Citations

Abstract INTRODUCTION Accurately mapping sensorimotor regions is crucial for preserving motor and sensory functions in the treatment of gliomas located in the peri-Rolandic areas of the brain. OBJECTIVE We examined the use of high-density electrocorticography (ECoG) for passive mapping of sensorimotor regions in treating peri-Rolandic gliomas by analyzing the spatial-temporal and spectral features of real-time somatosensory evoked potentials (SSEPs), and their spectral patterns in differentiating states of consciousness. METHODS During surgery, SSEPs were recorded using high-density ECoG on fourteen patients (n=14), both in anesthetized and awake states. Neural data from 0.6Hz median nerve stimulation were captured at 2.4kHz and processed in real-time using MATLAB Simulink. The system displayed SSEPs’ peak activations as a 2D heat map on a screen, particularly around the 20ms time point (N20), and generated the spectral power in the gamma range using the Stockwell transform. Accuracy in delineating the central sulcus (CS) was assessed using the ROC curve, and paired t-tests compared gamma oscillations between states of consciousness. RESULTS Patients consistently showed clear discrimination between anterior and posterior channels at the 20ms time point, with 93.6±14.9% accuracy. Color contrast delineated the CS, correlating with the sulcus in the 3D reconstructed magnetic resonance imaging of each patient. Late gamma (60–250 Hz) modulation occurred 50 ms after stimulation onset, extending up to 250 ms in the primary somatosensory area. It was suppressed in the anesthetized state and significantly increased in the awake state (delineation accuracy: 81±10.3% and 91±13.4%, respectively). CONCLUSIONS These results demonstrate that SSEPs and gamma modulations can delineate sensorimotor areas and assess consciousness, significantly impacting neurosurgical planning.

Abstract Advancements in understanding H3 K27-altered diffuse midline glioma (DMG) biology have not yet translated into effective therapies for these tumors likely due to delivery challenges across the blood-brain barrier (BBB) and variable tumor genetics. This study systematically probes convective-enhanced delivery (CED) as a means to administer small molecule drugs directly to DMG tumors, circumventing constraints imposed by the BBB. Our findings emphasize the necessity of strategic drug selection and pharmacokinetic analysis in refining CED approaches, advocating for precision medicine techniques specialized for DMG. We demonstrate that while most small molecule drugs are rapidly cleared from the brain following CED, their retention and effectiveness are substantially improved by co-administration of systemic efflux transporter (ET) inhibitors such as everolimus. The synergistic potential of combining everolimus with topotecan or ponatinib offers a novel therapeutic pathway, advocating for further investigation into this DMG management strategy.

Abstract The prevalence of asymptomatic, incidental meningiomas is increasing due to greater frequency of brain imaging. This retrospective cohort study of adult patients presenting at a single institution from 1996-2020 integrated clinical data, serial magnetic resonance imaging (MRI) volumetrics, DNA methylation profiling, and targeted gene expression profiling to define the natural history and molecular architecture of incidental meningiomas. Volumetrics were calculated from contrast-enhanced brain MRIs at time of diagnosis compared to serial surveillance MRIs (average 3 MRIs per patient pre-intervention, range: 1-12) DNA methylation groups and gene expression risk scores were defined for 123 samples that underwent resection. Time-to-event analyses were performed for progression-free survival (PFS), symptom-free survival (SFS), and treatment-free survival (TFS). The cohort included 238 meningiomas from 207 patients. Median age at diagnosis was 59 years and 81.5% of patients were female. Median clinical and imaging follow-up were 9.1 and 6.7 years, respectively, during which time 50.8% progressed. Median maximum diameter and volume at diagnosis were 2.20 cm and 4.25 cm3, respectively, and median pre-treatment volumetric growth rate was 19.2% per year. Median pre-treatment PFS and TFS were 3.10 and 1.27 years, respectively, and median SFS and post-treatment PFS were not reached. Cox proportional hazards regression identified maximum diameter at diagnosis as a significant predictor of worse pre-treatment PFS (multivariate HR 1.65 per 1 cm [95% CI 1.19–2.28], p=0.0027) and worse TFS (multivariate HR 1.44 per 1 cm [95% CI 1.17–1.76], p<0.001). Skull base tumors had with worse SFS (multivariate HR 2.48 [95% CI 1.02–6.00], p=0.045). Molecular and histological features among incidental meningiomas that ultimately underwent resection (n=176, 74.0%) were reassuring (89.2% WHO grade 1, 10.2% WHO grade 2). These findings suggest maximum diameter at diagnosis of incidental meningiomas is significantly associated with earlier progression and eventual treatment, and skull base tumors have earlier symptom development.

