| Authors: |
Capper, D.; Jones, D. T. W.; Sill, M.; Hovestadt, V.; Schrimpf, D.; Sturm, D.; Koelsche, C.; Sahm, F.; Chavez, L.; Reuss, D. E.; Kratz, A.; Wefers, A. K.; Huang, K.; Pajtler, K. W.; Schweizer, L.; Stichel, D.; Olar, A.; Engel, N. W.; Lindenberg, K.; Harter, P. N.; Braczynski, A. K.; Plate, K. H.; Dohmen, H.; Garvalov, B. K.; Coras, R.; Hölsken, A.; Hewer, E.; Bewerunge-Hudler, M.; Schick, M.; Fischer, R.; Beschorner, R.; Schittenhelm, J.; Staszewski, O.; Wani, K.; Varlet, P.; Pages, M.; Temming, P.; Lohmann, D.; Selt, F.; Witt, H.; Milde, T.; Witt, O.; Aronica, E.; Giangaspero, F.; Rushing, E.; Scheurlen, W.; Geisenberger, C.; Rodriguez, F. J.; Becker, A.; Preusser, M.; Haberler, C.; Bjerkvig, R.; Cryan, J.; Farrell, M.; Deckert, M.; Hench, J.; Frank, S.; Serrano, J.; Kannan, K.; Tsirigos, A.; Brück, W.; Hofer, S.; Brehmer, S.; Seiz-Rosenhagen, M.; Hänggi, D.; Hans, V.; Rozsnoki, S.; Hansford, J. R.; Kohlhof, P.; Kristensen, B. W.; Lechner, M.; Lopes, B.; Mawrin, C.; Ketter, R.; Kulozik, A.; Khatib, Z.; Heppner, F.; Koch, A.; Jouvet, A.; Keohane, C.; Mühleisen, H.; Mueller, W.; Pohl, U.; Prinz, M.; Benner, A.; Zapatka, M.; Gottardo, N. G.; Hernáiz Driever, P.; Kramm, C. M.; Müller, H. L.; Rutkowski, S.; von Hoff, K.; Frühwald, M. C.; Gnekow, A.; Fleischhack, G.; Tippelt, S.; Calaminus, G.; Monoranu, C. M.; Perry, A.; Jones, C.; Jacques, T. S.; Radlwimmer, B.; Gessi, M.; Pietsch, T.; Schramm, J.; Schackert, G.; Westphal, M.; Reifenberger, G.; Wesseling, P.; Weller, M.; Collins, V. P.; Blümcke, I.; Bendszus, M.; Debus, J.; Huang, A.; Jabado, N.; Northcott, P. A.; Paulus, W.; Gajjar, A.; Robinson, G. W.; Taylor, M. D.; Jaunmuktane, Z.; Ryzhova, M.; Platten, M.; Unterberg, A.; Wick, W.; Karajannis, M. A.; Mittelbronn, M.; Acker, T.; Hartmann, C.; Aldape, K.; Schüller, U.; Buslei, R.; Lichter, P.; Kool, M.; Herold-Mende, C.; Ellison, D. W.; Hasselblatt, M.; Snuderl, M.; Brandner, S.; Korshunov, A.; von Deimling, A.; Pfister, S. M. |
| Article Title: |
DNA methylation-based classification of central nervous system tumours |
| 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 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. © 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. |
| Keywords: |
adolescent; adult; child; controlled study; preschool child; aged; major clinical study; methylation; histopathology; diagnostic accuracy; cohort analysis; dna methylation; central nervous system tumor; dna; infant; newborn; tumor; software; tumor classification; tumor diagnosis; classification algorithm; nervous system; online system; diagnostic test accuracy study; world wide web; machine learning; data processing; cancer; human; male; female; priority journal; article
|
| Journal Title: |
Nature
|
| Volume: |
555 |
| Issue: |
7697 |
| ISSN: |
0028-0836 |
| Publisher: |
Nature Publishing Group
|
| Date Published: |
2018-03-22 |
| Start Page: |
469 |
| End Page: |
474 |
| Language: |
English |
| DOI: |
10.1038/nature26000
|
| PROVIDER: |
scopus
|
| PUBMED: |
29539639
|
| PMCID: |
PMC6093218
|
| DOI/URL: |
|
| Notes: |
Article -- Export Date: 1 May 2018 -- Source: Scopus |
