Citations

Abstract Glioblastoma (GBM), the most aggressive primary brain tumor in adults, presents significant challenges due to its universal recurrence and limited survival rates, exacerbated when proximal to the lateral ventricles (LV). The subpopulation of brain tumor-initiating cells (BTICs) plays a pivotal role in tumor initiation and invasiveness, interacting with the microenvironment, particularly the cellular components in the subventricular zone (SVZ), like Neural Progenitor Cells (NPCs). Mechanisms of intercellular communication present in the SVZ include paracrine, autocrine, direct cell contact, and more recently extracellular vesicles (EVs). EVs are membrane-bound particles released by cells that are central to intercellular communication. They carry bioactive proteins, RNA, and other molecules that influence recipient cell behavior. This study investigates the role of EVs in GBM’s communication with non-cancer cells. Our findings indicate that BTIC-derived EVs promote migration and proliferation (*p < 0.02, ****p <0.001) in NPCs in vitro, highlighting the EVs’ role in altering the microenvironment. Additionally, we leverage a multi-omic approach to profile the small RNA and protein cargo of BTIC-EVs while also evaluating changes in the transcriptome of NPCs after BTIC-EV treatment. To identify the protein cargo contained in GBM-derived EVs, we utilized the innovative proximity-labeling system TurboID. We successfully induced TurboID expression in primary-cultured human BTICs from GBM patients, enabling the unbiased biotinylation of proteins in EVs. This method marks the first implementation of TurboID for unbiased global labeling of EV protein cargo in primary GBM cells. We identified unique miRNAs to be regulators of NPC’s transcriptome, and ontogenic analysis revealed upregulation of pathways involved in maintaining stem-like state, and upregulating PI3k-AKT, mTOR, and WNT signaling. This approach facilitates the investigation of EV-mediated communication and potential therapeutic targets, contributing to the understanding of GBM’s complex interactions with the brain’s microenvironment and the identification of biomarkers for improved diagnosis and treatment response.

Abstract Glioblastoma (GBM) is a highly treatment-resistant malignancy characterized by its poor prognosis and intrinsic resistance to therapy, driven largely by glioblastoma stem cells (GSCs) and an immunosuppressive tumor microenvironment (TME). This dual resistance plays a significant role in the failure of current treatment strategies. Consequently, there is an urgent need for novel therapeutic approaches that can effectively target GSCs while simultaneously reshaping the TME to promote anti-tumor immunity. In this study, we investigated the dual therapeutic potential of Xevinapant, a lead SMAC mimetic, through a combination of in vitro, in vivo, and single-cell transcriptomic analyses. We found that Xevinapant demonstrated potent anti-tumor activity through inducing dose-dependent apoptosis and significantly reduced cell viability in both human and mouse GSCs. In vivo administration of Xevinapant led to significant tumor suppression and extended overall survival in orthotopic models. Notably, our single-cell RNA sequencing result revealed that Xevinapant activated immune effector cell responses, contributing to the reprogramming of the immunosuppressive TME. Immune cell activation (both lymphoid and myeloid lineages) was further validated by flow cytometry using tumor-derived cells. To overcome potential therapeutic resistance, we derived Xevinapant-specific gene expression signatures and queried the LINCS database to identify small molecules with synergistic effects. Our analysis identified a promising compound ST-059620 that, when used in combination with Xevinapant, enhanced therapeutic efficacy and overcame resistance. Taken together, our findings highlight the dual mechanism of action of Xevinapant in targeting both tumor-intrinsic and microenvironmental resistance mechanisms. These results support the continued clinical development of Xevinapant and provide a strong rationale for combination strategies aimed at improving treatment efficacy in GBM.