Abstract BACKGROUND Standard of care treatment for recurrent malignant glioma after prior radiotherapy (RT) is not well established. Proton therapy (PT) is increasingly used for reirradiation (ReRT) at the time of recurrence; however, treatment outcomes, toxicity, and prognostic factors for patients treated with PT-ReRT remain poorly defined. METHODS The prospective, multi-institutional Proton Collaborative Group (PCG) registry was queried for patients with malignant glioma who previously received RT and underwent PT-ReRT between 7/2011-12/2023. Overall survival (OS) and progression-free survival (PFS) were assessed using the Kaplan-Meier method, and Cox proportional hazards regression was used for uni- and multivariate analysis (UVA and MVA). Dose was calculated using equivalent dose in 2-Gy fractions (EQD2). RESULTS 143 consecutive patients were identified. Median follow-up was 11.2 months and median time interval (TI) from prior RT (median 58.5 Gy) to PT-ReRT (median 44.6 Gy) was 42.4 months. Primary histology was glioblastoma (n=74), astrocytoma (n=35), and oligodendroglioma (n=34). Median PFS and OS were 8.1 and 11.2 months, respectively. On UVA, improved OS was associated with oligodendroglioma (HR 0.37) and astrocytoma histology (HR 0.53) compared to glioblastoma, TI >60 months (HR 0.2), CNS WHO Grade 2 compared to 4 (HR 0.42), and ECOG performance status 0 (HR 0.47). On MVA, improved OS remained associated only with oligodendroglioma (HR 0.42) and TI >60 months (HR 0.49). Acute and Late Grade 3 toxicity occurred in 7% and 4% of patients. Acute Grade 3 toxicity was associated with poor performance status (HR 16.15). CONCLUSIONS In the largest series of glioma PT-ReRT reported to date, retreatment appears well tolerated with variable outcomes based on clinical prognostic factors. Toxicity rates were acceptable compared to historical photon-based literature despite a high median prescription dose.

Abstract Histologic features, presence of CDKN2A/B homozygous deletion and methylation subtype are strong determinants of outcome and of therapy in IDH-mutant gliomas. We were interested in learning if there are additional markers of outcome in these tumors. To address this question, we assembled a cohort of 963 IDH-mutant gliomas with overall survival data (median follow-up alive 2.7 years, median follow-up deceased 3.9 years). Array-based copy number data, targeted NGS, germline genotyping data and Illumina EPIC array methylation data were available on 872, 226, 542, and 401 patients, respectively. Morphologic type (oligodendroglioma versus astrocytoma, grade (2/3 vs 4) and methylation subtype (A_IDH_LG vs A_IDH_HG) were all significantly associated with survival (p <0.001). There was no significant difference in survival between grade 2 vs 3 IDH-mutant astrocytomas (p=0.53 adjusting for age and sex). However, subjects with the risk allele (G) for rs55705857 had a better overall survival than subjects with the non-risk allele (A) in IDH-mutant oligodendroglioma (AG/GG vs AA, median overall survival 21.6 vs 15.7 years, p=0.048 after adjusting for grade, age, and sex). Conversely, rs55705857 was associated with a markedly worse survival in grade 2 IDH-mutant astrocytomas (AG/GG vs AA, median overall survival 8.6 vs 19.6 years, p=0.007 after adjusting for age and sex). Despite similar sample sizes and number of deaths, there was no significant difference in overall survival by rs55705857 genotype in grade 3 or 4 IDH-mutant astrocytomas. Upon further functional analyses, TLX1 and GALNT17 were found to be differentially methylated in IDH1-mutant astrocytomas and oligodendrogliomas, respectively, when stratified by rs55705857 risk allele. This is the first observation of a germline characteristic (e.g. rs55705857) predicting survival in low-grade IDH-mutant astrocytoma. While this observation requires validation, it suggests that germline genotype may be practice changing and inform results of trials such as CATNON and CODEL.

