Association of frequent NF2 mutations with spinal location predominance and worse outcomes in psammomatous meningiomas.

OBJECTIVE: Psammomatous meningiomas (PMs) are a rare histological subtype of meningioma but are rather frequent in spinal meningiomas. The authors aimed to analyze the incidence, clinical features, molecular alterations, long-term outcomes, and prognostic factors of PMs. METHODS: In total, 151 patients with PMs were included in this study. Clinical characteristics, molecular alterations, and progression-free survival (PFS) were analyzed in PMs. Clinical characteristics were compared between PMs and other WHO grade 1 meningiomas. Targeted sequencing of meningioma-relevant genes was performed to determine the molecular alterations in PMs. RESULTS: PMs accounted for 1.34% of all meningiomas. Clinically, spinal location (p < 0.001) and female predominance (p < 0.001) were statistically significant in PMs when compared with the other grade 1 subtypes. Radiologically, calcification was frequently found in PMs (88.24%). Genetically, NF2 was the most frequently mutated gene in PMs (59.7%), followed by TRAF7 and AKT1. Ten patients experienced recurrence during the long-term follow-up. Multivariate analysis demonstrated that age (p = 0.009), extent of resection (p < 0.001), Ki-67 index (p = 0.007), and NF2 status (p < 0.001) were independent prognostic factors in the cohort of PMs. Interestingly, NF2 mutation was detected in all (48/48) spinal PMs (SPMs) but in only 38.46% (35/91) of cranial PMs (CPMs), revealing a significant difference (p < 0.001). The mean Ki-67 index (p = 0.044) and proportion of PMs with PR-positive expression (p = 0.048) were significantly higher in SPMs than in CPMs. The frequent NF2 mutations are associated with spinal location predominance and worse PFS in PMs. CONCLUSIONS: Female sex and spinal location predominance were statistically significant in PMs. NF2 mutation was an independent predictor for worse PFS of PMs. Of note, NF2 mutation was detected in all SPMs but in only 38.46% of CPMs, revealing a significant difference.

Genetic characterization and mutational profiling of foramen magnum meningiomas: a multi-institutional study.

OBJECTIVE: Foramen magnum (FM) meningiomas pose significant surgical challenges and have high morbidity and mortality rates. This study aimed to investigate the distribution of clinically actionable mutations in FM meningiomas and identify clinical characteristics associated with specific mutational profiles. METHODS: The authors conducted targeted next-generation sequencing of 62 FM meningiomas from three international institutions, covering all relevant meningioma genes (AKT1, KLF4, NF2, POLR2A, PIK3CA, SMO, TERT promoter, and TRAF7). Patients with a radiation-induced meningioma or neurofibromatosis type 2 (NF2) were excluded from the study. Additionally, patient and tumor characteristics, including age, sex, radiological features, and tumor location, were retrospectively collected and evaluated. RESULTS: The study cohort consisted of 46 female and 16 male patients. Clinically significant driver mutations were detected in 58 patients (93.5%). The most commonly observed alteration was TRAF7 mutations (26, 41.9%), followed by AKT1E17K mutations (19, 30.6%). Both mutations were significantly associated with an anterolateral tumor location relative to the brainstem (p = 0.0078). NF2 mutations were present in 11 cases (17.7%) and were associated with posterior tumor location, in contrast to tumors with TRAF7 and AKT1E17K mutations. Other common mutations in FM meningiomas included POLR2A mutations (8, 12.9%; 6 POLR2AQ403K and 2 POLR2AH439_L440del), KLF4K409Q mutations (7, 11.3%), and PIK3CA mutations (4, 6.5%; 2 PIK3CAH1047R and 2 PIK3CAE545K). POLR2A and KLF4 mutations exclusively occurred in female patients and showed no significant association with specific tumor locations. All tumors harboring AKT1E17K and POLR2A mutations displayed meningothelial histology. Ten tumors exhibited intratumoral calcification, which was significantly more frequent in NF2-mutant compared with AKT1-mutant FM meningiomas (p = 0.047). CONCLUSIONS: These findings provide important insights into the molecular genetics and clinicopathological characteristics of FM meningiomas. The identification of specific genetic alterations associated with tumor location, volume, calcification, histology, and sex at diagnosis may have implications for personalized treatment strategies in the future.

The development of a combined clinico-radiomics model for predicting post-operative recurrence in atypical meningiomas: a multicenter study.

PURPOSE: Atypical meningiomas could manifest early recurrence after surgery and even adjuvant radiotherapy. We aimed to construct a clinico-radiomics model to predict post-operative recurrence of atypical meningiomas based on clinicopathological and radiomics features. MATERIALS AND METHODS: The study cohort was comprised of 224 patients from two neurosurgical centers. 164 patients from center I were divided to the training cohort for model development and the testing cohort for internal validation. 60 patients from center II were used for external validation. Clinicopathological characteristics, radiological semantic, and radiomics features were collected. A radiomic signature was comprised of four radiomics features. A clinico-radiomics model combining the radiomics signature and clinical characteristics was constructed to predict the recurrence of atypical meningiomas. RESULTS: 1920 radiomics features were extracted from the T1 Contrast and T2-FLAIR sequences of patients in center I. The radiomics signature was able to differentiate post-operative patients into low-risk and high-risk groups based on tumor recurrence (P < 0.001). A clinic-radiomics model was established by combining age, extent of resection, Ki-67 index, surgical history and the radiomics signature for recurrence prediction in atypical meningiomas. The model achieved a good prediction performance with the integrated AUC of 0.858 (0.802-0.915), 0.781 (0.649-0.912) and 0.840 (0.747-0.933) in the training, internal validation and external validation cohort, respectively. CONCLUSIONS: The present study established a radiomics signature and a clinico-radiomics model with a favorable performance in predicting tumor recurrence for atypical meningiomas.

