Faculty Bibliography

PURPOSE/OBJECTIVE:Non-invasive prognostic biomarkers to inform clinical decision-making are an urgent unmet need for the management of patients with glioblastoma (GBM). We previously showed that higher circulating cell-free DNA concentration [ccfDNA] is associated with worse survival in GBM. However, the biology underlying this is unknown. EXPERIMENTAL DESIGN/METHODS:We prospectively enrolled 129 patients with treatment-naïve GBM with blood drawn prior to initial resection (baseline) and at time of first post-radiotherapy MRI. We performed ccfDNA methylation deconvolution to determine cellular sources of ccfDNA. ELISA was performed to detect citrullinated H3 (citH3), a marker of neutrophil extracellular traps (NETs). Multiplex proteomic analysis was used to measure soluble inflammatory proteins. RESULTS:We found that neutrophils contributed the highest proportion of prognostic ccfDNA. The percentage of ccfDNA derived from neutrophils was correlated with total [ccfDNA], but only in patients receiving pre-operative corticosteroids. At baseline and on-therapy, [citH3] was significantly higher in the plasma of patients with GBM receiving corticosteroids compared to corticosteroid-naïve GBMs or no-cancer controls. Unsupervised hierarchical clustering of ccfDNA methylation patterns yielded two clusters, with one enriched for patients with the NETosis phenotype and who received corticosteroids. Unsupervised clustering of circulating inflammatory proteins yielded similar results. CONCLUSIONS:These data suggest neutrophil-mediated NETosis is the dominant source of prognostic ccfDNA in patients with GBM and may be associated with glucocorticoid exposure. If further studies show that pharmacological inhibition of NETosis can mitigate the deleterious effects of corticosteroids, these plasma markers will have important clinical utility as non-invasive correlative biomarkers.

BACKGROUND:Diffuse hemispheric glioma, histone 3 (H3) G34-mutant, has been newly defined in the 2021 WHO classification of central nervous system tumors. Here we sought to define the prognostic roles of clinical, neuroimaging, pathological, and molecular features of these tumors. METHODS:We retrospectively assembled a cohort of 114 patients (median age 22 years) with diffuse hemispheric glioma, H3 G34-mutant, CNS WHO grade 4 and profiled the imaging, histological and molecular landscape of their tumors. RESULTS:Compared with glioblastoma, H3 G34-mutant diffuse hemispheric gliomas exhibited less avid contrast enhancement, necrosis and edema on MRI. Comprehensive analyses of mutational and DNA copy number profiles revealed recurrent mutations in TP53 and ATRX, homozygous deletions of CDKN2A/B, and amplifications of PDGFRA, EGFR, CCND2, and MYCN. MGMT promoter methylation was detected in 79 tumors (75%); 11 tumors (13%) showed DNA copy number profiles suggestive of circumscribed deletions on 10q26.3 involving the MGMT locus. Median survival was 21.5 months. Female sex, gross total resection, and MGMT promoter methylation were positive prognostic factors on univariate analysis. Among radiological, pathological and molecular features, absence of pial invasion, and presence of microvascular proliferation and CDK6 amplification were positive prognostic factors on univariate analyses. CONCLUSIONS:This study refines the clinical and molecular landscape of H3 G34-mutant diffuse hemispheric gliomas. Dedicated trials for this novel tumor type are urgently needed.

Genome-wide DNA methylation signatures correlate with and distinguish central nervous system (CNS) tumor types. Since the publication of the initial CNS tumor DNA methylation classifier in 2018, this platform has been increasingly used as a diagnostic tool for CNS tumors, with multiple studies showing the value and utility of DNA methylation-based classification of CNS tumors. A Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) Working Group was therefore convened to describe the current state of the field and to provide advice based on lessons learned to date. Here, we provide recommendations for the use of DNA methylation-based classification in CNS tumor diagnostics, emphasizing the attributes and limitations of the modality. We emphasize that the methylation classifier is one diagnostic tool to be used alongside previously established diagnostic tools in a fully integrated fashion. In addition, we provide examples of the inclusion of DNA methylation data within the layered diagnostic reporting format endorsed by the World Health Organization (WHO) and the International Collaboration on Cancer Reporting. We emphasize the need for backward compatibility of future platforms to enable accumulated data to be compatible with new versions of the array. Finally, we outline the specific connections between methylation classes and CNS WHO tumor types to aid in the interpretation of classifier results. It is hoped that this update will assist the neuro-oncology community in the interpretation of DNA methylation classifier results to facilitate the accurate diagnosis of CNS tumors and thereby help guide patient management.

