Suppiah, Suganth

Abstract Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas arising from Schwann cells and characterized by marked cellular and molecular heterogeneity. Although bulk multi-omic studies have provided valuable insights into MPNST biology, recent advances in single-cell profiling have deepened our understanding of the tumor microenvironment and molecular mechanisms underlying malignant transformation. Single cell analyses have revealed distinct Schwann cell-like, malignant neural crest-like, immune, and stromal cellular subpopulations within MPNSTs and their precursor lesions. Comparative profiling of MPNSTs, neurofibromas, and atypical neurofibromatous neoplasms of uncertain biologic potential, suggest that MPNST progression involves Schwann cell dedifferentiation into a more primitive, stem-like state. In this review, we summarize key discoveries from single-cell characterization studies, and discuss how these findings illuminate MPNST tumorigenesis, cellular plasticity, and potential therapeutic vulnerabilities.

OBJECTIVE Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas predominantly associated with neurofibromatosis type 1 (NF1). However, their occurrence within NF type 2 (NF2)–related and SMARCB1-related schwannomatosis remains rare and poorly characterized. Accurate and timely diagnosis is challenging due to clinical and radiological similarities with benign schwannomas, potentially delaying appropriate management and impacting outcomes. This study presents an institutional case series aiming to better characterize the clinical presentations specifically for MPNSTs arising in patients with NF2- and SMARCB1-related schwannomatosis. METHODS This retrospective case series included patients diagnosed with schwannomatosis who subsequently developed histopathologically confirmed MPNSTs. Conducted at Mayo Clinic (Rochester, Minnesota) and University Health Network (Toronto, Canada), the study spanned January 1, 2003, to November 1, 2024. Patients were selected based on clinical or genetic diagnoses of schwannomatosis using International Consensus Group on Neurofibromatosis Diagnostic Criteria. Comprehensive clinical, radiological, and pathological data, including demographics, presenting symptoms, tumor features (size, location, immunohistochemistry, genetics), treatments (resection, chemotherapy, radiotherapy), and follow-up outcomes were extracted from electronic medical records. RESULTS The authors identified 8 patients with a mean age of 36 years, half of whom had NF2-related schwannomatosis. The most common presenting symptom was pain (71%). The mean tumor size was 8.2 ± 7.0 cm, with gross-total resection being the most common surgical treatment (67%), typically supplemented with radiation therapy (78%). More than half of the patients (56%) exhibited metastatic disease, and all tumors with reported grading were Fédération Nationale des Centres de Lutte Contre le Cancer grade 3. No tumors were associated with LZTR1 mutations. One notable case involved a 39-year-old male with SMARCB1-related schwannomatosis who had a femoral MPNST resected 13 years prior and subsequently developed a sciatic nerve MPNST that was managed successfully with neoadjuvant chemotherapy, radiation therapy, and negative margin resection. Of note, the second lesion arose from a hybrid neurofibroma/schwannoma. Another case, a 33-year-old male with SMARCB1-related schwannomatosis, had an incidental finding of epithelioid MPNST in a minimally symptomatic small palmar lesion. CONCLUSIONS This case series highlights that MPNSTs, although uncommon, can arise in NF2- and SMARCB1-related schwannomatosis without prior radiation exposure, presenting significant diagnostic challenges due to their similarity to benign schwannomas. The findings underscore the importance of maintaining clinical vigilance and employing individualized management strategies, balancing thorough resection with the preservation of function and patient quality of life.