Abstract BACKGROUND Despite multimodal treatment, brain tumors frequently recur and are often life-threatening. Patients commonly experience progressive neurologic decline, significantly impacting quality of life. We aimed to characterize the symptom burden of central nervous system tumors and to explore patient and caregiver experiences. METHODS In this observational study (NCT06676306), we conducted semi-structured interviews with 22 patients receiving care through the Mayo Clinic Neuro-oncology division. Caregivers were invited to participate. Demographic data were obtained from electronic medical records. Interviews were recorded, transcribed, and analyzed thematically. RESULTS Twenty-two patients (9/22, 41% female; median age 41.5 years, range 24–71) and 13 caregivers (13/22, 59%) participated. Diagnoses included astrocytoma, IDH mutant (8/22, 36%), glioblastoma (4/22, 18%), oligodendroglioma (3/22, 14%), astrocytoma, IDH wildtype (2/22, 9%), and other (5/22, 23%). The most frequently reported symptoms were headaches (13/22, 59%), cognitive changes (8/22, 36%), and fatigue (7/22, 32%). Among twenty patients who discussed treatment impacts, the most common were fatigue (45%), cognitive changes (40%), and mood changes (40%). Caregivers reported emotional toll (13/13, 100%), career changes (7/13, 54%), and difficulty balancing responsibilities (6/13, 46%). Twenty-one patients shared coping strategies, including faith (29%), hobbies (24%), and exercise (19%). All 20 respondents who discussed overall experience with neuro-oncology care reported a positive overall experience (100%), with the patient–neuro-oncologist relationship (40%) and communication (39%) cited as key contributors. For 19 patients who discussed treatment outcomes, quality of life (26%), maintaining function (21%), and tumor stability (21%) were paramount. For 9 caregivers who discussed treatment outcomes, 44% prioritized quality of life and 44% reported desire for a cure. CONCLUSIONS Brain tumors and their treatments affect patients and caregivers across physical, emotional, and social domains. Strong relationships and communication with the care team are central to patient satisfaction. Quality of life should be prioritized in neuro-oncology research and trials.

Abstract Case Description: A 73-year-old female with history of stage IIIC high-grade mixed endometroid and serous ovarian cancer in remission presented with lower extremity weakness and paresthesias for several months ultimately wheelchair bound by presentation. Her exam was notable for severe proximal greater than distal lower extremity weakness, allodynia, absent patellar and Achilles reflexes, and diminished vibration and pinprick sensation. MRI demonstrated symmetric enhancement of the spinocerebellar tracts in the lateral cord from T6-T9. EMG showed a length-dependent axonal predominant sensorimotor neuropathy. The differential included metabolic, paraneoplastic, or inflammatory etiologies of her myelopathy. CSF studies revealed TNCs 30, elevated kappa free light chain, and negative cytology. Autoimmune/paraneoplastic myelopathy panels were negative. With her past history of cancer, FDG PET performed showed a right hypermetabolic chest wall and upper abdominal mass. Core needle biopsy demonstrated recurrence of high-grade carcinoma of mullerian origin consistent with recurrence of ovarian cancer. Her in-hospital treatment included 5 days of 1g IV methylprednisolone and seven sessions of PLEX. Her exam improved following PLEX with improvements in strength, sensation, and neurogenic bowel and bladder. She also started Carboplatin and Doxorubicin chemotherapy prior to discharge. She continued 60mg prednisone after discharge. She unfortunately had many hospitalizations for infections and anemia impacting her neurological recovery and strength has declined. Discussion: This case illustrates an interesting case of paraneoplastic myelopathy as the presenting symptom for relapsed ovarian cancer previously in remission for more than 10 years. The case shows the importance of keeping a paraneoplastic process on the differential when imaging findings and clinical syndrome are consistent with a paraneoplastic myelopathy even though the patient did not have a known, active cancer or positive antibodies identified. The work-up for malignancy is crucial as cancer-specific therapy is needed for hopeful symptom improvement.

