eprintid: 10092064
rev_number: 22
eprint_status: archive
userid: 608
dir: disk0/10/09/20/64
datestamp: 2020-02-27 11:00:42
lastmod: 2021-11-30 22:54:25
status_changed: 2020-02-27 11:00:42
type: article
metadata_visibility: show
creators_name: Pickles, JC
creators_name: Stone, TJ
creators_name: Jacques, TS
title: Methylation-based algorithms for diagnosis: experience from neuro-oncology
ispublished: pub
subjects: GOSH
divisions: UCL
divisions: B02
divisions: D13
divisions: G22
keywords: CNS tumour,s medulloblastoma, neuroblastoma, ependymoma, astrocytoma, glioblastoma, Ewing's tumou,r classification, pathology, DNA methylation profiling
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: 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.
date: 2020-04
date_type: published
official_url: https://doi.org/10.1002/path.5397
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1758320
doi: 10.1002/path.5397
lyricists_name: Jacques, Thomas
lyricists_name: Pickles, Jessica
lyricists_name: Stone, Thomas
lyricists_id: TJACQ32
lyricists_id: JPICK56
lyricists_id: STONE38
actors_name: Jacques, Thomas
actors_id: TJACQ32
actors_role: owner
full_text_status: public
publication: The Journal of Pathology
volume: 250
number: 5
pagerange: 510-517
event_location: England
citation:        Pickles, JC;    Stone, TJ;    Jacques, TS;      (2020)    Methylation-based algorithms for diagnosis: experience from neuro-oncology.                   The Journal of Pathology , 250  (5)   pp. 510-517.    10.1002/path.5397 <https://doi.org/10.1002/path.5397>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10092064/1/Pickles%20et%20al%20final%20version.pdf