OBJECTIVE Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas commonly associated with neurofibromatosis type 1 (NF1), whose occurrence in schwannomatosis remains poorly understood. This study aimed to characterize MPNSTs in NF type 2 (NF2)– and SMARCB1-related schwannomatosis through a systematic review and meta-analysis of survival outcomes. METHODS A comprehensive search of the PubMed, Embase, Scopus, SEER (Surveillance, Epidemiology, and End Results), and Web of Science databases was conducted from database inception through January 2024. Clinical, radiological, histopathological, and treatment data were extracted. Primary endpoints included overall survival (OS) and progression-free survival (PFS). Predictors of outcomes were analyzed using Kaplan-Meier survival curves and Cox proportional hazards models. RESULTS A total of 39 cases were identified. NF2-related disease accounted for 67% of cases, while 28% were SMARCB1 related. The mean age at MPNST diagnosis was 33 years (range 9–79 years). Pain (41%) and weakness (26%) were the most common presenting symptoms. The mortality rate was 72.9%. No tumors were associated with LZTR1 mutations. Tumor locations varied widely, with involvement of the pelvis, thigh, skull base, forearm/hand, and cranial nerves. Trends suggested improved survival in the absence of S100 loss, gross-total resection, and a known schwannoma precursor. Conversely, having an intracranial or intraspinal lesion or having NF2 in the setting of prior radiation therapy were found to be associated with decreased survival and increased progression. A risk stratification tool predicted OS (HR 28.0, p < 0.0001) and PFS (HR 12.1, p < 0.0001). CONCLUSIONS MPNSTs, although rare in schwannomatosis, can arise even in the absence of prior radiation exposure and may mimic benign schwannomas. A preliminary risk stratification tool may aid in identifying high-risk patients and optimizing treatment approaches, although validation is needed. Given the aggressive nature of MPNSTs and their potential for delayed diagnosis due to their rarity, vigilant monitoring and individualized treatment strategies are crucial. Future research should focus on refining risk prediction models and exploring targeted therapies for schwannomatosis-associated MPNSTs to improve patient outcomes.

Abstract INTRODUCTION Brain metastases (BM) are the most common intracranial tumor, with a poor prognosis of 10-16 months, and lung adenocarcinoma (LUAD) is the most common source. Currently, we cannot reliably predict which patients will develop BMs clinically, so most are detected after they develop and growing to cause deficits. Here, we use tumor DNA methylomes to predict which patients are likely to develop BM through the course of disease and we use both cerebrospinal fluid (CSF) and plasma methylomes for BM liquid biopsy, enabling their early detection and treatment. METHODS DNA methylomes were acquired from 419 tumor and plasma samples from 363 LUAD and BM patients. We built DNA methylation-based models that predict BM development and that also identify BMs non-invasively from CSF and plasma in discovery data subsets. A nomogram was built that predicts BM risk using methylation scores and clinical stage together. Models were evaluated in independent validation sets. RESULTS Our model predicting BM development was accurate (Univariable Cox: HR=5.7, 95% CI=1.9-17.2), p=0.0023), independent of clinical factors (Multivariable Cox: HR=8.9, 95% CI=2.0-40.5, p=0.0046), and more predictive than cancer staging used currently clinically (AUC=0.81 versus 0.65). Our combinatorial nomogram using methylation and staging data together showed enhanced BM prediction (Univariable Cox: HR=17.2, 95% CI=4.1-71.3, p&lt;0.0001; AUROC=0.82). Our models identifying BM through biofluid methylomes accurately distinguished BM from differential diagnoses of gliomas and lymphomas in plasma (AUROC=0.80, 95% CI=0.68-0.93) and with greater accuracy in CSF (AUROC=0.93, 95% CI=0.71-1.0). CONCLUSION Overall, we show the first approaches for robust molecular prediction of BM development and for reliable liquid biopsy of BM. This work is expected to transform cancer management by identifying high-risk lung cancer patients after initial treatment for inclusion in screening protocols using neuroimaging and liquid biopsy, to identify BM development early with less advanced disease and more optimal therapeutic outcomes.