Abstract BACKGROUND Diffuse midline gliomas (DMGs) and posterior fossa group A (PFA) ependymomas are aggressive pediatric brain tumors. Most DMGs harbor histone H3.3K27M or G34R mutations, or exhibit EZHIP overexpression. With a median survival of just 9–15 months, DMGs are among the most lethal human cancers. PFAs, nearly universally overexpress EZHIP and have a 5-year survival rate of ~50%. Unlike K27M or EZHIP-overexpressing DMGs, G34R-mutant tumors retain H3K27me3. METHODS Using the RCAS/Nestin-TVA system, we introduced H3.3 K27M–, G34R–, or S31A–P2A–PDGFβ or H3.3WT–P2A–PDGFβ into neonatal mice. Controls included, histone mutants EZHIP alone and ΔEZHIP (PRC2-binding-deficient). Tumor bearing mice were assessed for incidence, grade, survival, and H3K27me3 and H3.3S31P status. RESULTS H3.3K27M, G34R, and S31A–P2A–PDGFβ induced high-grade gliomas with significantly reduced survival (p < 0.001). Mechanistically, G34R—like K27M—reduced mitotic Ser31 phosphorylation (S31P), causing chromosomal instability and impaired p53 checkpoint function. S31A directly modeled loss of S31P and similarly drove high-grade tumor formation. H3.3WT–P2A–PDGFβ induced only low-grade lesions. EZHIP–P2A–PDGFβ enhanced tumor grade but not survival; only EZHIP fully abolished H3K27me3. ΔEZHIP and all unlinked constructs were non-tumorigenic. CONCLUSION These models establish a robust platform to dissect glioma drivers and chromatin vulnerabilities. We previously showed that H3.3K27M reduces S31P, promoting chromosomal instability and impaired p53 function. We now demonstrate that H3.3G34R also reduces S31P and drives tumor formation in vivo. Direct loss of S31P via H3.3S31A is likewise sufficient for gliomagenesis. Although EZHIP does not alter S31P, it promotes genome instability through distinct mechanisms—disrupting PALB2–BRCA2-mediated DNA repair and mislocalizing TopoIIα, a process dependent on H3K27me3. H3.3K27M, G34R, and EZHIP thus converge on genome instability through distinct pathways. This platform supports mechanistic and therapeutic studies and is now being expanded using tetracycline-regulated expression to investigate tumor maintenance.

Abstract Glioblastoma (GBM) progression and recurrence are often driven by therapy-resistant cellular states emerging within hypoxic tumor niches. While hypoxia is a hallmark of GBM, the spatial transcriptomic heterogeneity that underpins resistance in these regions remains poorly characterized. Here, we employ pimonidazole labeling in conjunction with high-resolution spatial and single cell transcriptomics across 29 primary, treatment-naive human GBM samples, syngeneic mouse models, and patient-derived glioma-initiating cells exposed to hypoxia to define the hypoxia-specific tumor microenvironment and its associated cellular programs. We reveal spatially organized sub-niches within hypoxic regions, each supporting diverse cellular programs yet coexisting tumor lineage states with minimal transitions between cell states. Phylogenetic reconstruction based on inferred copy number variations demonstrates consistent evolutionary trajectories from non-hypoxic to hypoxic tumor loci. Specific copy number alterations were enriched in hypoxic regions and associated with immune infiltration and poor prognosis in MGMT-methylated tumors. Cross-species analyses confirmed the conservation of hypoxia-associated gene programs and spatial architectures. Together, our study delineates the cellular, evolutionary, and spatial complexity of hypoxia in GBM, identifies hypoxia-induced genomic alterations that may promote tumor fitness, and offers insights into new therapeutic vulnerabilities within hypoxic niches.

