Zadeh, Gelareh

Abstract Background Glioblastoma (GB) exhibits marked tumor microenvironmental heterogeneity, contributing to both therapy resistance and poor survival outcomes. Intercellular adhesion molecule 1 (ICAM1) is an inflammation-associated adhesion molecule implicated in immune-stromal interactions, but its clinical and biological significance in GB remains incompletely defined. Methods We performed ICAM1 immunohistochemistry, bulk RNA sequencing, DNA methylation analysis, single-nucleus RNA sequencing, and preoperative MRI-derived morphologic feature analysis across multi-institutional cohorts of treatment-naïve IDH-wildtype GB. Results High ICAM1 expression at both transcript and protein levels is associated with shorter overall survival, particularly within the mesenchymal transcriptional subtype. ICAM1 expression is inversely associated with promoter methylation. Single-nucleus RNA-sequencing analysis shows that ICAM1-high tumors are enriched for mesenchymal, hypoxia, stress-associated, and immunosuppressive myeloid programs, suggesting that ICAM1 reflects a multicompartment inflammatory tumor ecosystem. ICAM1 expression, tumor surface irregularity, and patient age are independently prognostic and minimally correlated, capturing complementary clinical, imaging, and molecular features of GB biology. When combined, our Clinical-Imaging-Molecular (CIM) framework refines outcome prediction across independent GB cohorts using routinely available clinical data, conventional imaging, and standard immunohistochemistry. Conclusions ICAM1 characterizes an immune-remodeled, stress-adapted GB ecosystem associated with poor clinical outcomes. Integrating patient age, surface irregularity, and ICAM1 expression yields a scalable and clinically accessible prognostic framework for GB, supporting tailored outcome prediction, particularly in low- and middle-resource settings without routine access to advanced molecular profiling.

Abstract Background Glioblastoma (GBM) is the most common malignant primary brain tumor and is associated with a poor prognosis. Repurposed posaconazole (PCZ) has demonstrated efficacy in vitro by targeting key metabolic pathways. The aim of this study was to determine the neuropharmacological profile of PCZ in patients with GBM through a Phase 0 first-in-human trial for this indication (NCT04825275). Methods We conducted an open-label, non-randomized, parallel-arm trial in participants with primary or recurrent GBM. Patients in the treatment arm received oral PCZ for 7-10 days presurgically to achieve steady-state concentrations. Microdialysis catheters were implanted to measure interstitial drug levels. Postoperative tissue and fluid samples were analyzed to evaluate PCZ pharmacokinetics (mass spectrometry) and pharmacodynamics, including vascular density, apoptosis, and metabolite concentrations (lactate and pyruvate) compared to controls. Results The trial was closed early due to slow accrual, enrolling 2 participants in the PCZ arm and three in the control arm. No drug-related safety issues were observed. Although PCZ was undetectable in microdialysate fluid, it accumulated in tumor tissue, with concentrations showing an association with CD31-measured endothelial content. PCZ-treated tumors exhibited trends toward lower BCL2 expression indicative of increased apoptosis, and significantly lower pyruvate levels in the tumor periphery compared to controls. Plasma lactate levels in treated patients normalized to control levels over 24 h. Conclusions Despite limited accrual, this trial provides the first clinical evidence that oral PCZ accumulates in human GBM tissue and shows preliminary signals of metabolic modulation. These findings provide biological rationale warranting further clinical investigation, potentially utilizing direct tissue sampling rather than microdialysis.

