4.6 Article

Integrative Metabolomics Reveals Deep Tissue and Systemic Metabolic Remodeling in Glioblastoma

期刊

CANCERS
卷 13, 期 20, 页码 -

出版社

MDPI
DOI: 10.3390/cancers13205157

关键词

glioblastoma; high-grade glioma; brain tumor; neuro-oncology; metabolomics; omics; mass spectrometry; machine learning

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资金

  1. University of Rouen Normandy
  2. INSA Rouen Normandy
  3. Centre National de la Recherche Scientifique (CNRS)
  4. Labex SynOrg [ANR-11-LABX-0029]
  5. Carnot Institut I2C
  6. graduate school for research Xl-Chem [ANR-18-EURE-0020 XL CHEM]
  7. Region Normandie
  8. European Union [731077]
  9. European Regional Development Fund (ERDF)

向作者/读者索取更多资源

This study investigates metabolic remodeling in patients with glioblastoma using targeted and untargeted metabolomics, identifying phospholipids, sphingomyelins, acylcarnitines, and acylglycerols as key impaired metabolic classes. The findings show deep metabolic rewiring in glioblastoma, highlighting the significant role of lipids in tumor progression.
This study aims to explore metabolic remodeling in plasma and tissue samples in patients with glioblastoma through an integrated targeted and untargeted metabolomics-based strategy. We report phospholipids, sphingomyelins, acylcarnitines, and acylglycerols as key impaired metabolic classes in glioblastoma. (1) Background: Glioblastoma is the most common malignant brain tumor in adults. Its etiology remains unknown in most cases. Glioblastoma pathogenesis consists of a progressive infiltration of the white matter by tumoral cells leading to progressive neurological deficit, epilepsy, and/or intracranial hypertension. The mean survival is between 15 to 17 months. Given this aggressive prognosis, there is an urgent need for a better understanding of the underlying mechanisms of glioblastoma to unveil new diagnostic strategies and therapeutic targets through a deeper understanding of its biology. (2) Methods: To systematically address this issue, we performed targeted and untargeted metabolomics-based investigations on both tissue and plasma samples from patients with glioblastoma. (3) Results: This study revealed 176 differentially expressed lipids and metabolites, 148 in plasma and 28 in tissue samples. Main biochemical classes include phospholipids, acylcarnitines, sphingomyelins, and triacylglycerols. Functional analyses revealed deep metabolic remodeling in glioblastoma lipids and energy substrates, which unveils the major role of lipids in tumor progression by modulating its own environment. (4) Conclusions: Overall, our study demonstrates in situ and systemic metabolic rewiring in glioblastoma that could shed light on its underlying biological plasticity and progression to inform diagnosis and/or therapeutic strategies.

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