Abstract BACKGROUND Poly(ADP-ribose) polymerase inhibitors (PARPi), initially developed for BRCA-mutant tumors, are now being explored in gliomas to target DNA repair defects. In this retrospective analysis, we report our institutional experience using PARPi with temozolomide for glioma treatment. METHODS The medical record was retrospectively reviewed at our institution for neuro-oncology patients treated with off-label PARPi combined with temozolomide for > 1 month between 1/1/2010 and 5/1/2025. RESULTS Nineteen patients (median age 45, 47% female) were included. PARPi included olaparib (n = 18) and niraparib (n = 1). Tumor types were glioblastoma (GBM, n = 7), Grade 4 IDH-mutant astrocytoma (G4A, n = 4), Grade 3 astrocytoma (G3A, n = 2), Grade 3 oligodendroglioma (G3O, n = 3), Grade 2 oligodendroglioma (G2O, n = 2), and IDH1-mutant brainstem glioma (BG, n = 1; IDH status determined per CSF 2-hydroxyglutarate without surgically confirmed histologic subtyping). Patients were heavily pre-treated. One patient lost to follow-up was censored at last contact. Patients had KPS ≥ 70 in all but one case (KPS 60) and multiple prior progressions (treatment was initiated at 4th recurrence or higher in 16/19 patients). Median time from drug initiation to progression, drug initiation to death, and overall survival were as follows (months): GBM (3.0, 6.5, 34.9), G4A (1.4, 3.9, 80.3), G3A (3.4, 4.2, 83.3), G3O (3.8, 17.2, 121.2), G2O (3.0, 3.5, 159.9), BG (4, 5.5, 164.8). CONCLUSIONS This retrospective analysis supports the tolerability of combining PARPi with temozolomide in a real-world, heavily pretreated glioma population. Despite limited evidence of durable tumor control, the regimen provided transient disease stability in patients with few remaining options. These findings may inform treatment in compassionate or salvage settings particularly when alkylator treatment is considered, and highlight the need for prospective trials to identify response biomarkers and assess clinical utility.

Abstract BACKGROUND The IDH inhibitor vorasidenib was FDA-approved for treatment of IDH-mutant grade 2 gliomas in August 2024. We evaluated vorasidenib in patients with grade 3 and 4 IDH-mutant gliomas who would not have been eligible for the INDIGO trial. METHODS Retrospective review of patients with grade 3 or 4 IDH-mutant gliomas treated with vorasidenib between 9/1/24 and 5/31/25. Prior treatments, radiographic response, adverse events and seizure control were collected for each patient. RESULTS Thirty-two patients (median age 39.5, 46.9% female) met inclusion criteria. Tumor types included grade 3 oligodendroglioma (11, 34.4%), grade 3 astrocytoma (13, 40.6%) and grade 4 astrocytoma (8, 25%). Thirty patients had contrast-enhancement; 2 patients had non-enhancing tumor. Prior treatments included surgical resection (30, 93.8%), radiation (27, 84.4%), cytotoxic chemotherapy (25, 78.1%), bevacizumab (5, 15.6%), pembrolizumab (3, 9.4%), and ivosidenib (8, 25%). Four patients (12.5%) were naïve to systemic treatment at the time of vorasidenib initiation. Median duration of vorasidenib was 101.5 days (range 18-255) with 19 patients still on vorasidenib at the time of last follow-up. Seventeen patients (53.1%) had stable disease, 11 (34.4%) had progressive disease, 2 (6.3%) did not yet have response assessment, and 2 (6.3%) died. Grade 1 transaminitis occurred in 12 patients with no high grade transaminitis. Two patients developed lymphopenia; both were heavily pre-treated with multiple alkylating agents; no other hematologic toxicity was noted. One patient developed myalgias leading to vorasidenib discontinuation. Nine patients had fatigue, 4 headaches, 2 nausea, 2 decreased appetite. In patients with a history of epilepsy, there were no reported seizures. CONCLUSIONS Vorasidenib was well-tolerated in this heavily pre-treated cohort of grade 3–4 IDH-mutant gliomas, with low-grade transaminitis and fatigue being the most common toxicities. Preliminary results show disease stability in 53.1% of patients after a median of 3.5 months. Conclusions are limited by short-interval follow-up.

