medium was refreshed every 48 h, and on day 10 it was removed, the plates placed on ice and the wells washed with 1 ml of ice - cold pbs, followed by the addition of 1 ml corning cell recovery solution. the plates were incubated at 4 °c for 1 h and then washed four times with ice - cold pbs. rna was isolated from cell pellets using a qiashredder spin column ( qiagen ) and allprep dna / rna mini kit ( qiagen ), quantified using a qubit fluorometer ( thermo fisher scientific ) and quality tested using an agilent 4200 tapestation. for library preparation, the illumina truseq stranded mrna kit was used, and single - read sequencing was performed on a hiseq 4000 machine ( illumina ). quality control of raw sequence data was carried out using fastqc ( v. 0. 11. 8 ). some reads were trimmed to remove adaptor content using trimmomatic ( v. 0. 39 ). reads were aligned to grch38 ensembl release 102 using star ( v. 2. 7. 7a ) and alignment quality control was carried out using picard tools ( v. 2. 25. 1 ). quantification was carried out using salmon ( v. 1. 6. 0 ) against a reference transcriptome for the same genome release. differential gene expression analysis was carried out in r ( v. 4. 2. 2 ) using the deseq2 package ( v. 1. 38. 3 ) with default parameters. multiple testing correction of p values was carried out using the benjamini – hochberg method. genes were determined to be differentially expressed at an adjusted p value of 0. 05. gene set enrichment analysis was carried out using clusterprofiler ( v. 4. 6. 0 ). experiments were performed under the authority of a home office project licence ( pp5634271 ) and approved by an animal welfare and ethical review body at the cancer research uk ( cruk ) cambridge institute, university of cambridge. athymic, female nude rats that were at least 9 weeks old were implanted orthotopically with the primary gb lines at passage 10. animals were anaesthetized using 2 % isoflurane ( isoflo, abbott laboratories ) in o 2 / air ( 25 / 75 %, vol / vol, 2 l min ) with 5 mg kg carpofen ( zoetis ) and 0. 3 mg ml buprenorphine hydrochloride ( alstoe ) subcutaneous analgesia. body temperature was maintained using a heating pad. a stereotactic surgical frame ( kopf ) was used to secure the animal ’ s head. a midline incision was made followed by a 1 mm burr hole anterior and to the right of the bregma. a total of 1 × 10 cells were injected in 5 µl of neurobasal medium at a depth of 4 mm. the burr hole was closed with bone wax ( ethicon ) and skin with 6 / 0 vicryl ( ethicon ). tumour growth was monitored using t 2 - weighted mri. specifically, animals were anaesthetized using 2 % isoflurane ( isoflo, abbott laboratories ) in o 2 / air ( 25 / 75 %, vol / vol, 2 l min ) and placed supine inside a 7t magnet ( agilent ), and t 2 - weighted mri was used to monitor tumour growth. a 72 mm h volume coil was placed around the animal ’ s head, and breathing rate and temperature were monitored with a small animal instruments monitoring system ( saii ). axial h t 2 - weighted images were acquired using a fast spin - echo sequence with an echo time of 50 ms, pulse repetition time of 1, 500 ms, flip angle of 60 – 90° and a slice thickness of 2. 0 mm, field - of - view of 40 mm × 40 mm and 128 × 128 or 256 × 256 data points. three animals per cell line were administered with [ u - c ] glucose as a bolus at 0. 4 mg g, followed by continuous infusion of 0. 012 mg g min at 300 µl h for 120 min ( ref. ). the brains were snap - frozen in liquid nitrogen, cryo - sectioned at a thickness of 10 µm and analysed with desi - msi and maldi - msi, as described above. the 10× genomics visium platform was used and analysed with the space ranger pipeline. downstream analyses were conducted in r using the seurat package. samples were processed individually using the sctransform ( ) function. spots were filtered based on standard quality control thresholds ( for example, mitochondrial gene percentage of > 20 %, ncount _ spatial of < 1, 000 and nfeature _ spatial of < 1, 000 ). data were re - corrected across samples using prepsctfindmarkers ( ) for joint numerical analyses. gene set scoring was performed using the hallmark gene sets and the ucell package, excluding mitochondrial genes from the oxidative phosphorylation score calculations. to annotate spatial spots, genes from hallmark gene sets of interest were combined and subjected to k - means clustering ( k = 3 ). to annotate tme spots, we performed two deconvolution steps with robust cell type decomposition, using previously published reference cell annotations. first, a balanced normal reference was sampled from the non - neoplastic cells, combined with the neoplastic cells and used as input for robust cell type decomposition. the assignment was further confirmed by histological evaluation. to label tme niches, we further deconvolved tme signals into oligodendrocytes, astrocytes, vascular cells, immune cells ( macrophages ) and neurons. given that each spatial spot contained multiple cells, we normalized the deconvolution weights to a maximum of one, providing a relative abundance. to mitigate over - assignment to sorted tme cell types, we included unsorted cell types ( neoplastic + oligodendrocyte precursor cell with high transcriptomic similarity ) in this deconvolution step as a ‘ block ’ effect. joint feature plots ( tumour and tme ) were generated using a custom modification of the spatialfeatureplotblend ( ) source function. the original repository is available at https: / / github. com / george - hall - ucl / spatialfeatureplotblend. for the tme population - level quantification, for each spot, the weights of all deconvolved populations were normalized to sum to one, thereby representing the relative contribution of each cell population within that specific spot. subsequently, these normalized weights were plotted across the three metabolic states. total ion count - normalized msi data were extracted using the scils lab api ( v. 2022b; bruker daltonik ), and metabolic labels were spatially smoothed to provide coherent spatial regions. immediately neighbouring pixels ( ≤8 ) were identified for each msi pixel, and across five iterations, for each pixel that had at least two neighbours and for which the majority of neighbours were assigned a different label, the label was replaced with the majority label. an image was created using spatial coordinates, in which pixels were coloured using the first three principal components as rgb channels. landmarks were identified between this msi dimensionality reduction image and the h & e image of the corresponding tissue section, and subsequently between the h & e image and the corresponding h & e image of the contiguous tissue section used for spatial transcriptomic analysis. these landmarks were then used to map the msi coordinates onto the spatial transcriptomic coordinate space using an affine transform. msi labels were finally transferred to spots on the spatial transcriptomic image using the k - nearest neighbours algorithm ( k = 3 ). regions were defined using k - means clustering and fitted using the kmeans function in the amap r package and performed independently on the neurosphere, human and metastases datasets. the values for each of the seven c - labelled metabolites used for metabolic clustering were standardised into z - scores ( by subtracting the metabolite ’ s mean and dividing by the metabolite ’ s standard deviation ). each pixel was then assigned to three or four groups, using k - means clustering with manhattan distances. antibod ies used for immunoh istochemistry are described in supplementary table 5. antibod ies were tagged using the fluidigm maxpar antibod y labelling kit.