Abstract Gliomas are heterogeneous brain tumors with prognostically-significant subtypes and few risk factors. IDH-wildtype glioblastoma, the most common subtype, carries a dismal prognosis. Using the largest GWAS dataset with histological (11,304 cases, 304,523 controls) and molecular (3,418 cases, 8,156 controls) subtypes, we analyzed the plasma and brain proteome to uncover proteins associated with glioma susceptibility. Using protein quantitative trait loci (pQTL) for 1,776 proteins in brain tissue, we identified 21 candidate proteins, including 9 associations with high probability (>70%) of colocalization (shared causal genetic variants for glioma risk and protein abundance). We confirmed known risk genes such as EGFR (p=1.9×10-35) and D2HGDH (p=1.1×10-5). We also identified novel risk proteins, including ENPP6, a choline phosphodiesterase overexpressed in glioma, for IDH-wildtype glioblastoma (OR=0.62, p=7.6×10-5), and galectin-3, a lectin encoded by a tumor fitness gene in CRISPR screens of glioma proliferation and a clinical drug target, for glioma overall (OR=1.37, p=1.3×10-5). Analyses of the plasma proteome using pQTLs for 1,362 proteins from 3 cohorts (N=88,838) identified 9 colocalized associations in whole blood. Most risk signals were subtype-specific, such as CRELD1 (p=2.5×10-5) for triple-negative glioblastoma. We found three candidate risk proteins for IDH-mutant 1p19q-intact glioma: immunoglobulin glycoprotein BCAM (p=9.6×10-8), neurotrophin receptor SorCS2 (p=3.6×10-5) and immune checkpoint PD-1 (p=1.1×10-5). Interestingly, genetically-predicted PD-1 levels had a larger effect on IDH-mutant 1p19q-intact (OR=2.75, 95% CI=1.61-4.69) than IDH-wildtype (OR=0.73, 95% CI=0.51-1.05) tumors, suggesting germline differences in immune checkpoint mechanisms among subtypes. For all colocalized candidates, genetically-predicted protein abundance was correlated with cis-regulated transcriptional activity in brain tissue. For example, genetically-predicted SORCS2 gene expression in brain tissue was associated with plasma SorCS2 levels (Z=16.1, p=1.1×10-68). Our analysis identified candidate proteins involved in immune response and neuronal proliferation, which may enable prioritization of drug targets and provide insight into disease mechanisms for glioma.

Abstract BACKGROUND Glioma radiotherapy planning requires accurate tumor delineation. While T1- contrast-enhanced-MRI (T1-CE-MRI) is the standard, due to blood-brain-barrier breakdown dependencies, T1-CE-MRI fails to reflect the extent of glioma. Studies using amino acid PET tracers report glioma uptake up to 3cm-4cm beyond T1-CE. In this study, amino acid tracer 18F-fluoro-dihydroxyphenylalanine (18F-DOPA) uptake was correlated with histopathological features to determine tumor thresholds. METHODS Using registered 18F-DOPA-PET and T1-CE-MRI images in the Stealth Neuronavigation system targeting concordant and discordant regions, 181 stereotactic biopsy samples (newly-diagnosed=74; recurrent=107) were obtained from 59 enrolled astrocytoma patients across two prospective phase II clinical trials between 2010-2019. An experienced neuropathologist reviewed each sample with hematoxylin and eosin stain and assigned an alphanumeric score: mitotic activity (0=no tumor; 1=no mitosis; 2=few/scattered mitosis; 3=frequent mitosis) and cellular density (A=<25%; B=25%-50%; C=50%-75%; D=>75%). Samples assigned 1C-1D, 2B-2D, or 3A-3D were categorized as histopathological high-score (aggressive disease), remaining samples as low-score. Relative mean (rFDOPA_mean) tumor-to-background uptake ratios were computed for 5mm uniformly expanded volumes from each Stealth biopsy coordinate using the crescent and wedge normalization methods. Relative uptake was compared overall and separately within newly-diagnosed/recurrent disease subgroups. An optimal rFDOPA_mean threshold to delineate high- from low-score was determined using the maximal Youden index of ROC curves. RESULTS Overall, high-score samples (n=116) had higher median (IQR) rFDOPA_mean uptake than low-score samples (n=65): high-score rFDOPA:mean=1.70(1.16-2.26), low-score rFDOPA:mean=1.16(0.83-1.49), Kruskal-Wallis p<0.001. The uptake difference between high- vs. low-score samples was observed within newly-diagnosed and recurrent subgroups, but was only significant for newly-diagnosed (p<0.001). For newly-diagnosed, an rFDOPA:mean=1.49 cutoff between high- and low-score groups shows 69% accuracy, 63% sensitivity, 80% specificity (AUC=0.782). Using the wedge normalization method, rFDOPA_mean values were 0.2 higher than crescent method values. CONCLUSIONS This work presents histologically verified 18F-DOPA-PET thresholds for aggressive disease in newly-diagnosed astrocytoma patients. Separate thresholds will need to be determined for recurrent glioma patients.

