Vaubel, Rachael A.

Abstract Background Murine double minute 2 (MDM2) inhibitors reactivate wild-type p53 and are a promising therapy for glioblastoma, IDH-wildtype (GBM). Brigimadlin is a highly potent MDM2 inhibitor being tested in a phase 0/1 clinical trial in combination with radiation in GBM. Methods Brigimadlin pharmacokinetics, pharmacodynamics, and efficacy were evaluated in GBM patient-derived xenografts (PDXs). Results In vitro, brigimadlin impaired viability in TP53 wild-type GBM with an IC50 of 0.8-6.6 nmol/L, but sensitivity did not correlate with MDM2 amplification. In vivo, MDM2 amplification was highly correlated with efficacy. In subcutaneous PDXs, 1 or 2 mg/kg brigimadlin dosed weekly was highly effective in 2 MDM2-amplified PDXs. At 2 mg/kg, brigimadlin delayed tumor regrowth by >5-fold in the MDM2-amplified PDXs compared to 1.5-fold in a non-amplified PDX. In orthotopic PDXs, efficacy was more limited, but 2 mg/kg brigimadlin enhanced the response to fractionated radiation in MDM2-amplified PDXs. Consistent with blood-brain barrier efflux limiting drug distribution, 2 mg/kg brigimadlin extended survival by >5-fold in an MDM2-amplified orthotopic PDX established in Rag1−/−Abcb1a−/− Abcg2−/− mice. In pharmacodynamic studies, p53 target genes were upregulated at both subtherapeutic and therapeutic dose levels, and the extent of activation did not correlate with MDM2 status. Concentrations of brigimadlin in tumor tissue were approximately 10-fold higher in MDM2-amplified tumors, and intracellular drug levels directly correlated with drug-dependent MDM2 upregulation, suggesting target binding affects drug accumulation. Conclusions Brigimadlin is highly effective in MDM2-amplified GBM when adequate drug levels are achieved in tumor tissue. MDM2 amplification impacts both treatment efficacy and intratumoral drug accumulation.

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.

Abstract Glioblastoma (GBM) diagnosis integrates morphology and tumor molecular alterations. Patients with classic morphology are designated as histologic GBM (hGBM). Patients without classic morphology harboring TERT promoter mutation (TERTp), or epidermal growth factor receptor amplification (EGFRamp), or combined gain of chromosome 7 and loss of 10 (+7/-10) designate molecular GBM (mGBM). We compared radiographic features, genomic alterations, and clinical outcome between hGBM and mGBM. 109 mGBM Mayo Clinic cases diagnosed between 1993-2021 were matched to 101 cGBM by age, sex, year of diagnosis, and TERT promoter (TERTp) status. Clinical and radiographic data abstraction was blinded. Progression-free and overall survival were compared across groups in the subset of patients who received standard of care. Contrast enhancement was present on index MRI (MRI at diagnosis) for 98% (96/98) hGBM and 50% (54/107) mGBM (p<0.0001) patients. mGBM tumors harbored fewer total copy number alterations (median of 16.5 vs 20, p=0.029) and were less likely to have CDKN2A/B homozygous deletion (56% vs 77%, p=0.005). Among the 87 mGBM and 82 hGBM receiving standard of care, median overall survival was longer for mGBM versus hGBM (2.24 vs 1.62 years, p=0.016). mGBM patients with +7/-10 (HR=2.60, p=0.035) or CDKN2A/B (HR=3.61, p=0.002) had poorer overall survival compared to mGBM patients without the corresponding alteration. On index MRI mGBM patients without contrast enhancement had better overall survival compared to hGBM (HR=0.50; p=0.003) whereas there was no survival difference between mGBM with enhancement and hGBM. mGBM with enhancement on index MRI likely represent undersampled, or early / evolving hGBM. mGBM patients with non-enhancing MRI, younger than 60, with long symptom profile including seizures, and some combination of non-anaplastic morphology, TERTp only, no homozygous deletion of CDKN2A/B, and low copy number complexity may represent other IDHwt glioma entities. Caution is advised in counseling, management, discussing prognosis, and inclusion in clinical trials.