2030 Background: Brain metastases (BM) are common and arise in 30% of lung adenocarcinoma (LUAD) patients. Patients with LUAD that develop BM have significantly poorer outcomes, with a 10-16 month median overall survival. Unfortunately, current clinical practice for BM prediction is limited and so BM are typically detected after they develop and grow to cause neurological symptoms. Once BM are detected, currently neurosurgical tumor biopsies are performed to enable BM diagnosis via neuropathological evaluation. The aims of this study were to develop DNA methylation-based models that predict LUAD BM and non-invasively detect BM in blood to enable early diagnosis and treatment. Methods: DNA methylomes were acquired from 402 tumor tissue and plasma samples in a cohort of 346 LUAD and BM patients. Machine learning models were built using DNA methylation signatures that stratify BM risk in tissue and detect BM in plasma. Models were evaluated in independent validation datasets. A predictive nomogram was developed using the BM prediction model together with clinical factors to provide composite patient-specific scores reflecting BM risk. Results: The methylation-based BM predictor accurately stratified BM risk in a univariable Cox model using validation set data (HR = 5.65, 95%CI 1.85–17.2, p = 0.0023). Model utility was independent of the predictive value of clinical factors in a multivariable Cox model using validation set data (Table 1: HR = 8.92, 95%CI 1.97–40.5, p = 0.0046). The 5-year model accuracy was 0.81 and significantly higher than a similarly built cancer stage-based model (0.65), demonstrating utility over current practice. The combinatorial clinical-methylomic predictive nomogram had enhanced utility with an accuracy of 0.82 univariable Cox HR of 17.2 (95%CI 4.13–71.3, p < 0.0001), demonstrating comprehensive patient-specificity. The plasma-based model accurately classified BM from gliomas and lymphomas (AUROC=0.80), as typical clinical differential diagnoses, in validation set data. The models were validated further in additional external data. Conclusions: DNA methylation-based modeling of BM can accurately predict LUAD patients at risk for BM development and can non-invasively detect BM that develop. Future treatment approaches may tailor initial LUAD treatment and ongoing cancer surveillance to a patient’s BM risk, allowing for the potential to prevent and treat BM early. DNA methylation-based BM prediction is independent of clinical factors in a multivariable Cox proportional hazards model. Variable HR 95% CI p Methylome risk score 8.92 1.97–40.5 0.005 Age Years 0.96 0.92–1.02 0.177 Smoking Pack-years 0.99 0.95–1.03 0.496 EGFR Mutant vs wildtype 0.92 0.25–3.34 0.895 T T2 vs T1 1.58 0.41–6.04 0.505 T3−4 vs T1 1.49 0.28–7.98 0.642 N N1 vs N0 1.05 0.31–3.58 0.943 N2−3 vs N0 1.00 0.27–3.69 0.995 M M1 vs M0 145 12.2–1730 <0.001

Abstract Background Malignant peripheral nerve sheath tumors (MPNSTs) can arise from atypical neurofibromas (ANF). Loss of the polycomb repressor complex 2 (PRC2) is a common event. Previous studies on PRC2-regulated genes in MPNST used genetic add-back experiments in highly aneuploid MPNST cell lines which may miss PRC2-regulated genes in NF1-mutant ANF-like precursor cells. A set of PRC2-regulated genes in human Schwann cells (SCs) has not been defined. We hypothesized that PRC2 loss has direct and indirect effects on gene expression resulting in MPNST, so we sought to identify PRC2-regulated genes in immortalized human Schwann cells (iHSCs). Methods We engineered NF1-deficient iHSCs with loss of function SUZ12 or EED mutations. RNA sequencing revealed 1327 differentially expressed genes to define PRC2-regulated genes. To investigate MPNST pathogenesis, we compared genes in iHSCs to consistent gene expression differences between ANF and MPNSTs. Chromatin immunoprecipitation sequencing was used to further define targets. Methylome and proteomic analyses were performed to further identify enriched pathways. Results We identified potential PRC2-regulated drivers of MPNST progression. Pathway analysis indicates many upregulated cancer-related pathways. We found transcriptional evidence for activated Notch and Sonic Hedgehog (SHH) signaling in PRC2-deficient iHSCs. Functional studies confirm that Notch signaling is active in MPNST cell lines, patient-derived xenografts, and transient cell models of PRC2 deficiency. A combination of MEK and γ-secretase inhibition shows synergy in MPNST cell lines. Conclusions We identified PRC2-regulated genes and potential drivers of MPNSTs. Our findings support the Notch pathway as a druggable target in MPNSTs. Our identification of PRC2-regulated genes and pathways could result in more novel therapeutic approaches.

