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