Volkmar Hans, Stephanie Rozsnoki, Jordan R. Hansford, Patricia Kohlhof, Bjarne W. Kristensen, Matt Lechner, Beatriz Lopes, Christian Mawrin, Ralf Ketter, Andreas Kulozik, Ziad Khatib, Frank Heppner, Arend Koch, Anne Jouvet, Catherine Keohane, Helmut Mühleisen, Wolf Mueller, Ute Pohl, Marco Prinz, Axel Benner, Marc Zapatka, Nicholas G. Gottardo, Pablo Hernáiz Driever, Christof M. Kramm, Hermann L. Müller, Stefan Rutkowski, Katja von Hoff, Michael C. Frühwald, Astrid Gnekow, Gudrun Fleischhack, Stephan Tippelt, Gabriele Calaminus, Camelia-Maria Monoranu, Arie Perry, Chris Jones, Thomas S. Jacques, Bernhard Radlwimmer, Marco Gessi, Torsten Pietsch, Johannes Schramm, Gabriele Schackert, Manfred Westphal, Guido Reifenberger, Pieter Wesseling, Michael Weller, Vincent Peter Collins, Ingmar Blümcke, Martin Bendszus, Jürgen Debus, Annie Huang, Nada Jabado, Paul A. Northcott, Werner Paulus, Amar Gajjar, Giles W. Robinson, Michael D. Taylor, Zane Jaunmuktane, Marina Ryzhova, Michael Platten, Andreas Unterberg, Wolfgang Wick, Matthias A. Karajannis, Michel Mittelbronn, Till Acker, Christian Hartmann, Kenneth Aldape, Ulrich Schüller, Rolf Buslei, Peter Lichter, Marcel Kool, Christel Herold-Mende, David W. Ellison, Martin Hasselblatt, Matija Snuderl, Sebastian Brandner, Andrey Korshunov, Andreas von Deimling, Stefan M. Pfister
ABSTRACTAccurate 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 challenging-with 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. More... »
PAGES469
http://scigraph.springernature.com/pub.10.1038/nature26000
DOIhttp://dx.doi.org/10.1038/nature26000
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1101533700
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/29539639
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JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nature26000'
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This table displays all metadata directly associated to this object as RDF triples.
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