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Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors
- Source :
- Frontiers in Neuroscience, Vol 17 (2023)
- Publication Year :
- 2023
- Publisher :
- Frontiers Media S.A., 2023.
-
Abstract
- IntroductionElderly 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.MethodsThe 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.ResultsA 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.ConclusionOur 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.
Details
- Language :
- English
- ISSN :
- 1662453X
- Volume :
- 17
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.41dd0fae770b4382be050667f37d1e22
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fnins.2023.1165823