Abstract Glioblastoma (GBM) is an aggressive brain tumor with poor outcomes due to resistance to radiation and temozolomide (TMZ). Death receptor 5 (DR5), a proapoptotic receptor, induces tumor-selective apoptosis upon activation, is expressed in GBM, and can be upregulated by radiation/TMZ. Ozekibart (INBRX-109), a tetravalent DR5 agonist antibody, has demonstrated tolerability and clinical benefit as monotherapy in chondrosarcoma (PMID: 37265425), prompting a phase 2 trial (NCT04950075), and in combination with irinotecan and TMZ in Ewing’s sarcoma. INBRX-109 was evaluated in GBM using in vitro and in vivo models. DR5 expression in cell lines was determined by flow cytometry and drug sensitivity was measured using CellTiter-Glo®. Efficacy of INBRX-109 as a single agent and in treatment combinations was evaluated in intracranial U87-MG and patient-derived xenograft (PDX) models with activity assessed by survival and tumor imaging. Pharmacodynamic activity was assessed by immunohistochemistry (IHC) for cleaved caspase-3 and PARP. TMZ upregulated DR5 and sensitized U87-MG cells to INBRX-109. GBM cell lines (n=33) exhibited variable sensitivity to INBRX-109 and TMZ as single agents, but a majority showed enhanced sensitivity to combination treatment. In the U87-MG model, combination therapy improved tumor control and survival versus TMZ alone (tumor volume fold increase over baseline 1.1 vs 7.4; median survival 44 vs 36d). IHC staining of tumors indicated INBRX-109 crosses the blood brain barrier and is pharmacologically active. In three PDX models, INBRX-109 improved survival as monotherapy (survival ratios 1.38, 1.47, 1.50). In two models, combination therapy improved survival vs TMZ (survival ratios 1.76 vs 0.93, 2.47 vs 1.94). In summary, TMZ upregulates DR5 and enhances INBRX-109 activity in intracranial GBM models. This combinatorial activity and potential for synergy with radiation/TMZ support clinical evaluation of INBRX-109 in GBM. Moreover, the established clinical safety and activity of INBRX-109 in solid tumors support its development in this indication.

Abstract Glioblastoma, IDH-wildtype (GBM), and primary central nervous system lymphoma (PCNSL) are two aggressive brain tumors with distinct treatment strategies but overlapping imaging features on MRI. Accurate preoperative differentiation remains a clinical challenge, due to their overlapping imaging features, even when advanced MRI techniques are employed. This study explored deep learning approaches leveraging multi-sequence MRI to distinguish GBM from PCNSL. Models were developed utilizing 146 PCNSL cases, which were matched to146 GBM by age, sex and year of diagnosis. A 3D-DenseNet121 convolutional neural network was trained using two analytical strategies: (i) loss-based model selection and (ii) ensemble prediction using five-fold cross-validation. Model performance was evaluated on an independent validation set of 256 GBM and 37 PCNSL from the same institution as well as 36 PCNSL cases from an external institution. All MRIs were preprocessed using the FeTS pipeline. Using the independent validation cohort, area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CI) were computed overall and stratified by demographic characteristics. Using both T1 post-contrast (T1Gd) and T2-weighted images, the loss-based model achieved AUC=0.83 (95% CI: 0.77-0.88) and the ensemble model yielded an AUC=0.82 (95% CI: 0.76-0.89). Model performance was similar across males and females; however, model performance was better for subjects older than 50 years of age versus younger than 50. When using only T1Gd images, the loss-based model dropped to AUC=0.55 (95% CI: 0.48-0.63), whereas the ensemble model had AUC=0.79 (95% CI: 0.72-0.85). Models trained with only T2 images achieved AUCs of 0.67 (95% CI: 0.60-0.73) (loss-based) and 0.75 (95% CI: 0.69-0.82) (ensemble). These results highlight the added value of the multi-sequence input. Our results confirm the feasibility of using automated deep learning models to differentiate GBM from PCNSL. Notably, the model generalized well to external MRI data, emphasizing its potential utility as a diagnostic aid in real-world clinical workflows.