AbstractBackgroundWith increasing molecular analyses of meningiomas, there is a need to harmonize language used to capture clinical data across centers to ensure that molecular alterations are appropriately linked to clinical variables of interest. Here the International Consortium on Meningiomas presents a set of core and supplemental meningioma-specific common data elements (CDEs) to facilitate comparative and pooled analyses.MethodsThe generation of CDEs followed the 4-phase process similar to other National Institute of Neurological Disorders and Stroke (NINDS) CDE projects: discovery, internal validation, external validation, and distribution.ResultsThe CDEs were organized into patient- and tumor-level modules. In total, 17 core CDEs (10 patient level and 7 tumor level) as well as 14 supplemental CDEs (7 patient level and 7 tumor level) were defined and described. These CDEs are now made publicly available for dissemination and adoption.ConclusionsCDEs provide a framework for discussion in the neuro-oncology community that will facilitate data-sharing for collaborative research projects and aid in developing a common language for comparative and pooled analyses. The meningioma-specific CDEs presented here are intended to be dynamic parameters that evolve with time and The Consortium welcomes international feedback for further refinement and implementation of these CDEs.

Abstract BACKGROUND With increasing studies reporting on the molecular profiling of meningiomas, there is a need to harmonize language used to capture clinical data across centers to ensure that molecular alterations are appropriately linked to clinical variables of interest. Here the International Consortium on Meningiomas presents a final set of core and supplemental meningioma-specific Common Data Elements (CDEs) to facilitate comparative and pooled analyses. METHODS The generation of CDEs followed the four-phase process similar to other National Institute of Neurological Disorders and Stroke (NINDS) CDE projects: development/discovery based on data from published and ongoing meningioma trials, internal validation, external validation including presentation of our data form at the Society for Neuro-Oncology previously, and distribution. RESULTS We developed a set of CDEs organized into patient- and tumor-level modules. In total, the Consortium identified 16 core CDEs (9 patient-level and 7-tumour-level) e.g. age at index surgery, diagnosis of neurofibromatosis, prior chemotherapy or radiation, tumor location, extent of resection, recurrence, etc. An additional 15 supplemental CDEs were defined and described (8 patient-level and 7 tumour-level) e.g. race, cause of death, multiple tumors, tumor size, Simpson grade, second intervention, etc. These CDES are now made publicly available for dissemination and adoption. We also present a narrative review and analysis of recent and ongoing meningioma trials. CONCLUSIONS These CDEs provide a framework for discussion in the neuro-oncology community that will facilitating data sharing for collaborative research projects and aid in developing a common language for comparative and pooled analyses. The CDEs are intended to be dynamic parameters that evolve with time and The Consortium welcomes international feedback for further refinement and implementation of these CDEs.

Abstract With increasing epidemiological and biological studies on meningiomas, standardized clinical data capture will be necessary to interpret results across studies and to translate them to clinical practice. To meet this need for consistent clinical data capture, the International Consortium on Meningioma, has developed a set of common data elements (CDEs), to be used across clinical and biological research. Building from terminology used in clinical practice and ongoing studies, we used a consensus-of-experts approach to arrive at a set of standardized and vetted data elements. Areas of focus include patient characteristics, patient history, radiological and intra-operative description, histological diagnosis and molecular testing, non-surgical interventions, and surveillance. These data elements are implemented in Research Electronic Data Capture (REDCap) forms. With REDCap implementation, components of the CDE set can be selected and instituted in a local REDCap instance for efficient study start-up. The scope of the current CDE set focuses on surgically treated meningioma. However, modular forms provide flexibility and to allow the scope to be expanded to include non-surgically treated meningioma. Dissemination plans are underway to introduce the CDEs to neuro-oncology researchers and clinicians through publication and presentations, where feedback will be solicited. Adoption of CDEs for research will improve consistency and interpretability across studies, expediting research in this frequently occurring tumor.