[This corrects the article DOI: 10.3389/fonc.2022.969812.].

BACKGROUND:Intracerebral schwannomas are rare tumors resembling their peripheral nerve sheath counterparts but localized in the CNS. They are not classified as a separate tumor type in the 2021 WHO classification. This study aimed to compile and characterize these rare neoplasms morphologically and molecularly. METHODS:We analyzed 20 tumor samples by histology, RNA Next-Generation Sequencing, DNA-methylation profiling, copy number analyses, and single nucleus RNA sequencing (snRNA-seq). Clinical data, including age, sex, and disease progression, were collected. MRI series were included when available. RESULTS:All cases with tissue available for histology review (n=13) were morphologically consistent with intracerebral schwannoma, but differed in their extent of GFAP staining. All (n=20) shared DNA-methylation profiles distinct from other CNS tumors, as well as from VGLL-altered peripheral nerve sheath tumors. Most cases (n=14/17) harbored fusions of either VGLL3 or VGLL1 (CHD7::VGLL3 (n=9/17) and EWSR1::VGLL1 (n=5/17)). In two cases the presence of a VGLL3 fusion was also confirmed by CNA analyses (n=2/17). MRI (n=4) showed well-defined, nodular tumors with strong, homogeneous enhancement and no diffusion restriction. Tumors were located throughout the neuroaxis [supratentorial (n=15), infratentorial (n=4), and spinal (n=1)]. snRNA-seq of a VGLL1-fused tumor indicated VGLL1 upregulation in 28.6% of tumor cells (n=1). During median follow-up of 1.8 years (range 3 months-9 years), none of the tumors recurred (n=10). CONCLUSIONS:We identify and define a new benign tumor class, designated VGLL-altered intraparenchymal CNS schwannomas. These tumors feature VGLL alterations and a specific DNA-methylation profile, with schwannoma-like histopathology and CNS localization, akin to previously classified intracerebral schwannomas.

BACKGROUND:Accurate intraoperative diagnosis is crucial for differentiating between primary CNS lymphoma (PCNSL) and other CNS entities, guiding surgical decision-making, but represents significant challenges due to overlapping histomorphological features, time constraints, and differing treatment strategies. We combined stimulated Raman histology (SRH) with deep learning to address this challenge. METHODS:We imaged unprocessed, label-free tissue samples intraoperatively using a portable Raman scattering microscope, generating virtual H&E-like images within less than three minutes. We developed a deep learning pipeline called RapidLymphoma based on a self-supervised learning strategy to (1) detect PCNSL, (2) differentiate from other CNS entities, and (3) test the diagnostic performance in a prospective international multicenter cohort and two additional independent test cohorts. We trained on 54,000 SRH patch images sourced from surgical resections and stereotactic-guided biopsies, including various CNS neoplastic/non-neoplastic lesions. Training and test data were collected from four tertiary international medical centers. The final histopathological diagnosis served as ground-truth. RESULTS:In the prospective test cohort of PCNSL and non-PCNSL entities (n=160), RapidLymphoma achieved an overall balanced accuracy of 97.81% ±0.91, non-inferior to frozen section analysis in detecting PCNSL (100% vs. 77.77%). The additional test cohorts (n=420, n=59) reached balanced accuracy rates of 95.44% ±0.74 and 95.57% ±2.47 in differentiating IDH-wildtype diffuse gliomas and various brain metastasis from PCNSL. Visual heatmaps revealed RapidLymphoma's capabilities to detect class-specific histomorphological key features. CONCLUSIONS:RapidLymphoma proves reliable and valid for intraoperative PCNSL detection and differentiation from other CNS entities. It provides visual feedback within three minutes, enabling fast clinical decision-making and subsequent treatment strategy planning.

Tumors of the major and minor salivary glands histologically encompass a diverse and partly overlapping spectrum of frequent diagnostically challenging neoplasms. Despite recent advances in molecular testing and the identification of tumor-specific mutations or gene fusions, there is an unmet need to identify additional diagnostic biomarkers for entities lacking specific alterations. In this study, we collected a comprehensive cohort of 363 cases encompassing 20 different salivary gland tumor entities and explored the potential of DNA methylation to classify these tumors. We were able to show that most entities show specific epigenetic signatures and present a machine learning algorithm that achieved a mean balanced accuracy of 0.991. Of note, we showed that cribriform adenocarcinoma is epigenetically distinct from classical polymorphous adenocarcinoma, which could support risk stratification of these tumors. Myoepithelioma and pleomorphic adenoma form a uniform epigenetic class, supporting the theory of a single entity with a broad but continuous morphologic spectrum. Furthermore, we identified a histomorphologically heterogeneous but epigenetically distinct class that could represent a novel tumor entity. In conclusion, our study provides a comprehensive resource of the DNA methylation landscape of salivary gland tumors. Our data provide novel insight into disputed entities and show the potential of DNA methylation to identify new tumor classes. Furthermore, in future, our machine learning classifier could support the histopathologic diagnosis of salivary gland tumors.

