Citations

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 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 Tumor Treating Field (TTF) therapy exerts antineoplastic effects through application of alternating electrical fields that disrupt mitotic machinery and induce DNA damage and activation of cell cycle checkpoints. However, despite extensive utilization in clinical practice for the management of glioblastoma, molecular markers for TTF sensitivity have proven elusive. METHODS To assess impact of molecular alterations on TTF response, we evaluated our institutional cohort of IDH wild type glioblastomas (n=449) for whom chromosomal microarray data was available. RESULTS A total of 142 patients were found to have undergone TTF treatment (31.6%) with improved overall survival (OS) (p=0.0049, univariate analysis). We assessed TTF treatment responses when stratified by alterations in the MDM2/4-TP53 axis, as well as the CDK4/6-RB1 axis, given well-described roles for these pathways on cellular responses to DNA damage and mitotic stressors. On univariate analysis, MDM2/4 amplified tumors treated with TTFs demonstrated significantly improved OS compared to untreated tumors (p=0.0012), and while MDM2/4-unaltered, TP53 intact tumors showed OS benefit from TTFs (p=0.0192), TP53-altered tumors did not demonstrate such benefit (p=0.6591). We confirmed these findings with multivariate Cox regression after adjusting for age and sex, where TTF therapy improved OS in MDM2/4 amplified tumors (HR 0.3881, p=0.0062) and a signal towards improved OS was seen in TP53 intact tumors (HR 0.7552, p=0.0509) but no such benefit was seen in TP53-altered tumors (HR 1.0025, p=0.9916). TTF therapy appeared to demonstrate improved OS in CDK4/6 amplified tumors (p=0.0116) on univariate analysis, with continued signal towards this effect on multivariate Cox regression (HR 0.5975, p=0.0870). CONCLUSIONS TP53 intact status and MDM2/4 amplification may represent previously unappreciated molecular markers for sensitivity to TTF therapy in IDH wild type glioblastoma. Confirmatory work with multi-institutional collaborations and evaluation of other potential prognostic factors are currently underway.

Abstract BACKGROUND Chromosomal instability is a well-recognized hallmark of tumorigenesis. However, it is not known how markers for chromosomal instability, such as total distance of DNA altered or total copy number variations (CNV), affect survival, particularly in IDH wild type glioblastoma. Additionally, whether alterations in pathways that impact cellular responses to chromosomal instability, such as the TP53 or RB1 axis, influence survival, similarly remain poorly understood. METHODS To better characterize potential prognostic impact of markers of chromosomal instability on patient outcomes, we assessed the Mayo Clinic cohort of IDH wild type glioblastomas (n=449) for whom chromosomal microarray data was available. RESULTS We found that while total distance of DNA altered on microarray analysis was not associated with overall survival (OS) (p=0.4030, univariate analysis), the least altered tumors (stratified by quartiles) when assessed by numbers of CNVs demonstrated improved OS (p=0.0057, univariate analysis). We next evaluated alterations in the MDM2/4-TP53 signaling axis, as well as the CDKN2A/B-CDK4/6-RB1 axis, as both amplifications and losses impacting these pathways have been well characterized in adult diffuse gliomas. While TP53 status was not predictive of OS (p=0.1504, univariate analysis), amplification of MDM2 or MDM4 was predictive of decreased OS (p=0.0071, univariate analysis). We also found that tumors without alterations in the CDKN2A/B-CDK4/6-RB1 axis had improved OS when compared to altered tumors (p<0.0001, univariate analysis). Multivariate Cox regression analysis, adjusting for age and sex, confirmed prognostic impact of MDM2/4 amplification status (HR 1.4090, p=0.0370) and CNV status (HR 0.6798, p=0.00312) on OS. CONCLUSIONS CNV status and MDM2/4 amplification represent previously unappreciated molecular markers for prognostication in IDH wild type glioblastoma. Further work is underway to confirm our findings through multi-institutional collaborations and to account for additional potential prognostic factors.