Abstract The 2021 WHO classification redefined glioblastoma IDH-wildtype (GBM), integrating histopathological and tumor molecular features. Diffuse astrocytic glioma lacking histologic features of necrosis and microvascular proliferation are classified as (molecular) GBM if the tumor is IDH- and H3-wildtype and has one or more additional tumor molecular alterations: TERT promoter mutation, EGFR amplification, or +7/-10. Due to the absence of histopathological features of classic GBM and presentation without enhancement on MRI in approximately 50% of cases, molecular GBM frequently resemble low-grade IDH-mutant gliomas. We hypothesized that MRI-based deep learning models could distinguish IDH-mutant glioma from molecular GBM. We retrospectively identified 97 individuals with molecular GBM, who were matched to 97 individuals with IDH-mutant glioma by age, sex, year of diagnosis, and enhancement on MRI. Of the 97 IDH-mutant gliomas, 51% were 1p/19q codeleted, 42% grade 2, 47% grade 3, and 10% grade 4. Preoperative postcontrast T1-weighted (T1C) and T2-weighted (T2) MRI sequences were used to train a 3D-DenseNet121 model. The model was validated on an independent prospective set of 150 IDH-mutant gliomas and 71 molecular GBM. The MRI-based deep learning model achieved an area under the receiver operator curve (AUC) of 0.75 (95% CI: 0.68-0.82) in the prospective validation set. Sex-stratified AUCs were 0.72 (95% CI: 0.59-0.85) for females and 0.76 (95% CI: 0.68-0.85) for males. Age stratified AUCs were 0.71 (95% CI: 0.60-0.83) for patients under 55 years of age and 0.64 (95% CI: 0.50-0.79) for patients older than 55. These results suggest that discriminative MRI features of IDH-mutant glioma and molecular GBM exist and can be identified from deep learning models. However, radiographic ambiguity exists and underscores the need for further optimization of the deep learning architecture or by integrating additional non-invasive modalities. For example, future work entails integrating germline variants into the model, including rs55705857, which is a causal variant for IDH-mutant glioma. With further validation and integration of multi-modal data, a noninvasive tool may support more personalized decision-making.

Abstract IDH-wildtype diffuse astrocytic gliomas with lower-grade histological features alongside specific genomic alterations (e.g., TERT promoter mutation, EGFR amplification, gain Chr7/loss Chr10) are presently diagnosed as glioblastoma, IDH-wildtype (GBM) under WHO 2021 criteria. Previous analyses categorized these into “early/evolving” or “surgically undersampled” GBMs. However, it remains unclear whether these tumors share identical clinical and prognostic features with histologic GBM. Data from IDH-wt molecular GBMs across six institutions were aggregated. Astrocytic IDH-wt tumors of any grade that lacked necrosis or microvascular proliferation on initial histopathology yet exhibited molecular alterations consistent with WHO 2021 GBM diagnosis, were included. Recursive partitioning analysis (RPA) was used to categorize patients into risk groups based on overall survival (OS). Among the 264 patients included, the median age was 60 years (IQR: 51-67), with 162 (61%) being male. Additionally, 210 (80%) were diagnosed since 2016, and 216 (82%) received chemoradiation plus adjuvant temozolomide (GBM-SOC). The median follow-up period was 3.9 years (95% CI: 3.4, 4.6). Identified univariate risk factors for worse survival included older age, biopsy-only status, EGFR amplification, absence of initial adjuvant treatment, low post-operative KPS, and tumor histologic grade of 3. RPA divided patients into four distinct survival groups (p<0.0001). The “best” risk group comprised lower grade (<=2) tumors (n=58, median OS (mOS): 40 months (95% CI: 33, NA)). The “second best” group included Grade 3 patients receiving GBM-SOC without steroids during initial RT (n=139, mOS: 25 months (95% CI: 22, 28)). The “second worst” group encompassed Grade 3 patients who were on steroids during initial RT while receiving GBM-SOC (n=38, mOS: 15 months (95% CI: 13, 20)). The “worst” group contained Grade 3 tumors that had not undergone SOC (n=29, mOS: 9 months (95% CI: 4, 26)). These data show that histologic features and treatment are strong indicators of patient outcomes.

