Cargando…

Brain Tumor Classification by Methylation Profile

The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients....

Descripción completa

Detalles Bibliográficos
Autores principales: Park, Jin Woo, Lee, Kwanghoon, Kim, Eric Eunshik, Kim, Seong-Ik, Park, Sung-Hye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Medical Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627723/
https://www.ncbi.nlm.nih.gov/pubmed/37935168
http://dx.doi.org/10.3346/jkms.2023.38.e356
_version_ 1785131584389644288
author Park, Jin Woo
Lee, Kwanghoon
Kim, Eric Eunshik
Kim, Seong-Ik
Park, Sung-Hye
author_facet Park, Jin Woo
Lee, Kwanghoon
Kim, Eric Eunshik
Kim, Seong-Ik
Park, Sung-Hye
author_sort Park, Jin Woo
collection PubMed
description The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients. The methylation classifier can be used to perform classification on tumor samples with diagnostic difficulties due to ambiguous histology or mismatch between histopathology and molecular signatures, i.e., not otherwise specified (NOS) cases or not elsewhere classified (NEC) cases, aiding in pathological decision-making. Here, the authors elucidate upon the application of a methylation classifier as a tool to mitigate the inherent complexities associated with the pathological evaluation of brain tumors, even when pathologists are experts in histopathological diagnosis and have access to enough molecular genetic information. Also, it should be emphasized that methylome cannot classify all types of brain tumors, and it often produces erroneous matches even with high matching scores, so, excessive trust is prohibited. The primary issue is the considerable difficulty in obtaining reference data regarding the methylation profile of each type of brain tumor. This challenge is further amplified when dealing with recently identified novel types or subtypes of brain tumors, as such data are not readily accessible through open databases or authors of publications. An additional obstacle arises from the fact that methylation classifiers are primarily research-based, leading to the unavailability of charging patients. It is important to note that the application of methylation classifiers may require specialized laboratory techniques and expertise in DNA methylation analysis.
format Online
Article
Text
id pubmed-10627723
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher The Korean Academy of Medical Sciences
record_format MEDLINE/PubMed
spelling pubmed-106277232023-11-07 Brain Tumor Classification by Methylation Profile Park, Jin Woo Lee, Kwanghoon Kim, Eric Eunshik Kim, Seong-Ik Park, Sung-Hye J Korean Med Sci Review Article The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients. The methylation classifier can be used to perform classification on tumor samples with diagnostic difficulties due to ambiguous histology or mismatch between histopathology and molecular signatures, i.e., not otherwise specified (NOS) cases or not elsewhere classified (NEC) cases, aiding in pathological decision-making. Here, the authors elucidate upon the application of a methylation classifier as a tool to mitigate the inherent complexities associated with the pathological evaluation of brain tumors, even when pathologists are experts in histopathological diagnosis and have access to enough molecular genetic information. Also, it should be emphasized that methylome cannot classify all types of brain tumors, and it often produces erroneous matches even with high matching scores, so, excessive trust is prohibited. The primary issue is the considerable difficulty in obtaining reference data regarding the methylation profile of each type of brain tumor. This challenge is further amplified when dealing with recently identified novel types or subtypes of brain tumors, as such data are not readily accessible through open databases or authors of publications. An additional obstacle arises from the fact that methylation classifiers are primarily research-based, leading to the unavailability of charging patients. It is important to note that the application of methylation classifiers may require specialized laboratory techniques and expertise in DNA methylation analysis. The Korean Academy of Medical Sciences 2023-10-23 /pmc/articles/PMC10627723/ /pubmed/37935168 http://dx.doi.org/10.3346/jkms.2023.38.e356 Text en © 2023 The Korean Academy of Medical Sciences. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Park, Jin Woo
Lee, Kwanghoon
Kim, Eric Eunshik
Kim, Seong-Ik
Park, Sung-Hye
Brain Tumor Classification by Methylation Profile
title Brain Tumor Classification by Methylation Profile
title_full Brain Tumor Classification by Methylation Profile
title_fullStr Brain Tumor Classification by Methylation Profile
title_full_unstemmed Brain Tumor Classification by Methylation Profile
title_short Brain Tumor Classification by Methylation Profile
title_sort brain tumor classification by methylation profile
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627723/
https://www.ncbi.nlm.nih.gov/pubmed/37935168
http://dx.doi.org/10.3346/jkms.2023.38.e356
work_keys_str_mv AT parkjinwoo braintumorclassificationbymethylationprofile
AT leekwanghoon braintumorclassificationbymethylationprofile
AT kimericeunshik braintumorclassificationbymethylationprofile
AT kimseongik braintumorclassificationbymethylationprofile
AT parksunghye braintumorclassificationbymethylationprofile