Cargando…
Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors
INTRODUCTION: Elderly glioblastoma (GBM) patients is characterized by high incidence and poor prognosis. Currently, however, there is still a lack of adequate molecular characterization of elderly GBM patients. The fifth edition of the WHO Classification of Central Nervous System Tumors (WHO5) gives...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10288210/ https://www.ncbi.nlm.nih.gov/pubmed/37360159 http://dx.doi.org/10.3389/fnins.2023.1165823 |
_version_ | 1785062032348807168 |
---|---|
author | Wang, Yaning Li, Junlin Cao, Yaning Chen, Wenlin Xing, Hao Guo, Xiaopeng Shi, Yixin Wang, Yuekun Liang, Tingyu Ye, Liguo Liu, Delin Yang, Tianrui Wang, Yu Ma, Wenbin |
author_facet | Wang, Yaning Li, Junlin Cao, Yaning Chen, Wenlin Xing, Hao Guo, Xiaopeng Shi, Yixin Wang, Yuekun Liang, Tingyu Ye, Liguo Liu, Delin Yang, Tianrui Wang, Yu Ma, Wenbin |
author_sort | Wang, Yaning |
collection | PubMed |
description | INTRODUCTION: Elderly glioblastoma (GBM) patients is characterized by high incidence and poor prognosis. Currently, however, there is still a lack of adequate molecular characterization of elderly GBM patients. The fifth edition of the WHO Classification of Central Nervous System Tumors (WHO5) gives a new classification approach for GBM, and the molecular characteristics of elderly GBM patients need to be investigated under this new framework. METHODS: The clinical and radiological features of patients with different classifications and different ages were compared. Potential prognostic molecular markers in elderly GBM patients under the WHO5 classification were found using Univariate Cox regression and Kaplan–Meier survival analysis. RESULTS: A total of 226 patients were included in the study. The prognostic differences between younger and elderly GBM patients were more pronounced under the WHO5 classification. Neurological impairment was more common in elderly patients (p = 0.001), while intracranial hypertension (p = 0.034) and epilepsy (p = 0.038) were more common in younger patients. Elderly patients were more likely to have higher Ki-67(p = 0.013), and in elderly WHO5 GBM patients, KMT5B (p = 0.082), KRAS (p = 0.1) and PPM1D (p = 0.055) were each associated with overall survival (OS). Among them, KRAS and PPM1D were found to be prognostic features unique to WHO5 elderly GBM patients. CONCLUSION: Our study demonstrates that WHO5 classification can better distinguish the prognosis of elderly and younger GBM. Furthermore, KRAS and PPM1D may be potential prognostic predictors in WHO5 elderly GBM patients. The specific mechanism of these two genes in elderly GBM remains to be further studied. |
format | Online Article Text |
id | pubmed-10288210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102882102023-06-24 Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors Wang, Yaning Li, Junlin Cao, Yaning Chen, Wenlin Xing, Hao Guo, Xiaopeng Shi, Yixin Wang, Yuekun Liang, Tingyu Ye, Liguo Liu, Delin Yang, Tianrui Wang, Yu Ma, Wenbin Front Neurosci Neuroscience INTRODUCTION: Elderly glioblastoma (GBM) patients is characterized by high incidence and poor prognosis. Currently, however, there is still a lack of adequate molecular characterization of elderly GBM patients. The fifth edition of the WHO Classification of Central Nervous System Tumors (WHO5) gives a new classification approach for GBM, and the molecular characteristics of elderly GBM patients need to be investigated under this new framework. METHODS: The clinical and radiological features of patients with different classifications and different ages were compared. Potential prognostic molecular markers in elderly GBM patients under the WHO5 classification were found using Univariate Cox regression and Kaplan–Meier survival analysis. RESULTS: A total of 226 patients were included in the study. The prognostic differences between younger and elderly GBM patients were more pronounced under the WHO5 classification. Neurological impairment was more common in elderly patients (p = 0.001), while intracranial hypertension (p = 0.034) and epilepsy (p = 0.038) were more common in younger patients. Elderly patients were more likely to have higher Ki-67(p = 0.013), and in elderly WHO5 GBM patients, KMT5B (p = 0.082), KRAS (p = 0.1) and PPM1D (p = 0.055) were each associated with overall survival (OS). Among them, KRAS and PPM1D were found to be prognostic features unique to WHO5 elderly GBM patients. CONCLUSION: Our study demonstrates that WHO5 classification can better distinguish the prognosis of elderly and younger GBM. Furthermore, KRAS and PPM1D may be potential prognostic predictors in WHO5 elderly GBM patients. The specific mechanism of these two genes in elderly GBM remains to be further studied. Frontiers Media S.A. 2023-06-09 /pmc/articles/PMC10288210/ /pubmed/37360159 http://dx.doi.org/10.3389/fnins.2023.1165823 Text en Copyright © 2023 Wang, Li, Cao, Chen, Xing, Guo, Shi, Wang, Liang, Ye, Liu, Yang, Wang and Ma. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Wang, Yaning Li, Junlin Cao, Yaning Chen, Wenlin Xing, Hao Guo, Xiaopeng Shi, Yixin Wang, Yuekun Liang, Tingyu Ye, Liguo Liu, Delin Yang, Tianrui Wang, Yu Ma, Wenbin Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors |
title | Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors |
title_full | Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors |
title_fullStr | Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors |
title_full_unstemmed | Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors |
title_short | Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors |
title_sort | characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 who classification of central nervous system tumors |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10288210/ https://www.ncbi.nlm.nih.gov/pubmed/37360159 http://dx.doi.org/10.3389/fnins.2023.1165823 |
work_keys_str_mv | AT wangyaning characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT lijunlin characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT caoyaning characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT chenwenlin characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT xinghao characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT guoxiaopeng characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT shiyixin characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT wangyuekun characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT liangtingyu characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT yeliguo characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT liudelin characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT yangtianrui characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT wangyu characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors AT mawenbin characteristicanalysisandidentificationofnovelmolecularbiomarkersinelderlyglioblastomapatientsusingthe2021whoclassificationofcentralnervoussystemtumors |