Faculty Bibliography

BACKGROUND AND PURPOSE/OBJECTIVE:-wt GBMs to help radiologists in differentiating them from nonmalignant mimic diagnoses (eg, encephalitis). Additionally, the histologic, genomic, and survival profiles of nonenhancing GBMs were compared with those of enhancing GBMs. MATERIALS AND METHODS/METHODS:-wt GBMs with nonmalignant mimics. Histopathologic and genomic analyses were performed on institutional cases. Overall survival between nonenhancing and enhancing GBMs was compared using Kaplan-Meier analysis. RESULTS:= .078). CONCLUSIONS:Nonenhancing GBMs demonstrate distinct MRI features that must be recognized for early diagnosis and differentiation from nonmalignant mimics. Nonenhancing GBMs demonstrated longer overall survival compared with enhancing GBMs, though they were not statistically significant.

BACKGROUND:Glioblastoma intramedullary spinal cord metastasis (GISCM) is a rare sequela of high-grade astrocytoma and glioblastoma multiforme (GBM). Discrete intramedullary spinal cord metastases are less common than spinal leptomeningeal spread and may follow a more indolent course. Once identified as GISCM, palliative maximal safe resection of the tumor may be considered to alleviate neurological symptoms. Reports describing the surgical management of these rare lesions, including the use of emerging technologies that may aid in maximal safe resection, are sparse. A further understanding is also required regarding the course of disease and factors contributing to mortality in GISCM. METHODS:We reviewed the intraoperative management and clinical course of three patients treated for GISCM at our institution between 2015 and 2024. We additionally conducted a PRISMA-guided systematic literature review of PubMed Central, MEDLINE, and Bookshelf databases through May 26th, 2025, including original patient reports of GISCM from cranial astrocytoma or GBM. The disease course, management strategies, and causes of mortality in previously reported cases were analyzed. RESULTS:Our institutional cohort had a mean time to spinal metastasis of 26.2 months from diagnosis of cranial disease (range 17.5-40.5 months), with a mean survival of 9.2 months following maximal safe resection of extramedullary components (range 7-12 months). In two cases, intraoperative Stimulated Raman Histology (SRH) was employed to facilitate the rapid identification of metastatic GBM, thereby influencing surgical strategy. In one case, 5-aminolevulinic acid (5-ALA) was used to differentiate between tumor and spinal cord parenchyma, facilitating maximal safe debulking without neurological injury. Literature review identified 38 prior reported cases of GISCM, with a median time to spinal diagnosis of 11.0 months and a median survival of 3.5 months thereafter. The cause of death in the review cohort often involved multiple factors, and when analyzed for contributing factors to death, 38.7% involved cranial progression, 38.7% involved progression of spinal disease, and 29.0% involved medical complications. Gait ataxia at presentation was associated with shorter survival in review patients, potentially reflecting advanced disease with extramedullary cord compression. CONCLUSION/CONCLUSIONS:GISCM represents an entity distinct from leptomeningeal disease and may be managed in conjunction with recurrent cranial disease. Surgical debulking is a technically feasible strategy that can be safely facilitated using tools employed in the management of intracranial GBM, facilitating maximal safe resection without compromising survival.

BACKGROUND:Astroblastomas are rare brain tumors predominantly affecting children and young adults, for which molecular subtypes and clinical management remain undefined. METHODS:We analyzed tumor samples, molecular profiles, and clinical data from 200 patients, classified as "Astroblastoma, MN1-altered" under WHO criteria, using DNA methylation profiling, DNA/RNA profiling/sequencing, and survival analyses. RESULTS:DNA methylation analyses identified 3 groups: Group A (n = 143, characterized by MN1::BEND2 fusions, predominantly supratentorial location, with striking female predominance and favorable survival); Group B (n = 37, epigenetically and transcriptionally closely related to Group A, but characterized by EWSR1::BEND2 fusions, with spinal and infratentorial locations and poor prognosis); and Group C (n = 20, epigenetically and transcriptionally distinct, characterized by MN1::CXXC5 fusions, exclusively supratentorially located, with favorable survival). Progression-free and overall survival were significantly shorter in Group B (5-year PFS 14%; 10-year OS 54%) compared to A (5-year PFS 47%; 10-year OS 89%) and C (5-year PFS 75%; 10-year OS 89%). Radiotherapy improved PFS in Group B (hazard ratio 0.25), while no clear benefit was identified for Groups A and C. CONCLUSIONS:Astroblastoma, MN1-altered, comprises 3 molecularly and clinically distinct groups, characterized by different fusion genes, including those without MN1. These new insights, including the identification of potential predictive biomarkers like 14q/16q loss, provide a framework for the development of risk-stratified therapeutic approaches. Importantly, we identified a molecularly defined high-risk group that benefits from radiation therapy. Our findings redefine Astroblastoma as a molecularly diverse tumor type, propose a refined classification, support the development of risk-adapted therapeutic strategies and provide a rational standard of care.

