TMET-50. Spatial Metabolomics Reveals Glioblastoma–Astrocyte Crosstalk in Models Mimicking the Tumour Microenvironment

Isocitrate dehydrogenase wild-type glioblastoma is an aggressive brain tumour with a poor prognosis and one of the highest recurrence rates despite multimodal treatment. The mechanisms underlying recurrence are not fully understood, but the tumour microenvironment is known to play a key role. Astrocytes, the most abundant glial cells in the brain, have been implicated in supporting tumour progression, yet their metabolic interactions with glioblastoma invasive margin cells remain poorly understood. This study aims to investigate these metabolic interactions using high resolution spatial metabolomics to identify pathways involved in tumour progression. We employed atmospheric pressure matrix-assisted laser desorption/ionisation (AP-MALDI) imaging mass spectrometry at 10 μm spatial resolution to investigate metabolic interactions between primary glioblastoma invasive margin (GIN) cells and human cortical astrocytes (HA) in a 2D co-culture model mimicking post-surgical residual disease. In addition, a 3D co-culture model was developed to better recapitulate the tumour microenvironment, enabling spatial comparative analysis. Metabolomic analysis revealed distinct pathway alterations in glioblastoma invasive margin cells and astrocytes in co-culture. Glioblastoma cells showed enrichment in purine metabolism and the pentose phosphate pathway, while astrocytes exhibited changes in pyrimidine, arginine, and serine-related pathways. Notably, both cell types showed involvement of tyrosine metabolism and phenylalanine, and tryptophan biosynthesis, with multiple contributing metabolites highlighting their potential importance in tumour–astrocyte metabolic communication. By mapping metabolite spatial distributions at high spatial resolution, this study provides novel insights into tumour–astrocyte metabolic interactions at the invasive margin, introducing methodology applicable to heterogeneous biopsy tissue from the glioblastoma infiltrative margin. The use of a 3D model revealed additional microenvironment-specific metabolic features, highlighting potential therapeutic targets to disrupt glioblastoma recurrence manifesting from residual disease.