Objective:

To develop a biological understanding of glioma metabolism.

Background:

Glioblastoma is a metabolically diverse and aggressive brain tumor. We used untargeted metabolomics and lipidomics with supervised analysis to define metabolic changes within IDH-wildtype glioblastoma and IDH-mutant astrocytoma, grade 4, as well as to identify potential subclusters of metabolically distinct tumor types.

Design/Methods:

Brain tissue from IDH-wildtype glioblastoma (n = 38), IDH-mutant astrocytoma, Grade 4 (n = 5), and non-neoplastic controls (n = 20) underwent untargeted metabolomic and lipidomic profiling. Partial Least Squares Discriminant Analysis was followed by k-means clustering. ANOVA was used to identify significantly altered metabolites, with significance defined as fold change (FC) of greater than 2 and p-value correction based on a false discovery rate of 0.05. Heatmaps visualized differences, and pathway enrichment was performed using MetaboAnalyst 6.0.

Results:

Glioblastoma exhibited numerous significantly altered metabolites and lipids compared to controls, including increases in hypotaurine (FC 5.5, p = 9x10^-5) and sorbitol (FC 3.9, p = 0.003), and decreases in ribonic acid (FC -3.3, p = 1.6x10^-13) and arabitol (FC -2.9, p = 4.1x10^-20). K-means clustering revealed three distinct metabolic subtypes within IDH-wildtype glioblastoma. Cluster 1 showed increased galactose (p=0.02) and sucrose metabolism (p=0.009). Cluster 2 was characterized by increased glutathione metabolism (p=0.002). Cluster 3 demonstrated increased arginine biosynthesis (p=7.5x10^-4). IDH-mutant tumors exhibited 130-fold elevated levels of 2-hydroxyglutarate (2HG). Lipidomic profiling demonstrated numerous altered lipids in both tumor types compared to controls, including increases in sphingomyelin 40:1 (FC 157, p=4.4x10^-5) and decreases in phosphatidylcholine 39:7 (FC -2.8, p=3.0x10^-19) , but overall similar lipidomic profiles between the two tumor types.

Conclusions:

Metabolomic profiling identified three distinct subtypes of IDH-wildtype glioblastoma with unique metabolic signatures and revealed shared metabolic features between glioblastoma and IDH-mutant astrocytoma grade 4. Results highlight the potential for metabolomics to improve understanding of tumor biology and guide personalized treatment strategies for patients.