Journal Article DKFZ-2018-00343

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DNA methylation-based classification of central nervous system tumours.

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2018
Nature Publ. Group London [u.a.]

Nature <London> 555(7697), 469 - 474 () [10.1038/nature26000]
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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.

Classification:

Contributing Institute(s):
  1. KKE Neuropathologie (G380)
  2. DKTK Heidelberg (L101)
  3. DKTK Berlin (L201)
  4. B062 Pädiatrische Neuroonkologie (B062)
  5. C060 Biostatistik (C060)
  6. B060 Molekulare Genetik (B060)
  7. DKTK Frankfurt (L501)
  8. Microarrays (W110)
  9. KKE Pädiatrische Onkologie (G340)
  10. DKTK Essen (L401)
Research Program(s):
  1. 312 - Functional and structural genomics (POF3-312) (POF3-312)

Appears in the scientific report 2018
Database coverage:
Medline ; BIOSIS Previews ; Current Contents - Agriculture, Biology and Environmental Sciences ; Current Contents - Life Sciences ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; IF >= 30 ; JCR ; NCBI Molecular Biology Database ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection ; Zoological Record
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 Record created 2018-04-10, last modified 2024-02-29



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