Glioblastoma (GBM) displays marked cellular and metabolic heterogeneity that varies among cellular microenvironments within a tumor. Metabolic targeting has long been advocated as a therapy against many tumors including GBM, but how lipid metabolism is altered to suit different microenvironmental conditions and whether cancer stem cells (CSCs) have altered lipid metabolism are outstanding questions in the field. We interrogated gene expression in separate microenvironments of GBM organoid models that mimic the transition between nutrient-rich and nutrient-poor pseudopalisading/perinecrotic tumor zones using spatial-capture RNA-sequencing. We revealed a striking difference in lipid processing gene expression and total lipid content between diverse cell populations from the same patient, with lipid enrichment in hypoxic organoid cores and also in perinecrotic and pseudopalisading regions of primary patient tumors. This was accompanied by regionally restricted upregulation of hypoxia-inducible lipid droplet-associated (HILPDA) gene expression in organoid cores and pseudopalisading regions of clinical GBM specimens, but not lower-grade brain tumors. CSCs have low lipid droplet accumulation compared to non-CSCs in organoid models and xenograft tumors, and prospectively sorted lipid-low GBM cells are functionally enriched for stem cell activity. Targeted lipidomic analysis of multiple patient-derived models revealed a significant shift in lipid metabolism between GBM CSCs and non-CSCs, suggesting that lipid levels may not be simply a product of the microenvironment but also may be a reflection of cellular state. CSCs had decreased levels of major classes of neutral lipids compared to non-CSCs, but had significantly increased polyunsaturated fatty acid production due to high fatty acid desaturase (FADS1/2) expression which was essential to maintain CSC viability and self-renewal. Our data demonstrate spatially and hierarchically distinct lipid metabolism phenotypes occur clinically in the majority of patients, can be recapitulated in laboratory models, and may represent therapeutic targets for GBM.

Glioblastoma (GBM) is the most common primary brain tumor with a dismal prognosis. The inherent cellular diversity and interactions within tumor microenvironments represent significant challenges to effective treatment. Traditional culture methods such as adherent or sphere cultures may mask such complexities whereas three-dimensional (3D) organoid culture systems derived from patient cancer stem cells (CSCs) can preserve cellular complexity and microenvironments. The objective of this study was to determine if GBM organoids may offer a platform, complimentary to traditional sphere culture methods, to recapitulate patterns of clinical drug resistance arising from 3D growth. Adult and pediatric surgical specimens were collected and established as organoids. We created organoid microarrays and visualized bulk and spatial differences in cell proliferation using immunohistochemistry (IHC) staining, and cell cycle analysis by flow cytometry paired with 3D regional labeling. We tested the response of CSCs grown in each culture method to temozolomide, ibrutinib, lomustine, ruxolitinib, and radiotherapy. GBM organoids showed diverse and spatially distinct proliferative cell niches and include heterogeneous populations of CSCs/non-CSCs (marked by SOX2) and cycling/senescent cells. Organoid cultures display a comparatively blunted response to current standard-of-care therapy (combination temozolomide and radiotherapy) that reflects what is seen in practice. Treatment of organoids with clinically relevant drugs showed general therapeutic resistance with drug- and patient-specific antiproliferative, apoptotic, and senescent effects, differing from those of matched sphere cultures. Therapeutic resistance in organoids appears to be driven by altered biological mechanisms rather than physical limitations of therapeutic access. GBM organoids may therefore offer a key technological approach to discover and understand resistance mechanisms of human cancer cells.

Synthetic lethality is a genetic interaction that results in cell death when two genetic deficiencies co-occur but not when either deficiency occurs alone, which can be co-opted for cancer therapeutics. Pairs of paralog genes are among the most straightforward potential synthetic–lethal interactions by virtue of their redundant functions. Here, we demonstrate a paralog-based synthetic lethality by targeting vaccinia-related kinase 1 (VRK1) in glioblastoma (GBM) deficient of VRK2, which is silenced by promoter methylation in approximately two thirds of GBM. Genetic knockdown of VRK1 in VRK2-null or VRK2-methylated cells resulted in decreased activity of the downstream substrate barrier to autointegration factor (BAF), a regulator of post-mitotic nuclear envelope formation. Reduced BAF activity following VRK1 knockdown caused nuclear lobulation, blebbing, and micronucleation, which subsequently resulted in G2–M arrest and DNA damage. The VRK1–VRK2 synthetic–lethal interaction was dependent on VRK1 kinase activity and was rescued by ectopic expression of VRK2. In VRK2-methylated GBM cell line–derived xenograft and patient-derived xenograft models, knockdown of VRK1 led to robust tumor growth inhibition. These results indicate that inhibiting VRK1 kinase activity could be a viable therapeutic strategy in VRK2-methylated GBM. Significance: A paralog synthetic–lethal interaction between VRK1 and VRK2 sensitizes VRK2-methylated glioblastoma to perturbation of VRK1 kinase activity, supporting VRK1 as a drug discovery target in this disease.

