Journalartikel
Autorenliste: Capper, David; Jones, David T. W.; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E.; Kratz, Annekathrin; Wefers, Annika K.; Huang, Kristin; Pajtler, Kristian W.; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W.; Lindenberg, Kerstin; Harter, Patrick N.; Braczynski, Anne K.; Plate, Karl H.; Dohmen, Hildegard; Garvalov, Boyan K.; Coras, Roland; Hoelsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J.; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Juergen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brueck, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Haenggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R.; Kohlhof, Patricia; Kristensen, Bjarne W.; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Muehleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G.; Driever, Pablo Hernaiz; Kramm, Christof M.; Mueller, Hermann L.; Rutkowski, Stefan; von Hoff, Katja; Fruehwald, Michael C.; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S.; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Bluemcke, Ingmar; Bendszus, Martin; Debus, Juergen; Huang, Annie; Jabado, Nada; Northcott, Paul A.; Paulus, Werner; Gajjar, Amar; Robinson, Giles W.; Taylor, Michael D.; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A.; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schueller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W.; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M.
Jahr der Veröffentlichung: 2018
Seiten: 469-46+
Zeitschrift: Nature
Bandnummer: 555
Heftnummer: 7697
ISSN: 0028-0836
eISSN: 1476-4687
DOI Link: https://doi.org/10.1038/nature26000
Verlag: Nature Research
Abstract:
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.
Zitierstile
Harvard-Zitierstil: Capper, D., Jones, D., Sill, M., Hovestadt, V., Schrimpf, D., Sturm, D., et al. (2018) DNA methylation-based classification of central nervous system tumours, Nature, 555(7697), pp. 469-46+. https://doi.org/10.1038/nature26000
APA-Zitierstil: Capper, D., Jones, D., Sill, M., Hovestadt, V., Schrimpf, D., Sturm, D., Koelsche, C., Sahm, F., Chavez, L., Reuss, D., Kratz, A., Wefers, A., Huang, K., Pajtler, K., Schweizer, L., Stichel, D., Olar, A., Engel, N., Lindenberg, K., ...Pfister, S. (2018). DNA methylation-based classification of central nervous system tumours. Nature. 555(7697), 469-46+. https://doi.org/10.1038/nature26000
Schlagwörter
CLASS PROBABILITY ESTIMATION; COMPRISE; GLIOMAS; MEDULLOBLASTOMA; Molecular classification; MULTICENTER; SUBGROUPS; SUBSETS