BACKGROUND:IDH-mutant astrocytomas are classified as WHO grade 4 in the presence of conventional high-grade histologic features and/or homozygous CDKN2A/B deletion in the 5th edition of the WHO Classification of Central Nervous System Tumour guidelines. However, work over the past decade has indicated a number of other molecular alterations that warrant consideration as potential prognostic markers. METHODS:We used univariate Kaplan-Meier and multivariate Cox proportional hazards regression analysis to evaluate the prognostic effects of homozygous CDKN2A/B deletion, CDK4 amplification, CCND2 amplification, PDGFRA amplification/mutation, PIK3R1 mutation, PIK3CA mutation, MYCN amplification, EGFR amplification/mutation, TERT promoter mutation, and grade 4 histologic features in two independent cohorts of WHO grade 2-4 IDH-mutant astrocytoma (n = 840 and n = 367). RESULTS:The presence of CDK4 amplification, CCND2 amplification, PDGFRA alteration, PIK3R1 mutation, MYCN amplification, and EGFR alteration were each associated with reduced overall survival compared to WHO grade 2/3 astrocytomas without these molecular features. 17.7% (148/837) of otherwise grade 2/3 astrocytomas had one or more of these molecular criteria, with resulting intermediate clinical outcome in terms of overall survival (median survival of 67.3-82.0 months) compared to grade 2/3 astrocytomas without these molecular features (median survival of 135.0-140.7 months) and grade 4 astrocytomas (median survival of 35.3-45.0 months). CONCLUSIONS:The presence of CDK4, CCND2, PDGFRA, PIK3R1, MYCN, and EGFR alterations result in an intermediate patient survival in IDH-mutant astrocytoma. Adding these molecular alterations should be considered in future diagnostic classification systems to improve stratification of high-risk patients.

Spinal tumor surgery requires rapid tissue diagnosis to guide surgical decisions and further treatment strategies, yet current intraoperative methods are time-intensive and require specialized expertise. No AI systems exist for real-time spinal tumor classification during surgery. We developed SpineXtract, the first AI-powered system for rapid intraoperative spinal tumor diagnosis using stimulated Raman histology (SRH) - a label-free Raman spectromics imaging technique without tissue processing available during surgery. We created a transformer-based classifier optimized for spinal tissue characteristics to identify common tumor types: meningioma, schwannoma, ependymoma, and metastasis. The system was tested in an international, multicenter, simulated, single-arm study using existing SRH datasets (44 patients, 142 slide-images) from three international institutions, with final pathological diagnosis as reference standard. SpineXtract achieved a 92.9% macro-average balanced accuracy (95% CI: 85.5-98.2) within 5 minutes (tumor-specific accuracy range, 84.2-98.6%), while providing quantitative microscopic feedback for granular tissue analysis. Performance remained consistent across institutions (macro balanced accuracy 91.4-92.0%) and outperformed existing brain tumor classifiers by 15.6%. Our results demonstrate clinical applicability, enabling rapid intraoperative diagnosis with performance exceeding current methods, potentially transforming intraoperative diagnostic workflows in spinal tumor surgery.

BACKGROUND:While immune checkpoint inhibitors (ICI) induce potent responses against several systemic malignancies, clinical efficacy against high-grade glioma has been limited by immunosuppression, low mutational burden and limited lymphocyte infiltration into tumors. Laser interstitial thermal therapy (LITT) induces coagulative necrosis and disrupts the peritumoral blood-brain barrier (BBB), creating a potentially antigenic milieu. We hypothesized that neoadjuvant and adjuvant ICI would synergize with LITT to potentiate antitumor immune responses and enhance survival. METHODS:This retrospective study is an exploratory case series that includes 9 adult patients with recurrent IDH wild-type glioblastoma (GBM, n = 6), IDH mutant high-grade astrocytoma (n = 2) and H3K27M mutant diffuse midline glioma (n = 1). All patients received neoadjuvant anti-PD1 ICI prior to LITT and most received adjuvant ICI (8/9). Disease burden was followed through radiographic volume segmentation of gadolinium-enhancing disease. Patients were followed for progression-free (PFS) and overall survival (OS). RESULTS:). There were no perioperative complications. All patients showed an initial increase in gadolinium-enhancing volume after LITT. Seven of 9 (78 %) patients demonstrated subsequent regression in total gadolinium-enhancing volume. Three non-contiguous satellite lesions naïve to laser ablation exhibited complete or near-complete regression in 2 patients. Median PFS was 5.90 months (range 1.00-41.23), and median OS was 9.97 months (range 1.20-41.23). CONCLUSIONS:Combination therapy with neoadjuvant and adjuvant pembrolizumab and LITT is feasible and safe in recurrent high-grade glioma. Responses may be more robust in certain molecular subtypes of glioma. Further studies are needed to investigate this potential synergy.

