Cargando…

Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma

Risk prediction for meningioma tumors was until recently almost exclusively based on morphological features of the tumor. To improve risk prediction, multiple models have been established that incorporate morphological and molecular features for an integrated risk prediction score. One such model is...

Descripción completa

Detalles Bibliográficos
Autores principales: Hielscher, Thomas, Sill, Martin, Sievers, Philipp, Stichel, Damian, Brandner, Sebastian, Jones, David T. W., von Deimling, Andreas, Sahm, Felix, Maas, Sybren L. N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154374/
https://www.ncbi.nlm.nih.gov/pubmed/36377252
http://dx.doi.org/10.1111/bpa.13132
_version_ 1785036113672404992
author Hielscher, Thomas
Sill, Martin
Sievers, Philipp
Stichel, Damian
Brandner, Sebastian
Jones, David T. W.
von Deimling, Andreas
Sahm, Felix
Maas, Sybren L. N.
author_facet Hielscher, Thomas
Sill, Martin
Sievers, Philipp
Stichel, Damian
Brandner, Sebastian
Jones, David T. W.
von Deimling, Andreas
Sahm, Felix
Maas, Sybren L. N.
author_sort Hielscher, Thomas
collection PubMed
description Risk prediction for meningioma tumors was until recently almost exclusively based on morphological features of the tumor. To improve risk prediction, multiple models have been established that incorporate morphological and molecular features for an integrated risk prediction score. One such model is the integrated molecular‐morphologic meningioma integrated score (IntS), which allocates points to the histological grade, epigenetic methylation family and specific copy‐number variations. After publication of the IntS, questions arose in the neuropathological community about the practical and clinical implementation of the IntS, specifically regarding the calling of CNVs, the applicability of the newly available version (v12.5) of the brain tumor classifier and the need for incorporation of TERT‐promoter and CDKN2A/B status analysis in the IntS calculation. To investigate and validate these questions additional analyses of the discovery (n = 514), retrospective validation (n = 184) and prospective validation (n = 287) cohorts used for IntS discovery and validation were performed. Our findings suggest that any loss over 5% of the chromosomal arm suffices for the calling of a CNV, that input from the v12.5 classifier is as good or better than the dedicated meningioma classifier (v2.4) and that there is most likely no need for additional testing for TERT‐promoter mutations and/or homozygous losses of CDKN2A/B when defining the IntS for an individual patient. The findings from this study help facilitate the clinical implementation of IntS‐based risk prediction for meningioma patients.
format Online
Article
Text
id pubmed-10154374
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-101543742023-05-04 Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma Hielscher, Thomas Sill, Martin Sievers, Philipp Stichel, Damian Brandner, Sebastian Jones, David T. W. von Deimling, Andreas Sahm, Felix Maas, Sybren L. N. Brain Pathol Research Articles Risk prediction for meningioma tumors was until recently almost exclusively based on morphological features of the tumor. To improve risk prediction, multiple models have been established that incorporate morphological and molecular features for an integrated risk prediction score. One such model is the integrated molecular‐morphologic meningioma integrated score (IntS), which allocates points to the histological grade, epigenetic methylation family and specific copy‐number variations. After publication of the IntS, questions arose in the neuropathological community about the practical and clinical implementation of the IntS, specifically regarding the calling of CNVs, the applicability of the newly available version (v12.5) of the brain tumor classifier and the need for incorporation of TERT‐promoter and CDKN2A/B status analysis in the IntS calculation. To investigate and validate these questions additional analyses of the discovery (n = 514), retrospective validation (n = 184) and prospective validation (n = 287) cohorts used for IntS discovery and validation were performed. Our findings suggest that any loss over 5% of the chromosomal arm suffices for the calling of a CNV, that input from the v12.5 classifier is as good or better than the dedicated meningioma classifier (v2.4) and that there is most likely no need for additional testing for TERT‐promoter mutations and/or homozygous losses of CDKN2A/B when defining the IntS for an individual patient. The findings from this study help facilitate the clinical implementation of IntS‐based risk prediction for meningioma patients. John Wiley and Sons Inc. 2022-11-14 /pmc/articles/PMC10154374/ /pubmed/36377252 http://dx.doi.org/10.1111/bpa.13132 Text en © 2022 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Hielscher, Thomas
Sill, Martin
Sievers, Philipp
Stichel, Damian
Brandner, Sebastian
Jones, David T. W.
von Deimling, Andreas
Sahm, Felix
Maas, Sybren L. N.
Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
title Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
title_full Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
title_fullStr Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
title_full_unstemmed Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
title_short Clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
title_sort clinical implementation of integrated molecular‐morphologic risk prediction for meningioma
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154374/
https://www.ncbi.nlm.nih.gov/pubmed/36377252
http://dx.doi.org/10.1111/bpa.13132
work_keys_str_mv AT hielscherthomas clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT sillmartin clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT sieversphilipp clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT sticheldamian clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT brandnersebastian clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT jonesdavidtw clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT vondeimlingandreas clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT sahmfelix clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma
AT maassybrenln clinicalimplementationofintegratedmolecularmorphologicriskpredictionformeningioma