Sudden unexplained death in childhood (SUDC) is death of a child ≥ 12 months old that is unexplained after autopsy and detailed analyses. Among SUDC cases, ~ 30% have febrile seizure (FS) history, versus 2-5% in the general population. SUDC cases share features with sudden unexpected death in epilepsy (SUDEP) and sudden infant death syndrome (SIDS), in which brainstem autonomic dysfunction is implicated. To understand whether brainstem protein changes are associated with FS history in SUDC, we performed label-free quantitative mass spectrometry on microdissected midbrain dorsal raphe, medullary raphe, and the ventrolateral medulla (n = 8 SUDC-noFS, n = 11 SUDC-FS). Differential expression analysis between SUDC-FS and SUDC-noFS at p < 0.05 identified 178 altered proteins in dorsal raphe, 344 in medullary raphe, and 100 in the ventrolateral medulla. These proteins were most significantly associated with increased eukaryotic translation initiation (p = 3.09 × 10^-7, z = 1.00), eukaryotic translation elongation (p = 6.31 × 10^-49, z = 6.01), and coagulation system (p = 1.32 × 10^-5, z = 1.00). The medullary raphe had the strongest enrichment for altered signaling pathways, including with comparisons to three other brain regions previously analyzed (frontal cortex, hippocampal dentate gyrus, cornu ammonus). Immunofluorescent tissue analysis of serotonin receptors identified 2.1-fold increased 5HT2A in the medullary raphe of SUDC-FS (p = 0.025). Weighted gene correlation network analysis (WGCNA) of case history indicated that longer FS history duration significantly correlated with protein levels in the medullary raphe and ventrolateral medulla; the most significant gene ontology biological processes were decreased cellular respiration (p = 9.8 × 10^-5, corr = - 0.80) in medullary raphe and decreased synaptic vesicle cycle (p = 1.60 × 10^-7, corr = - 0.90) in the ventrolateral medulla. Overall, FS in SUDC was associated with more protein differences in the medullary raphe and was related with increased translation-related signaling pathways. Future studies should assess whether these changes result from FS or may in some way predispose to FS or SUDC.

BACKGROUND AND OBJECTIVES/OBJECTIVE:The management of World Health Organization (WHO) grade 2 meningiomas is complicated by their diverse clinical behaviors. Stereotactic radiosurgery (SRS) can be an effective management option. Literature on SRS dose selection is limited but suggests that a higher dose is better for tumor control. We characterize the predictors of post-SRS outcomes that can help guide planning and management. METHODS:We reviewed a cohort of consecutive patients with pathologically-proven WHO grade 2 meningiomas who underwent SRS at a single institution between 2011 and 2023. RESULTS:Ninety-nine patients (median age 62 years) underwent SRS, 11 of whom received hypofractionated SRS in 5 fractions. Twenty-two patients had received previous irradiation. The median follow-up was 49 months. The median overall survival was 119 months (95% CI 92-NA) with estimated 5- and 10-year survival of 83% and 27%, respectively. The median progression-free survival (PFS) was 40 months (95% CI 32-62), with 3- and 5-year rates at 54% and 35%, respectively. The median locomarginal PFS was 63 months (95% CI 51.8-NA) with 3- and 5-year rates at 65% and 52%. Nine (9%) patients experienced adverse events, 2 Common Terminology Criteria for Adverse Events grade 3 and 7 grade 2, consisting of worsening neurologic deficit from edema. In the single-session cohort, Ki-67 significantly predicted both overall survival and intracranial PFS. Tumors with Ki-67 >10% had 2.17 times the risk of locomarginal progression compared with Ki-67 ≤10% (P = .018) adjusting for covariates. Sex, prescription dose, tumor volume, and location also predicted tumor control. In tumors with Ki-67 >10%, margin dose ≥14 Gy was associated with significantly better tumor control but not for tumors with Ki-67 ≤10%. CONCLUSION/CONCLUSIONS:The management of WHO grade 2 meningiomas requires a multimodality approach. This study demonstrates the value of a targeted SRS approach in patients with limited disease and further establishes predictive biomarkers that can guide planning through a personalized approach.