The complex molecular epileptogenesis landscape of glioblastoma.

The cortical microenvironment surrounding malignant glioblastoma is a source of depolarizing crosstalk favoring hyperexcitability, tumor expansion, and immune evasion. Neosynaptogenesis, excess glutamate, and altered intrinsic membrane currents contribute to excitability dyshomeostasis, yet only half of the cases develop seizures, suggesting that tumor and host genomics, along with location, rather than mass effect, play a critical role. We analyzed the spatial contours and expression of 358 clinically validated human epilepsy genes in the human glioblastoma transcriptome compared to non-tumor adult and developing cortex datasets. Nearly half, including dosage-sensitive genes whose expression levels are securely linked to monogenic epilepsy, are strikingly enriched and aberrantly regulated at the leading edge, supporting a complex epistatic basis for peritumoral epileptogenesis. Surround hyperexcitability induced by complex patterns of proepileptic gene expression may explain the limited efficacy of narrowly targeted antiseizure medicines and the persistence of epilepsy following tumor resection and clarify why not all brain tumors provoke seizures.

Agent-based computational modeling of glioblastoma predicts that stromal density is central to oncolytic virus efficacy.

Oncolytic viruses (OVs) are emerging cancer immunotherapy. Despite notable successes in the treatment of some tumors, OV therapy for central nervous system cancers has failed to show efficacy. We used an ex vivo tumor model developed from human glioblastoma tissue to evaluate the infiltration of herpes simplex OV rQNestin (oHSV-1) into glioblastoma tumors. We next leveraged our data to develop a computational, model of glioblastoma dynamics that accounts for cellular interactions within the tumor. Using our computational model, we found that low stromal density was highly predictive of oHSV-1 therapeutic success, suggesting that the efficacy of oHSV-1 in glioblastoma may be determined by stromal-to-tumor cell regional density. We validated these findings in heterogenous patient samples from brain metastatic adenocarcinoma. Our integrated modeling strategy can be applied to suggest mechanisms of therapeutic responses for central nervous system cancers and to facilitate the successful translation of OVs into the clinic.

Gelatin methacrylate hydrogels culture model for glioblastoma cells enriches for mesenchymal-like state and models interactions with immune cells.

Glioblastoma is the most lethal primary malignant brain tumor in adults. Simplified two-dimensional (2D) cell culture and neurospheres in vitro models fail to recapitulate the complexity of the tumor microenvironment, limiting its ability to predict therapeutic response. Three-dimensional (3D) scaffold-based models have emerged as a promising alternative for addressing these concerns. One such 3D system is gelatin methacrylate (GelMA) hydrogels, and we aimed to understand the suitability of using this system to mimic treatment-resistant glioblastoma cells that reside in specific niches. We characterized the phenotype of patient-derived glioma cells cultured in GelMA hydrogels (3D-GMH) for their tumorigenic properties using invasion and chemoresponse assays. In addition, we used integrated single-cell and spatial transcriptome analysis to compare cells cultured in 3D-GMH to neoplastic cells in vivo. Finally, we assessed tumor-immune cell interactions with a macrophage infiltration assay and a cytokine array. We show that the 3D-GMH system enriches treatment-resistant mesenchymal cells that are not represented in neurosphere cultures. Cells cultured in 3D-GMH resemble a mesenchymal-like cellular phenotype found in perivascular and hypoxic regions and recruit macrophages by secreting cytokines, a hallmark of the mesenchymal phenotype. Our 3D-GMH model effectively mimics the phenotype of glioma cells that are found in the perivascular and hypoxic niches of the glioblastoma core in situ, in contrast to the neurosphere cultures that enrich cells of the infiltrative edge of the tumor. This contrast highlights the need for due diligence in selecting an appropriate model when designing a study's objectives.

Glioblastoma radiomics: can genomic and molecular characteristics correlate with imaging response patterns?

PURPOSE: For glioblastoma (GBM), imaging response (IR) or pseudoprogression (PSP) is frequently observed after chemoradiation and may connote a favorable prognosis. With tumors categorized by the Cancer Genome Atlas Project (mesenchymal, classical, neural, and proneural) and by methylguanine-methyltransferase (MGMT) methylation status, we attempted to determine if certain genomic or molecular subtypes of GBM were specifically associated with IR or PSP. METHODS: Patients with GBM treated at two institutions were reviewed. Kaplan-Meier method was used to estimate overall survival (OS) and progression-free survival (PFS). Mantel-cox test determined effect of IR and PSP on OS and PFS. Fisher's exact test was utilized to correlate IR and PSP with genomic subtypes and MGMT status. RESULTS: Eighty-two patients with GBM were reviewed. The median OS and PFS were 17.9 months and 8.9 months. IR was observed in 28 (40%) and was associated with improved OS (median 29.4 vs 14.5 months p < 0.01) and PFS (median 17.7 vs 5.5 months, p < 0.01). PSP was observed in 14 (19.2%) and trended towards improved PFS (15.0 vs 7.7 months p = 0.08). Tumors with a proneural component had a higher rate of IR compared to those without a proneural component (IR 60% vs 28%; p = 0.03). MGMT methylation was associated with IR (58% vs 24%, p = 0.032), but not PSP (34%, p = 0.10). CONCLUSION: IR is associated with improved OS and PFS. The proneural subtype and MGMT methylated tumors had higher rates of IR.

An anatomic transcriptional atlas of human glioblastoma.

Glioblastoma is an aggressive brain tumor that carries a poor prognosis. The tumor's molecular and cellular landscapes are complex, and their relationships to histologic features routinely used for diagnosis are unclear. We present the Ivy Glioblastoma Atlas, an anatomically based transcriptional atlas of human glioblastoma that aligns individual histologic features with genomic alterations and gene expression patterns, thus assigning molecular information to the most important morphologic hallmarks of the tumor. The atlas and its clinical and genomic database are freely accessible online data resources that will serve as a valuable platform for future investigations of glioblastoma pathogenesis, diagnosis, and treatment.