Abstract Background Meningiomas exhibit clinical heterogeneity. Radiotherapy (RT) remains the only adjuvant therapy, but tumor-control is variable, and biomarkers are limited. NRG/RTOG-0539 is the first prospective phase 2 trial to stratify meningioma patients for adjuvant RT based on clinical risk. Here, we apply modern molecular tools to this cohort and identify correlates of RT response. Methods Tumor tissue from 100 RTOG-0539 patients was profiled using DNA methylation arrays, RNA sequencing, and whole-exome sequencing. Recurrence scores, Molecular Groups, gene expression, and copy number alterations were compared across clinical groups and between RT responders and non-responders; non-response was defined as progression or death within 3 years. Results Modern grading criteria, including brain invasion, TERT mutation, CDKN2A/B deletion, and 1p/1q status, would reclassify 10% of tumors and alter treatment group assignment in 7%. Non-responders to RT exhibited more frequent 1p and 14q loss, and more copy number alterations. Transcriptomic and epigenetic profiling revealed immune-related signatures in responders and cell cycle–related pathways in non-responders, several of which overlapped with targets of vorinostat, a histone deacetylase inhibitor previously validated in aggressive meningioma models. The Proliferative Molecular Group was an independent predictor of post-RT recurrence in multivariable analysis, outperforming WHO grade. Conclusion Multi-omic analysis of the NRG/RTOG-0539 cohort shows that updated WHO grading criteria, incorporating molecular and cytogenetic features, improve risk stratification. However, molecular classification, particularly the Proliferative group, remains an independent and stronger predictor of RT response. These findings support integrating molecular biomarkers alongside modern grading frameworks to guide treatment and trial design in meningioma. Clinical Trial Information NCT00895622.

The classification and management of central nervous system (CNS) tumours have undergone substantial transformation over the past two decades, with the recognition of an expanding set of molecularly defined disease entities. Genome-wide DNA methylation profiling has emerged as an important complement to histopathology and targeted molecular testing, providing an epigenetic framework that captures tumour lineage, biological state and large-scale genomic alterations within a single assay. Accumulating evidence demonstrates that methylation-based approaches improve diagnostic precision, resolve biologically heterogeneous entities and support clinically meaningful risk stratification across a broad spectrum of CNS tumours. Methylation profiling has also increasingly been applied to outcome prediction, liquid biopsy-based analyses and the resolution of diagnostically challenging or misclassified cases. In addition, advances in multi-omic integration, computational inference from routinely acquired clinical data and evolving implementation frameworks are extending the clinical applicability of epigenetic profiling. This review synthesises the current state of DNA methylation profiling within the diagnostic and clinical framework of CNS tumours and considers how emerging technologies and practice models are shaping its ongoing integration into neuro-oncological care.

Abstract Background Approximately 12 000 adolescents and young adults (ages 15-39, AYAs) are diagnosed with a primary central nervous system (CNS) tumor each year. DNA methylation profiling has transformed CNS tumor classification by refining diagnostic accuracy and identifying biologically distinct subtypes, but its application has not been systematically evaluated in the AYA population. In this study, we examined the spectrum of CNS tumor types across age groups, with a focus on the AYA population. Methods We assembled a large dataset of CNS tumor samples with age annotations and methylation profiles matching with high confidence to a CNS tumor type using the NCI/Bethesda classifier. Prevalence of tumor type, methylation class and DNA copy number aberrations were compared across age strata (pediatric, AYA, and adult). Results The cohort of 21 712 CNS tumors included 5351 tumors from AYAs (25%), which showed a mixed pattern, with tumors typical of childhood (eg, medulloblastoma) as well as those common in older adults (eg, glioblastoma). Several tumor types were specifically enriched in the AYA, including IDH-mutant astrocytoma, pleomorphic xanthoastrocytoma, posterior fossa group B ependymoma, and diffuse hemispheric glioma, H3 G34-mutant, among others. Distinct methylation subclasses of multiple tumor types were observed in the AYA, and patterns of genomic aberrations showed age-specific distributions. Conclusion Large-scale methylation profiling revealed unique classification patterns of CNS tumors in AYAs, with specific tumor types, subclasses, and genomic alterations enriched in this population. These data may serve as a valuable reference resource for better understanding the spectrum of CNS tumors affecting AYA patients.