Glioblastoma is the most frequent and malignant primary brain tumor. Standard of care includes surgery followed by radiation and temozolomide chemotherapy. Despite treatment, patients have a poor prognosis with a median survival of less than 15 months. The poor prognosis is associated with an increased abundance of tumor-associated microglia and macrophages (TAMs), which are known to play a role in creating a pro-tumorigenic environment and aiding tumor progression. Most treatment strategies are directed against glioblastoma cells; however, accumulating evidence suggests targeting of TAMs as a promising therapeutic strategy. While TAMs are typically dichotomously classified as M1 and M2 phenotypes, recent studies utilizing single cell technologies have identified expression pattern differences, which is beginning to give a deeper understanding of the heterogeneous subpopulations of TAMs in glioblastomas. In this review, we evaluate the role of TAMs in the glioblastoma microenvironment and discuss how their interactions with cancer cells have an extensive impact on glioblastoma progression and treatment resistance. Finally, we summarize the effects and challenges of therapeutic strategies, which specifically aim to target TAMs.

Glioblastoma is one of the most aggressive cancers, but the molecular evolution is not fully understood. We used PET imaging combined with deep sequencing of glioblastoma biopsies at both the RNA and DNA levels to get a deeper insight into molecular evolution. In the clinical setting, PET imaging provides information about metabolically active tumor areas, but the molecular interpretation is unclear. Our primary objective was to perform an intratumoral spatial comparison of biopsies from potentially aggressive and less aggressive areas in glioblastomas according to PET scans. We used MRI co-registered with 11C-MET-PET (amino acid) and 18F-FDG PET (glucose) in order to obtain representative neurosurgical stereotactic biopsies from tumor areas with high accumulation of these two metabolites (hotspot), low accumulation (coldspot), and no accumulation as the periphery of six glioblastoma patients that were processed for whole genome, exome, and transcriptome sequencing. Differential gene expression and gene ontology analysis showed that hotspots were enriched in gene sets associated with DNA replication, cell cycle, and ligand-receptor interaction. Genome and exome analysis suggested hotspots and coldspots have similar mutational profiles. However, a limited number of hotspot-specific mutations and novel fusion transcripts indicated that hotspot-associated tumor cells developed from coldspot-associated tumor cells and point at the potential role of hotspot driver genes in glioblastoma evolution. Our findings reveal that hotspots in glioblastomas represent a more advanced stage of molecular evolution than coldspots. Citation Format: Atul Anand, Jeanette Krogh Petersen, Mark Burton, Martin Jakob Larsen, Lars van Andersen, Dylan Scott Harwood, Christian Bonde Pedersen, Frantz Rom Poulsen, Peter Grupe, Torben A. Kruse, Mads Thomassen, Bjarne Winther Kristensen. Deeper insight into intratumoral heterogeneity by MRI and PET-guided stereotactic biopsies from glioblastoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3796.

Background The standard therapy for glioblastoma patients is tumor resection followed by radiotherapy and temozolomide chemotherapy. Although glioblastoma has been extensively molecularly profiled along with other cancers, this knowledge has not yet been translated into improved survival outcomes. We used a bioinformatics approach to identify potential novel therapeutic strategies for glioblastoma. Objectives: Comprehensive online datasets which have assessed up to 1376 cancer cell lines in multiple ways were interrogated to identify potential drug candidates for glioblastoma. Material and Methods Datasets included were from the cancer cell line encyclopedia (mRNA expression), the Achillies project (cell viability following Crispr-Cas9 knockout) and PRISM (drug treatment). A t-test comparing cell viability of glioblastoma cell lines versus other cancers was used to identify potential drug candidates, followed by the use of multiple statistical tools to investigate potential mechanism of action and status of biomarkers. Results Fluvastatin and pitavastatin were amongst the drugs with the most significant effects against glioblastoma cell lines while also being FDA approved. These effects were found in both glioblastoma cells and other cancer types with a mesenchymal-like expression phenotype. The anti-cancer properties of statins have previously been attributed to the inhibition of HMG-Coa reductase. Here, we found their effects correlated with the gene knockout of UBIAD1. We tested the effects of statins on patient-derived glioblastoma cell lines with a mesenchymal (n = 2) and non-mesenchymal phenotype (n=2). Mesenchymal-like glioblastoma cells lines were found to be more susceptible to statins. Conclusion Statins appeared to be especially effective against glioblastoma lines and the effect could be linked to the direct or indirect inhibition of UBIAD1. In vitro validation of this finding is ongoing.