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The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care
BACKGROUND: Molecular signatures are being increasingly incorporated into cancer classification systems. DNA methylation-based central nervous system (CNS) tumor classification is being recognized as having the potential to aid in cases of difficult histopathological diagnoses. Here, we present our...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896594/ https://www.ncbi.nlm.nih.gov/pubmed/31806041 http://dx.doi.org/10.1186/s13148-019-0766-2 |
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author | Karimi, Shirin Zuccato, Jeffrey A. Mamatjan, Yasin Mansouri, Sheila Suppiah, Suganth Nassiri, Farshad Diamandis, Phedias Munoz, David G. Aldape, Kenneth D. Zadeh, Gelareh |
author_facet | Karimi, Shirin Zuccato, Jeffrey A. Mamatjan, Yasin Mansouri, Sheila Suppiah, Suganth Nassiri, Farshad Diamandis, Phedias Munoz, David G. Aldape, Kenneth D. Zadeh, Gelareh |
author_sort | Karimi, Shirin |
collection | PubMed |
description | BACKGROUND: Molecular signatures are being increasingly incorporated into cancer classification systems. DNA methylation-based central nervous system (CNS) tumor classification is being recognized as having the potential to aid in cases of difficult histopathological diagnoses. Here, we present our institutional clinical experience in integrating a DNA-methylation-based classifier into clinical practice and report its impact on CNS tumor patient diagnosis and treatment. METHODS: Prospective case review was undertaken at CNS tumor board discussions over a 3-year period and 55 tumors with a diagnosis that was not certain to two senior neuropathologists were recommended for methylation profiling based on diagnostic needs. Tumor classification, calibrated scores, and copy number variant (CNV) plots were obtained for all 55 cases. These results were integrated with histopathological findings to reach a final diagnosis. We retrospectively reviewed each patient's clinical course to determine final neuro-pathology diagnoses and the impact of methylation profiling on their clinical management, with a focus on changes that were made to treatment decisions. RESULTS: Following methylation profiling, 46 of the 55 (84%) challenging cases received a clinically relevant diagnostic alteration, with two-thirds having a change in the histopathological diagnosis and the other one-third obtaining clinically important molecular diagnostic or subtyping alterations. WHO grading changed by 27% with two-thirds receiving a higher grade. Patient care was directly changed in 15% of all cases with major changes in clinical decision-making being made for these patients to avoid unnecessary or insufficient treatment. CONCLUSIONS: The integration of methylation-based CNS tumor classification into diagnostics has a substantial clinical benefit for patients with challenging CNS tumors while also avoiding unnecessary health care costs. The clinical impact shown here may prompt the expanded use of DNA methylation profiling for CNS tumor diagnostics within prominent neuro-oncology centers globally. |
format | Online Article Text |
id | pubmed-6896594 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68965942019-12-11 The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care Karimi, Shirin Zuccato, Jeffrey A. Mamatjan, Yasin Mansouri, Sheila Suppiah, Suganth Nassiri, Farshad Diamandis, Phedias Munoz, David G. Aldape, Kenneth D. Zadeh, Gelareh Clin Epigenetics Research BACKGROUND: Molecular signatures are being increasingly incorporated into cancer classification systems. DNA methylation-based central nervous system (CNS) tumor classification is being recognized as having the potential to aid in cases of difficult histopathological diagnoses. Here, we present our institutional clinical experience in integrating a DNA-methylation-based classifier into clinical practice and report its impact on CNS tumor patient diagnosis and treatment. METHODS: Prospective case review was undertaken at CNS tumor board discussions over a 3-year period and 55 tumors with a diagnosis that was not certain to two senior neuropathologists were recommended for methylation profiling based on diagnostic needs. Tumor classification, calibrated scores, and copy number variant (CNV) plots were obtained for all 55 cases. These results were integrated with histopathological findings to reach a final diagnosis. We retrospectively reviewed each patient's clinical course to determine final neuro-pathology diagnoses and the impact of methylation profiling on their clinical management, with a focus on changes that were made to treatment decisions. RESULTS: Following methylation profiling, 46 of the 55 (84%) challenging cases received a clinically relevant diagnostic alteration, with two-thirds having a change in the histopathological diagnosis and the other one-third obtaining clinically important molecular diagnostic or subtyping alterations. WHO grading changed by 27% with two-thirds receiving a higher grade. Patient care was directly changed in 15% of all cases with major changes in clinical decision-making being made for these patients to avoid unnecessary or insufficient treatment. CONCLUSIONS: The integration of methylation-based CNS tumor classification into diagnostics has a substantial clinical benefit for patients with challenging CNS tumors while also avoiding unnecessary health care costs. The clinical impact shown here may prompt the expanded use of DNA methylation profiling for CNS tumor diagnostics within prominent neuro-oncology centers globally. BioMed Central 2019-12-05 /pmc/articles/PMC6896594/ /pubmed/31806041 http://dx.doi.org/10.1186/s13148-019-0766-2 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Karimi, Shirin Zuccato, Jeffrey A. Mamatjan, Yasin Mansouri, Sheila Suppiah, Suganth Nassiri, Farshad Diamandis, Phedias Munoz, David G. Aldape, Kenneth D. Zadeh, Gelareh The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
title | The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
title_full | The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
title_fullStr | The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
title_full_unstemmed | The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
title_short | The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
title_sort | central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896594/ https://www.ncbi.nlm.nih.gov/pubmed/31806041 http://dx.doi.org/10.1186/s13148-019-0766-2 |
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