Abstract WSD0922-Fu is an oral, CNS-penetrant, small molecule EGFR inhibitor which potently inhibits EGFR aberrations specific to non-small cell lung cancer (NSCLC) and glioblastoma (GBM). MC1914 (NCT04197934) is a first-in-human phase 1 trial in patients with EGFR aberrant recurrent GBM and NSCLC. After determining the maximum tolerated dose, adults with recurrent GBM were treated in two expansion cohorts: (a) non-surgical cohort (6/12 patients thus far): EGFRvIII mutation, first recurrence; food-effect study included (b) surgical cohort (6/6 patients), any EGFR mutation, any recurrence; window-of-opportunity study (WOO) included. Among these 12 patients, median age = 60 years; 50% female; 58% ECOG 0). All patients received prior radiation and temozolomide. After the WOO or food-effect study, patients were dosed at 120 mg BID (5 days on, 2 days off), and escalated to 160 mg BID (5 days on, 2 days off) based on tolerability. Common adverse events (>40%) are comparable to other EGFR inhibitors (acneiform rash, diarrhea, fatigue, xerosis, pruritis). Treatment-related grade 3+ adverse events were limited to lymphopenia (n = 1). WSD0922-Fu exposure in the fed state exceeded the fasted state (median plasma Cmax and AUC0-24h are 1.6x and 1.3x, respectively) with a delayed Tmax (6.0 vs 1.8 hours). For the WOO, time between last dose administered to tumor collection ranged between 4 - 13.5 hours. Median tumor WSD0922-Fu concentration was 0.76 µg/g; estimated median unbound tumor concentration was 24.9 ng/g and within expectations for pharmacodynamic effect. Median brain/plasma ratio = 0.59; median unbound brain/unbound plasma = 0.88. Enrollment to the non-surgical cohort is ongoing, so formal efficacy data remain immature. However, examples of clinical efficacy will be shown along with data on recurrence patterns. Phase 2 clinical trial development is in progress.

Abstract The WHO 2021 classification of central nervous system tumors incorporated molecular markers to better define diffuse glioma subgroups. We analyzed array-based copy number, targeted next-generation sequencing, germline genotyping, and Illumina EPIC array methylation data from 404 primary IDH-mutant astrocytomas to further understand the relationship between copy number and outcomes. Loss of chromosome arm 13q was associated with poor overall survival after adjusting for age, sex, tumor grade, and treatment status (hazard ratio [HR]=2.04 (95% confidence interval: 1.25-3.33), p=0.004). Chromosome 13q loss was also significantly associated with the total number of copy number alterations (p<0.001). Loss of arm 11p was associated with poor survival in the adjusted analysis (HR=2.29 (1.38-3.79), p=0.001). Unsupervised clustering of the raw copy number data identified 12 clusters, where each cluster was defined by distinct copy number alteration(s). Clusters that contained 13q loss exhibited worse overall survival compared to other clusters. The clusters were significantly associated with age at diagnosis (p=0.015), tumor grade (p<0.001) and copy number complexity (p<0.001). The clusters with a high proportion of grade 4 tumors and with the highest complexity had the poorest overall survival. These findings highlight the prognostic relevance of chromosome 13q and 11p losses in IDH-mutant astrocytomas and support the integration of additional copy number alterations into molecular classification frameworks of IDH-mutant astrocytomas to improve risk stratification and patient management.

Abstract BACKGROUND Pembrolizumab is FDA approved for solid tumors with high tumor mutation burden (TMB) and may thus have efficacy in hypermutant glioma. This study aimed to identify factors influencing efficacy of pembrolizumab in recurrent glioma. METHODS This retrospective study at Mayo Clinic included patients with adult-type diffuse gliomas who received pembrolizumab (≥2 cycles) for recurrent disease (01/01/2014–05/01/2025). The Mayo Clinic Solid Tumor Panel (MCSTP), which uses the Illumina TruSight Oncology 500 High-Throughput next-generation sequencing (NGS) assay, was also used to assess the molecular characteristics of the recurrent tumors. Responders to pembrolizumab were defined as patients who did not meet RANO 2.0 criteria for progressive disease on first radiographic response assessment. Progression-free survival (PFS) was analyzed using Kaplan-Meier and Cox-Regression analyses. RESULTS Sixty-two patients were identified (median age: 46 years; 65% male; 94% white). All patients received pembrolizumab and had prior alkylating chemotherapy. The median PFS from pembrolizumab initiation was 2.3 months. Twenty-five (40%) patients were responders. Patients with IDH-mutant, 1p/19q co-deleted gliomas (OLIGO, n=13) had a longer PFS (4.3 months) than IDH wildtype gliomas (IDH-WT, n=33, 2.2 months, p=0.012) and IDH-mutant, 1p/19q non-co-deleted (IDH-MUT, n=16, 1.7 months, p=0.0006). The proportion of responders was significantly greater in OLIGO patients (IDH-WT, 33%; IDH-MUT, 19%; OLIGO, 85%, p=0.0008). Overall PFS was not impacted by patient age, sex, or extent of initial resection. Twenty-nine percent of patient tumors tested thus far (6/21) had a high TMB (≥10 mut/Mb). Two-thirds (4/6) of high TMB patients were responders, while only one-third (5/15) of low TMB patients were responders. CONCLUSIONS Patients with recurrent OLIGO may have a longer PFS with pembrolizumab therapy than IDH-WT and IDH-MUT. Furthermore, high TMB may be associated with longer PFS with pembrolizumab therapy in glioma. Additional patients are being assessed using MCSTP (total expected n=43); complete data will be presented.

