TY  - JOUR
AV  - public
IS  - 5
EP  - 517
SP  - 510
N2  - Brain tumours are the most common tumour?related cause of death in young people. Survivors are at risk of significant disability, at least in part related to the effects of treatment. Therefore, there is a need for a precise diagnosis that stratifies patients for the most suitable treatment, matched to the underlying biology of their tumour. Although traditional histopathology has been accurate in predicting treatment responses in many cases, molecular profiling has revealed a remarkable, previously unappreciated, level of biological complexity in the classification of these tumours. Among different molecular technologies, DNA methylation profiling has had the most pronounced impact on brain tumour classification. Furthermore, using machine learning?based algorithms, DNA methylation profiling is changing diagnostic practice. This can be regarded as an exemplar for how molecular pathology can influence diagnostic practice and illustrates some of the unanticipated benefits and risks. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
KW  - CNS tumour
KW  - s medulloblastoma
KW  -  neuroblastoma
KW  -  ependymoma
KW  -  astrocytoma
KW  -  glioblastoma
KW  -  Ewing's tumou
KW  - r classification
KW  -  pathology
KW  -  DNA methylation profiling
A1  - Pickles, JC
A1  - Stone, TJ
A1  - Jacques, TS
VL  - 250
JF  - The Journal of Pathology
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
TI  - Methylation-based algorithms for diagnosis: experience from neuro-oncology
UR  - https://doi.org/10.1002/path.5397
Y1  - 2020/04//
ID  - discovery10092064
ER  -