Abstract BACKGROUND Glioblastoma (GBM), one of the deadliest primary tumors of the central nervous system, is characterized by a highly immunosuppressive tumor microenvironment (TME). Tumor-associated macrophages and microglia (TAMs) are a dominant population of immune cells in the GBM TME and substantially contribute to immunosuppression, tumor progression, and treatment resistance. Elucidating the molecular mechanisms underlying TAM behavior is crucial to the development of effective immuno-therapeutic strategies for treating GBM. The adaptor protein, Caspase Recruitment Domain-containing protein 9 (CARD9) is primarily expressed in myeloid cells and its activation triggers assembly of the CARD9-BCL10-MALT1 (CBM) complex, which then promotes activation of NF-κB and/or MAPK pathways. The aim of this study was to investigate the role of the CBM complex in the GBM TME and assess its potential as a therapeutic target. METHODS/RESULTS In silico analyses revealed that GBM tumors demonstrate increased CARD9 and MALT1 expression in comparison to non-tumor brain tissue, with CARD9 expressed only within the myeloid compartment. Using co-culture, scratch wound, and transwell assays, we found that GBM tumor cells induce macrophage M2 polarization and migration via a mechanism that is dependent on CARD9/MALT1 signaling within macrophages. scRNA-Seq and flow-cytometric analysis of orthotopic syngeneic immunocompetent GBM tumor models revealed that the GBM TME is dominated by macrophages. Disruption of MALT1 protease activity within the TME leads to reduced tumor infiltration by immunosuppressive TAMs, remodeling of TAMs toward an immunoreactive anti-tumor phenotype, and improved survival of GBM-bearing mice. Additionally, we found that tumor growth was abrogated when GBM-bearing mice were treated with either a MALT1-protease inhibitor or a CARD9 inhibitor. CONCLUSIONS Our study suggests that blockade of the CARD9-MALT1 signaling axis impairs GBM-induced macrophage recruitment and M2 polarization and inhibits tumor progression. These findings nominate the CARD9-MALT1 signaling axis as a new target for TAM-directed immunotherapy for the treatment of GBM.

Abstract Aims Aortic stenosis (AS) is a common and progressive disease, which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild AS. Methods and results A comprehensive database including 9611 patients with serial transthoracic echocardiograms was collected from a single institution across three clinical sites. The data set included parameters from echocardiograms, electrocardiograms, laboratory values, and diagnosis codes. Data from a single clinical site were preserved as an independent test group. Machine learning models were trained to identify progression to severe stenosis and all-cause mortality and tested in their performance for endpoints at 2 and 5 years. In the independent test group, the AS progression model differentiated those with progression to severe AS within 2 and 5 years with an area under the curve (AUC) of 0.86 for both. The feature of greatest importance was aortic valve mean gradient, followed by other valve haemodynamic measurements including valve area and dimensionless index. The mortality model identified those with mortality within 2 and 5 years with an AUC of 0.84 and 0.87, respectively. Smaller reduced-input validation models had similarly robust findings. Conclusion Machine learning models can be used in patients with mild AS to identify those at high risk of disease progression and mortality. Implementation of such models may facilitate real-time, patient-specific follow-up recommendations.

AbstractPediatric obesity, characterized by a body mass index (BMI) at or above the 95th percentile for age, affects a substantial number of children and adolescents worldwide. Metabolic dysfunction‐associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease, represents a prominent hepatic manifestation of obesity and metabolic syndrome, emerging as the most prevalent hepatic disorder among pediatric patients and a significant contributor to liver transplantation in adults. The escalating prevalence of pediatric MASLD mirrors the alarming rise in childhood obesity rates over recent decades. While lifestyle modifications focusing on dietary changes and increased physical activity constitute the cornerstone of MASLD management, achieving and maintaining significant weight reduction remains challenging. Moreover, disease progression often persists despite standard‐of‐care interventions, warranting exploration into alternative therapeutic strategies. Pharmacological interventions, particularly, glucagon‐like peptide‐1 receptor agonists (GLP‐1RA), have shown promise in addressing pediatric obesity and its associated comorbidities, including MASLD. Recent studies have demonstrated the efficacy of GLP‐1RA in inducing weight loss and improving liver enzyme levels, suggesting a potential role in halting disease progression, and reducing the risk of major adverse liver outcomes. This review provides a comprehensive overview of the current pharmacotherapy landscape for pediatric MASLD, with a focus on novel agents such as GLP‐1RA. Furthermore, the manuscript proposes a practical algorithm to assist in integrating GLP‐1RA into the clinical management of pediatric patients with obesity and MASLD. Despite promising results, further research is warranted to elucidate the long‐term efficacy and safety of GLP‐1RA in pediatric populations.