Glioblastoma metabolomics: uncovering biomarkers for diagnosis, prognosis and targeted therapy
Abstract Glioblastoma (GBM) is characterized by rapid growth, high molecular heterogeneity, and invasiveness. Specific aggressive factors are represented by MGMT promoter methylation, and IDH mutation status. Current standard-of-care for GBM includes surgical resection, followed by radiotherapy plus...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-08-01
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| Series: | Journal of Experimental & Clinical Cancer Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13046-025-03497-2 |
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| Summary: | Abstract Glioblastoma (GBM) is characterized by rapid growth, high molecular heterogeneity, and invasiveness. Specific aggressive factors are represented by MGMT promoter methylation, and IDH mutation status. Current standard-of-care for GBM includes surgical resection, followed by radiotherapy plus concomitant and adjuvant chemotherapy with temozolomide. However, patients almost invariably succumb due to therapy resistance and disease recurrences. Therefore, novel therapies for GBM are urgently needed to improve patient survival, necessitating the identification of new diagnostic and prognostic biomarkers, as well as therapeutic targets. In this context, “omics” technologies, such as metabolomics and lipidomics, can generate vast amounts of data useful to elucidate the complex molecular mechanisms driving this disease, and discover potential novel biomarkers and therapeutic targets. Our review aims to highlight the current literature on the metabolomics studies conducted on GBM biological matrices, such as in vitro and in vivo models, tissues and biofluids, including plasma, saliva and cerebrospinal fluid. From the data reported here, it appears that metabolic reprogramming in GBM is characterized by dysregulation in multiple pathways, particularly glycolysis (Warburg effect), amino acid metabolism, and the urea cycle, and the metabolic changes disclose promising tumor targets. |
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| ISSN: | 1756-9966 |