Abstract Telomere length variation is a hallmark of genomic instability, however, its role in shaping the structural variant (SV) landscape of diffuse astrocytoma remains poorly understood. In this study, we employed Oxford Nanopore long-read sequencing to investigate the association between SVs and chromosome arm-specific telomere length in a clinical patient cohort consisting of n = 20 individuals diagnosed with an IDH mutant astrocytoma. Oxford Nanopore long-read sequencing was performed to a depth of ~20-40× coverage. SVs were identified using Sniffles, copy number alterations were assessed using DNAcopy and chromosome arm-specific telomere length was estimated with Telogator. Statistical analyses were conducted to assess associations between telomere dynamics, structural variation, and copy number changes. Astrocytoma genomes exhibited a broad spectrum of structural variants, including deletions and insertions, with significant enrichment in the short arms of acrocentric chromosomes. A subset of samples demonstrated markedly shorter telomeres relative to the overall cohort, accompanied by an increased burden of structural variants, particularly duplications and inversions, suggesting enhanced genomic instability. Notably, a prominent accumulation of deletion and insertion SVs was observed near chromosome ends and centromeres, highlighting the (sub)telomeric and peri(centromeric) regions as SV hotspots. Statistical modeling revealed a significant association between telomere length and arm-specific variation, including telomeric deletions, inversions, and copy number losses. In summary, our findings reveal a previously underappreciated link between SVs and telomere length in astrocytomas. Genomic rearrangements caused by telomere shortening may represent critical drivers of genome instability and could serve as novel biomarkers for disease progression.

Abstract Imaging-based monitoring of gliomas is hampered by treatment-related changes, as well as the insidious growth of gliomas harboring the isocitrate dehydrogenase (IDH) mutation. The IDH mutation results in elevated D-2-hydroxyglutarate (D-2-HG), which is detectable in cerebrospinal fluid (CSF) that can be accessed longitudinally from multiple compartments, including cranially via CSF access devices. As such, we evaluated the early utility of CSF D-2-HG as a serially accessible biomarker for IDH-mutant gliomas. A CLIA-approved gas chromatography mass spectrometry assay was developed for CSF D- and L-2-HG. Lumbar and cranial CSF samples were collected from patients with IDH-mutant gliomas or IDH-wild-type brain tumors and non-tumor pathologies via surgical field collection, lumbar punctures, Ommaya reservoirs, and ventriculoperitoneal shunts. First, to confirm the ability of CSF D-2-HG to detect IDH-mutant gliomas, concentrations were compared between IDH-mutant gliomas and wild-type lesions. Cranial, but not lumbar, CSF D-2-HG distinguished primary IDH-mutant gliomas from IDH-wild type lesions (cranial AUC= 0.89, 95% confidence interval (CI)= 0.80-0.97); lumbar AUC= 0.52, 95% CI=0.28-0.76). Indeed, CSF D-2-HG was significantly higher in cranial than lumbar samples from IDH-mutant glioma patients (median lumbar=0.20 μM, cranial = 1.72 μM; p<0.0001), confirming a significantly elevated abundance of CSF D-2-HG only in cranial CSF from IDH-mutant gliomas. Then, response to cytoreduction was evaluated, demonstrating that cranial CSF D-2-HG levels decreased to 0.54x of baseline with resection in seventeen patients (p=0.0129). Changes in tumor-to-CSF contact impacted the serial evaluation of CSF D-2-HG prior to versus after chemoradiation in some patients. Nevertheless, in patients with grade 4 IDH-mutant astrocytomas, serial cranial CSF D-2-HG increased with disease progression and differentiated stability from pseudoprogression when tumor-CSF contact was sufficient. In conclusion, serial cranial CSF D-2-HG shows promise as a monitoring biomarker in patients with IDH-mutant gliomas, although anatomic variables must be considered in parallel to CSF D-2-HG evaluation.