Standard techniques for detecting genomic rearrangements in formalin-fixed paraffin-embedded (FFPE) biopsies have important limitations. We performed FFPE-compatible Hi-C on 44 clinical biopsies comprising large B cell lymphomas (n = 18), plasma cell neoplasms (n = 14), and other diverse lymphoid cancers, identifying consistent topological differences between malignant B cell and plasma cell states. Hi-C detected expected oncogene rearrangements at high concordance with fluorescence in situ hybridization (FISH) and supported enhancer hijacking in recurrent rearrangements of BCL2, CCND1, and MYC plus unanticipated variants involving homologous loci. Hi-C identified unanticipated non-coding rearrangements involving PD-1 ligand genes and other loci of potential therapeutic relevance, distinguished between functionally divergent classes of BCL6 rearrangements, and provided topological information supporting interpretation of variant MYC rearrangements. Hi-C revealed disease-selective MYC locus topological features that correlated with disease-selective MYC locus enhancers and rearrangement breakpoint distributions. FFPE-compatible Hi-C detects oncogene rearrangements and their topological consequences at genome-wide scale, finding clinically relevant drivers missed by standard approaches.

BACKGROUND:Meningiomas are the most common adult brain tumors. While homozygous deletions of CDKN2A/B are linked to early recurrence and hence serve as CNS WHO grade 3 criterion, the clinical impact of hemizygous deletions remains unclear-especially since distinguishing between hemi- and homozygous losses can be technically challenging. METHODS:DNA methylation data, copy-number and mutation data were evaluated on a multicenter cohort of 970 meningiomas. Each sample's CDKN2A/B status was manually classified by visual inspection in relation to whole chromosomal losses and gains in the copy number profile generated from global methylation array in relation to other copy number events. Progression probabilities were determined using the Kaplan-Meier method. RESULTS:Among 970 meningiomas, n = 30 had homozygous, n = 114 hemizygous (n = 31 segmental; n = 83 focal) and n = 826 CDKN2A/B balanced status. In cases with hemizygous deletions in general, an association with increased progression risk compared to balanced cases was observed, although this did not reach statistical significance (log-rank p = 0.074; HR 1.36, 95% CI [0.97, 1.90]; p = 0.07). However, segmental hemizygous losses were linked to a significantly worse prognosis (log-rank p = 0.0023), but focal hemizygous deletions were not (log-rank p = 0.523). Segmental hemizygous CDKN2A/B deletions were more frequently associated with a higher amount of high-risk copy number variations (CNVs) than focal losses. CONCLUSION/CONCLUSIONS:Our findings suggest that hemizygous CDKN2A/B deletions overall do not confer worse risks for progression in meningiomas. The signal for segmental deletions may not be locus-specific but just one representation of the generally instable genome of aggressive meningiomas.

DNA methylation-based classification is now central to contemporary neuro-oncology, as highlighted by the World Health Organization (WHO) classification of central nervous system (CNS) tumors. We present the Heidelberg CNS Tumor Methylation Classifier version 12.8 (v12.8), trained on 7,495 methylation profiles, which expands recognized entities from 91 classes in version 11 (v11) to 184 subclasses. This expansion is a result of newly identified tumor types discovered through our large online repository and global collaborations, underscoring CNS tumor heterogeneity. The random forest-based classifier achieves 95% subclass-level accuracy, with its well-calibrated probabilistic scores providing a reliable measure of confidence for each classification. Its hierarchical output structure enables interpretation across subclass, class, family, and superfamily levels, thereby supporting clinical decisions at multiple granularities. Comparative analyses demonstrate that v12.8 surpasses previous versions and conventional WHO-based approaches. These advances highlight the improved precision and practical utility of the updated classifier in personalized neuro-oncology.

The detection and identification of intracranial tumours is limited by the lack of accurate biomarkers and requires invasive biopsy procedures. We investigated a machine perception liquid biopsy approach to detect and identify intracranial tumours from peripheral blood and to discover biomarkers responsible for the predictions. Quantum well defect-modified single-walled carbon nanotubes stabilized with single-stranded DNA, interrogating 739 plasma samples from brain tumour patients, were used to train and validate machine-learning models to detect intracranial tumours with 98% accuracy and identify tumour type. The protein corona of the top model-contributing nanosensor was interrogated using quantitative proteomics, resulting in the identification of tumour ecosystem-secreted factors, both previously reported and newly discovered, originating from intracranial tumour cells, the tumour microenvironment and the innate immune system of patients with glioblastoma and meningioma. Newly discovered factors elicited linear nanosensor responses and were elevated in one or both tumour types, matching the original protein corona enrichment. This investigation reveals that a perception-based detection of disease in blood can identify biomarkers responsible for the signal and also amplify cancer detection signals by detecting factors beyond tumour cells, thereby recruiting the entire tumour ecosystem for cancer diagnosis.