Background and Purpose: Traumatic brain injury (TBI) remains a major public health concern worldwide with unmet effective treatment. Stimulator of interferon genes (STING) and its downstream type‐I interferon (IFN) signalling are now appreciated to be involved in TBI pathogenesis. Compelling evidence have shown that STING and type‐I IFNs are key in mediating the detrimental neuroinflammatory response after TBI. Therefore, pharmacological inhibition of STING presents a viable therapeutic opportunity in combating the detrimental neuroinflammatory response after TBI.Experimental Approach: This study investigated the neuroprotective effects of the small‐molecule STING inhibitor n‐(4‐iodophenyl)‐5‐nitrofuran‐2‐carboxamide (C‐176) in the controlled cortical impact mouse model of TBI in 10‐ to 12‐week‐old male mice. Thirty minutes post‐controlled cortical impact surgery, a single 750‐nmol dose of C‐176 or saline (vehicle) was administered intravenously. Analysis was conducted 2 h and 24 h post‐TBI.Key Results: Mice administered C‐176 had significantly smaller cortical lesion area when compared to vehicle‐treated mice 24 h post‐TBI. Quantitative temporal gait analysis conducted using DigiGait™ showed C‐176 administration attenuated TBI‐induced impairments in gait symmetry, stride frequency and forelimb stance width. C‐176‐treated mice displayed a significant reduction in striatal gene expression of pro‐inflammatory cytokines Tnf‐α, Il‐1β and Cxcl10 compared to their vehicle‐treated counterparts 2 h post‐TBI.Conclusion and Implications: This study demonstrates the neuroprotective activity of C‐176 in ameliorating acute neuroinflammation and preventing white matter neurodegeneration post‐TBI. This study highlights the therapeutic potential of small‐molecule inhibitors targeting STING for the treatment of trauma‐induced inflammation and neuroprotective potential.

Matrix-assisted laser desorption/ionization mass spectrometry imaging allows for the study of metabolic activity in the tumor microenvironment of brain cancers. The detectable metabolites within these tumors are contingent upon the choice of matrix, deposition technique, and polarity setting. In this study, we compared the performance of three different matrices, two deposition techniques, and the use of positive and negative polarity in two different brain cancer types and across two species. Optimal combinations were confirmed by a comparative analysis of lipid and small-molecule abundance by using liquid chromatography–mass spectrometry and RNA sequencing to assess differential metabolites and enzymes between normal and tumor regions. Our findings indicate that in the tumor-bearing brain, the recrystallized α-cyano-4-hydroxycinnamic acid matrix with positive polarity offered superior performance for both detected metabolites and consistency with other techniques. Beyond these implications for brain cancer, our work establishes a workflow to identify optimal matrices for spatial metabolomics studies.

Background: The intra- and inter-tumoral heterogeneity of glioblastoma (GBM) represents a significant therapeutic challenge and barrier to the generation of reliable and accurate models for in vitro studies. Three-dimensional models, such as patient-derived neurospheres (PDN) and organoids (PDO), recapitulate complex cellular states. However, the direct comparison of models derived in parallel from the same primary tumor tissue has never been performed. The aim of this study was to determine the tumor cell composition of PDN and PDO models relative to matched primary GBM tissue. Methods: Four GBM surgical samples were used to establish matched PDO and PDN models, which were genomically verified using single nucleotide polymorphism array. DNA methylation, histology, and transcriptome were examined for intra-tumoral heterogeneity correlating with the matched GBM tissue. PDN lines were used to investigate the tumor cell composition response to temozolomide chemotherapy over time, maximizing their utility. Results: We find that both patient-derived models recapitulate the genomic, epigenomic, and tumor cell heterogeneity of the primary tissue at similar capacity. Furthermore, single-nuclei RNA sequencing revealed a subset of organoids containing small numbers of non-malignant cells from neuron and immune cell lineages. Harnessing the intra-tumoral heterogeneity of PDN models, we reveal the impact of temozolomide chemotherapy on individual cell states, altering composition of tumors over time in response to treatment. Conclusions: Our data confirms that both PDN and PDO patient-derived models recapitulate patient intra-tumoral heterogeneity providing a platform for tumor cell state refined therapeutic studies.

The intra- and inter-tumoral heterogeneity of glioblastoma represents a significant therapeutic challenge, as well as difficulty in generating reliable models for in vitro studies. Historical 2D adherent cell lines do not recapitulate this complexity, whereas both patient-derived neurospheres (PDN) and organoids (PDO) demonstrate intra-tumoral heterogeneity. Here, we quantify the tumor cell composition from matched models established from the same primary tumor using a series of multi-omic interrogations. We find that both patient-derived models recapitulate the genomic, epigenomic and tumor cell heterogeneity of the primary tissue. Furthermore, single-nuclei RNA sequencing revealed a subset of organoids containing small numbers of non-malignant cells from neuron and immune cell lineages. Harnessing the intra-tumoral heterogeneity of PDN models, we reveal the impact of temozolomide chemotherapy on individual cell states, altering composition of tumors over time in response to treatment. Our data confirms that both patient-derived models recapitulate patient intra-tumoral heterogeneity providing a platform for tumor cell state refined therapeutic studies. Key Points: Generation of matched patient-derived neurosphere and organoid models from resected GBM tissue Neurosphere models exhibit greater proliferative signatures Both patient-derived models recapitulate genomic and epigenomic features of the primary tissue Single-nuclei RNA sequencing reveals both models recapitulate intra-tumoral heterogeneity of the primary tissue Neurosphere models enable interrogation of therapeutic responses in the context of heterogeneity Importance of study: Patient derived models can be powerful tools when they faithfully recapitulate the tumor tissue from which they are derived. In glioblastoma, patient derived neurospheres (PDN) and organoids (PDO) have both been used in studies, however the differences between these models and the recapitulation of patient heterogeneity remain to be fully characterized. To address this, we performed multi-omic profiling of PDN and PDO models generated from the same tumor tissue. We find that that across a range of data modalities, both model systems exhibit a high level of resemblance to tissue, and critically, maintain heterogeneity and tumor cell composition. The importance of modeling heterogeneity was demonstrated in PDN models, where temozolomide treatment specifically alters the abundance of MES-like and AC-like tumor cells. Our findings demonstrate that neurosphere and organoid models effectively preserve cellular heterogeneity, genomic alterations, methylation signatures and transcriptomic features, both highly suitable to model glioblastoma’s complex cellular landscape.