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ORIGINAL RESEARCH article
Front. Oncol.
Sec. Neuro-Oncology and Neurosurgical Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1568040
This article is part of the Research TopicInnovative Strategies in Overcoming Glioblastoma: Advancements in Treatment and ResearchView all articles
Nontargeted Metabolomics Uncovering Metabolite Signatures in Glioblastoma: A Preliminary Study on Candidate Biomarker Discovery for IDH Subtyping and Survival Prediction
Provisionally accepted- 1Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
- 2First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China
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Background: Currently, there are no established tumor-derived metabolic biomarkers in clinical practice that can simultaneously differentiate among nontumorous brain tissues, isocitrate dehydrogenase (IDH) wild-type glioblastomas (GBMs), and IDH mutant GBMs, or accurately predict patient survival. The aim of this study was to identify GBM biomarkers for molecular classification and survival prediction via nontargeted metabolomics.Methods: Brain tissue samples from nontumors, IDH-mutant GBMs, and IDH-wild-type GBMs were analyzed via liquid chromatography-mass spectrometry (LC-MS). Metabolites for molecular classification and survival prediction were identified via sparse partial leastsquares discriminant analysis (sPLS-DA) and extreme gradient boosting (XGBoost) models, respectively. Both sets of metabolites were then validated via bootstrap resampling. The biomarkers for survival prediction were further validated using an independent metabolomics dataset.In total, 185 human-derived metabolites were identified with high confidence levels.Two non-overlapping sets of 11 candidate biomarkers for molecular subtyping and survival prediction were screened out. In the validation models for molecular subtyping, the random forest model achieved the highest accuracy (0.787, 95% CI: 0.780-0.795) and a Kappa value of 0.681. The Cox proportional hazards regression model established based on cholic acid and citrulline had an AUC of 0.942 (95% CI: 0.920-0.956) at 84 days and an AUC of 0.812 (95% CI: 0.746-0.826) at 297 days.This exploratory study identified potential metabolic biomarkers for GBM subtyping and prognosis prediction. However, further validation in large-scale clinical studies and mechanistic investigations are needed to confirm their applicability and reliability.
Keywords: Glioblastoma, Isocitrate Dehydrogenase, Molecular classification, biomarkers, Survival risk prediction
Received: 28 Jan 2025; Accepted: 16 Apr 2025.
Copyright: © 2025 Peng, Chen, Li, Dong, Zhu, Su, Zhang and Fang. 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) or licensor 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.
* Correspondence: Kui Fang, Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.