LAUSR

Simple Summary Glioblastoma (GB) is an aggressive brain tumour with poor survival. Tumour microenvironment is a key element in GB evolution and response to therapy. We assessed presence and phenotypes of microglia/macrophages in preclinical GL261-GB microenvironment under Temozolomide (TMZ) treatment to unveil its possible relationship with MRSI-detected metabolomics changes. Microglia/macrophage polarisation towards an anti-tumour phenotype prevailed in TMZ-treated tumours. Since microglia/macrophages can represent 30–40% of the GB tumour volume, they must contribute the metabolomic pattern change. PD-L1 expression also correlated with the anti-tumour microglia/macrophage phenotype. These results highlight the potential of MRSI-detected metabolomics as non-invasive biomarker for immune system action. Abstract Glioblastomas (GB) are brain tumours with poor prognosis even after aggressive therapy. Previous work suggests that magnetic resonance spectroscopic imaging (MRSI) could act as a biomarker of efficient immune system attack onto GB, presenting oscillatory changes. Glioma-associated microglia/macrophages (GAMs) constitute the most abundant non-tumour cell type within the GB and can be polarised into anti-tumour (M1) or pro-tumour (M2) phenotypes. One of the mechanisms to mediate immunosuppression in brain tumours is the interaction between programmed cell death-1 ligand 1 (PD-L1) and programmed cell death-1 receptor (PD-1). We evaluated the subpopulations of GAMs in responding and control GB tumours to correlate PD-L1 expression to GAM polarisation in order to explain/validate MRSI-detected findings. Mice were evaluated by MRI/MRSI to assess the extent of response to treatment and with qPCR for GAMs M1 and M2 polarisation analyses. M1/M2 ratios and PD-L1 expression were higher in treated compared to control tumours. Furthermore, PD-L1 expression was positively correlated with the M1/M2 ratio. The oscillatory change in the GAMs prevailing population could be one of the key causes for the differential MRSI-detected pattern, allowing this to act as immune system activity biomarker in future work.