Abstract BACKGROUND High-grade and recurrent meningiomas frequently demonstrate aggressive behavior and therapeutic resistance, with limited treatment options. Dysregulation of the MAPK and FAK pathways drive meningioma progression, but compensatory activation between these pathways could limit single agent efficacy. Recently, a clinical trial (Alliance A071401) showed encouraging efficacy of single-agent FAK inhibition in recurrent/progressive meningioma (Brastianos et al, JCO 2023). This preclinical study aimed to evaluate the therapeutic potential of dual RAF/MEK (avutometinib) and FAK (VS-4718) inhibition in suppressing tumor growth and improving survival in intracranial meningioma models. METHODS Orthotopic intracranial models were established by injecting IOMM-Lee (Fluc-mCherry) or CH157-MN (eGFP-LUC2) cells into nu/nu mice. Mice were randomized into four groups: vehicle, VS-4718 (murine formulation of defactinib, 50 mg/kg, BID), avutometinib (0.3 mg/kg, QD), or combination therapy. Treatments were administered for a 4-week period. Tumor growth was monitored via bioluminescent imaging (BLI) at baseline, midpoint, and study endpoint. Pharmacokinetic (PK) and pharmacodynamic (PD) effects were assessed by intratumoral drug concentrations and Western blotting for p-ERK and p-AKT, respectively. RESULTS In the NF2-mutant CH157-MN model, avutometinib increased median survival from 12.5 to 20.5 days (p=0.001), while combination therapy extended survival further to 22 days (p<0.0001 vs vehicle). Similarly, in the NF2-wildtype IOMM-Lee model, avutometinib raised survival from 27.5 to 33 days (p=0.0237), with combination therapy reaching 34.5 days (p=0.0057 vs vehicle). VS-4718 monotherapy did not extend survival in both models. BLI demonstrated significant inhibition of tumor growth in both avutometinib and combination groups in both tumor models. PK analysis revealed Kp values of 0.26–0.37 for avutometinib and 0.46–0.50 for VS-4718 in orthotopic tumor tissue. Furthermore, combination therapy lowered p-ERK in tumors (p=0.001) compared to vehicle. CONCLUSION Dual RAF/MEK and FAK inhibitor therapy blocks MAPK activation and enhances survival in orthotopic meningioma models, supporting further clinical evaluation for aggressive meningiomas.

Abstract Background Disruption of the blood–brain barrier (BBB) in high-grade brain tumors is characterized by contrast accumulation on diagnostic imaging. This window of opportunity study correlates contrast imaging features with the tumor distribution of BBB-permeable (levetiracetam) and -impermeable (cefazolin) drugs. Methods Patients with a clinical diagnosis of a high-grade brain tumor underwent MRI for surgical planning. Cefazolin and levetiracetam were administered prior to skin incision, and serial plasma and image-registered tumor samples were collected during the operation. Drug levels were measured by LC-MS/MS, tissue drug levels were corrected for residual blood, and tumor-to-plasma concentration ratios were calculated. Intraoperative microdialysis was performed in a subset of patients to measure the same two drugs. Results Tumor (n = 125) and plasma (n = 261) samples were available for analysis from 42 operative cases. Across all samples, the tumor-to-plasma ratio was significantly lower for cefazolin (marginal mean [MM]: 0.15, 95% CI: 0.11–0.19) as compared to levetiracetam (MM: 0.70, 95% CI: 0.64–0.75; P < .001). When compared between contrast-enhancing and non-enhancing regions, tumor-to-plasma ratios for cefazolin varied by 4.4-fold (0.27, 95% CI: 0.20–0.35 vs. 0.06, 95% CI: 0.04–0.08, respectively; P < .001), and varied for levetiracetam by 1.4-fold (0.88, 95% CI: 0.78–0.97 vs. 0.61, 95% CI: 0.55–0.66, respectively; P < .001). These results were confirmed with the intra-operative microdialysis and a population pharmacokinetic analysis. Conclusions This study demonstrates significant inter- and intra-tumoral heterogeneity in drug delivery for both levetiracetam and cefazolin within high-grade brain tumors that is not necessarily predicted by clinical MR imaging and may reflect tumor-induced changes in both perfusion and BBB integrity.