Glioblastoma (GBM) commonly displays epidermal growth factor receptor (EGFR) alterations (mainly amplification and EGFRvIII) and TAT-Cx43_266–283 is a Src-inhibitory peptide with antitumor properties in preclinical GBM models. Given the link between EGFR and Src, the aim of this study was to explore the role of EGFR in the antitumor effects of TAT-Cx43_266–283. The effect of TAT-Cx43_266–283, temozolomide (TMZ), and erlotinib (EGFR inhibitor) was studied in patient-derived GBM stem cells (GSCs) and murine neural stem cells (NSCs) with and without EGFR alterations, in vitro and in vivo. EGFR alterations were analyzed by western blot and fluorescence in situ hybridization in these cells, and compared with Src activity and survival in GBM samples from The Cancer Genome Atlas. The effect of TAT-Cx43_266–283 correlated with EGFR alterations in a set of patient-derived GSCs and was stronger than that exerted by TMZ and erlotinib. In fact, TAT-Cx43_266-283 only affected NSCs with EGFR alterations, but not healthy NSCs. EGFR alterations correlated with Src activity and poor survival in GBM patients. Finally, tumors generated from NSCs with EGFR alterations showed a decrease in growth, invasiveness, and vascularization after treatment with TAT-Cx43_266–283, which enhanced the survival of immunocompetent mice. Clinically relevant EGFR alterations are predictors of TAT-Cx43_266–283 response and part of its mechanism of action, even in TMZ- and erlotinib-resistant GSCs. TAT-Cx43_266–283 targets NSCs with GBM-driver mutations, including EGFR alterations, in an immunocompetent GBM model in vivo, suggesting a promising effect on GBM recurrence. Together, this study represents an important step toward the clinical application of TAT-Cx43_266–283.

Glioblastoma (GBM) is the most commonly occurring primary malignant brain cancer with an extremely poor prognosis. Intra-tumoral cellular and molecular diversity, as well as complex interactions between tumor microenvironments, can make finding effective treatments a challenge. Traditional adherent or sphere culture methods can mask such complexities, whereas three-dimensional organoid culture can recapitulate regional microenvironmental gradients. Organoids are a method of three-dimensional GBM culture that better mimics patient tumor architecture, contains phenotypically diverse cell populations, and can be used for medium-throughput experiments. Although three-dimensional organoid culture is more laborious and time-consuming compared to traditional culture, it offers unique benefits and can serve to bridge the gap between current in vitro and in vivo systems. Organoids have established themselves as invaluable tools in the arsenal of cancer biologists to better understand tumor behavior and mechanisms of resistance, and their applications only continue to grow. Here, details are provided about methods for generating and maintaining GBM organoids. Instructions of how to perform organoid sample embedding and sectioning using both frozen and paraffin-embedding techniques, as well as recommendations for immunohistochemistry and immunofluorescence protocols on organoid sections, and measurement of total organoid cell viability, are all also described.

Advances in organoid technology have transformed how gliomas are modeled and studied. Recent FDA and NIH initiatives further promote human-relevant organoid platforms for preclinical research. Glioma organoids can be broadly categorized into 3 main classes: Engineered organoids, which enable controlled modeling of gliomagenesis driven by specific mutations; patient-derived organoids, which preserve key molecular and histopathological features of the original tumors; and assembloids, which are designed to model tumor-microenvironment interactions. Together, these systems provide a human cell-relevant framework for investigating glioma biology, tumor-microenvironment crosstalk, and therapeutic responses and resistance. In this review, we provide a comprehensive overview of the spectrum of glioma organoid models, recognizing that different systems offer distinct and complementary strengths, and we offer practical guidance for selecting appropriate models and analytical readouts based on specific basic and translational research objectives. To address increasing methodological heterogeneity and fragmented terminology, we propose a foundational nomenclature framework for glioma organoid models to improve clarity and communication within the field. We highlight applications in technically challenging subtypes, including isocitrate dehydrogenase (IDH)-mutant gliomas and diffuse midline gliomas (DMGs). We also discuss key challenges—including scalability, standardization, microenvironment fidelity, and vascularization—and emerging innovations addressing these limitations. Finally, we call for greater collaboration and standardization within the glioma organoid community to accelerate the integration of organoid models into translational pipelines to redefine and refine preclinical modeling in neuro-oncology.