التفاصيل البيبلوغرافية
| العنوان: |
DNA methylation‐based classification of glioneuronal tumours synergises with histology and radiology to refine accurate molecular stratification |
| المؤلفون: |
Stone, Thomas J., Mankad, Kshitij, Tan, Ai Peng, Jan, Wajanat, Pickles, Jessica C., Gogou, Maria, Chalker, Jane, Slodkowska, Iwona, Pang, Emily, Kristiansen, Mark, Madhan, Gaganjit K., Forrest, Leysa, Hughes, Deborah, Koutroumanidou, Eleni, Mistry, Talisa, Ogunbiyi, Olumide, Ahmed, Saira W., Cross, J. Helen, Hubank, Mike, Hargrave, Darren, Jacques, Thomas S. |
| المساهمون: |
Brain Tumour Charity, Great Ormond Street Hospital Charity, CHILDREN with CANCER UK, Cancer Research UK, National Institute for Health and Care Research, NIHR Great Ormond Street Hospital Biomedical Research Centre, NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research |
| المصدر: |
Neuropathology and Applied Neurobiology ; volume 49, issue 2 ; ISSN 0305-1846 1365-2990 |
| بيانات النشر: |
Wiley |
| سنة النشر: |
2023 |
| المجموعة: |
Wiley Online Library (Open Access Articles via Crossref) |
| الوصف: |
Aims Glioneuronal tumours (GNTs) are poorly distinguished by their histology and lack robust diagnostic indicators. Previously, we showed that common GNTs comprise two molecularly distinct groups, correlating poorly with histology. To refine diagnosis, we constructed a methylation‐based model for GNT classification, subsequently evaluating standards for molecular stratification by methylation, histology and radiology. Methods We comprehensively analysed methylation, radiology and histology for 83 GNT samples: a training cohort of 49, previously classified into molecularly defined groups by genomic profiles, plus a validation cohort of 34. We identified histological and radiological correlates to molecular classification and constructed a methylation‐based support vector machine (SVM) model for prediction. Subsequently, we contrasted methylation, radiological and histological classifications in validation GNTs. Results By methylation clustering, all training and 23/34 validation GNTs segregated into two groups, the remaining 11 clustering alongside control cortex. Histological review identified prominent astrocytic/oligodendrocyte‐like components, dysplastic neurons and a specific glioneuronal element as discriminators between groups. However, these were present in only a subset of tumours. Radiological review identified location, margin definition, enhancement and T2 FLAIR‐rim sign as discriminators. When validation GNTs were classified by SVM, 22/23 classified correctly, comparing favourably against histology and radiology that resolved 17/22 and 15/21, respectively, where data were available for comparison. Conclusions Diagnostic criteria inadequately reflect glioneuronal tumour biology, leaving a proportion unresolvable. In the largest cohort of molecularly defined glioneuronal tumours, we develop molecular, histological and radiological approaches for biologically meaningful classification and demonstrate almost all cases are resolvable, emphasising the importance of an integrated diagnostic ... |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| DOI: |
10.1111/nan.12894 |
| الإتاحة: |
https://doi.org/10.1111/nan.12894Test |
| حقوق: |
http://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.11729BB8 |
| قاعدة البيانات: |
BASE |