CBX7 reprograms metabolic flux to protect against meningioma progression by modulating the USP44/c-MYC/LDHA axis.

Meningioma is one of the most common primary neoplasms in the central nervous system, whereas there is still no specific molecularly targeted therapy that has been approved for the clinical treatment of aggressive meningiomas. There is therefore an urgent demand to decrypt the biological and molecular landscape of malignant meningioma. Here, through the in-silica prescreening and 10-year follow-up of 445 meningioma patients, we uncovered that CBX7 is progressively decreased with malignancy grade and neoplasia stage in meningioma and a high CBX7 expression level predicts a favorable prognosis in meningioma patients. CBX7 restoration significantly induces cell cycle arrest and inhibits meningioma cell proliferation. iTRAQ-based proteomics analysis indicated that CBX7 restoration triggers the metabolic shift from glycolysis to oxidative phosphorylation. The mechanistic study demonstrated that CBX7 promotes the proteasome-dependent degradation of c-MYC proteins by transcriptionally inhibiting the expression of a c-MYC deubiquitinase, USP44, which attenuates c-MYC-mediated transactivation of LDHA transcripts and further inhibits glycolysis and subsequent cellular proliferation. More importantly, the functional role of CBX7 was further confirmed in both subcutaneous and orthotopic meningioma xenografts mouse models and human meningioma patients. Together, our results shed light on the critical role of CBX7 during meningioma malignancy progression and identified the CBX7/USP44/c-MYC/LDHA axis as a promising therapeutic target against meningioma progression.

Predicting meningioma grades and pathologic marker expression via deep learning.

OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma. METHODS: A total of 1192 meningioma patients from two centers who underwent surgical resection between September 2018 and December 2021 were retrospectively included. The pathological data and post-contrast T1-weight images for each patient were collected. The patients from institute I were subdivided into training, validation, and testing sets, while the patients from institute II served as the external testing cohort. The fine-tuned ResNet50 model based on transfer learning was adopted to classify WHO grade in the whole cohort and predict Ki-67 index, H3K27me3, and progesterone receptor (PR) status of grade 1 meningiomas. The predictive performance was evaluated by the accuracy and loss curve, confusion matrix, receiver operating characteristic curve (ROC), and area under curve (AUC). RESULTS: The DL prediction model for each label achieved high predictive performance in two cohorts. For WHO grade prediction, the area under the curve (AUC) was 0.966 (95%CI 0.957-0.975) in the internal testing set and 0.669 (95%CI 0.643-0.695) in the external validation cohort. The AUC in predicting Ki-67 index, H3K27me3, and PR status were 0.905 (95%CI 0.895-0.915), 0.773 (95%CI 0.760-0.786), and 0.771 (95%CI 0.750-0.792) in the internal testing set and 0.591 (95%CI 0.562-0.620), 0.658 (95%CI 0.648-0.668), and 0.703 (95%CI 0.674-0.732) in the external validation cohort, respectively. CONCLUSION: DL models can preoperatively predict meningioma grades and pathologic marker expression with favorable predictive performance. CLINICAL RELEVANCE STATEMENT: Our DL model could predict meningioma grades and expression of pathologic markers and identify high-risk patients with WHO grade 1 meningioma, which would suggest a more aggressive operative intervention preoperatively and a more frequent follow-up schedule postoperatively. KEY POINTS: WHO grades and some pathologic markers of meningioma were associated with therapeutic strategies and clinical outcomes. A deep learning-based approach was employed to develop a model for predicting meningioma grades and the expression of pathologic markers. Preoperative prediction of meningioma grades and the expression of pathologic markers was beneficial for clinical decision-making.

Identification of the Key Immune Cells and Genes for the Diagnostics and Therapeutics of Meningioma.

BACKGROUND: Dysregulation of immune infiltration critically contributes to the tumorigenesis and progression of meningiomas. However, the landscape of immune microenvironment and key genes correlated with immune cell infiltration remains unclear. METHODS: Four Gene Expression Omnibus data sets were included. CIBERSORT algorithm was utilized to analyze the immune cell infiltration in samples. Wilcoxon test, Random Forest algorithm, and Least Absolute Shrinkage and Selection Operator regression were adopted in identifying significantly different infiltrating immune cells and differentially expressed genes (DEGs). Functional enrichment analysis was performed by Kyoto Encyclopedia of Genes and Genomes and Gene Ontology. The correlation between genes and immune cells was evaluated via Spearman's correlation analysis. Receiver Operator Characteristic curve analysis evaluated the markers' diagnostic effectiveness. The mRNA-miRNA and Drug-Gene-Immune cell interaction networks were constructed to identify potential diagnostic and therapeutic targets. RESULTS: Plasma cells, M1 macrophages, M2 macrophages, neutrophils, eosinophils, and activated NK cells were the significantly different infiltrating immune cells in meningioma. A total of 951 DEGs, associated with synaptic function and structure, ion transport regulation, brain function, and immune-related pathways, were identified. Among 11 hub DEGs, RYR2 and TTR were correlated with plasma cells; SNCG was associated with NK cells; ADCY1 exhibited excellent diagnostic effectiveness; and ADCY1, BMX, KCNA5, SLCO4A1, and TTR could be considered as therapeutic targets. CONCLUSIONS: ADCY1 can be identified as a diagnostic marker; ADCY1, BMX, KCNA5, SLCO4A1, and TTR are potential therapeutic targets, and their associations with macrophages, neutrophils, NK cells, and plasma cells might impact the tumorigenesis of meningiomas.

Distinct clinical outcome of microcystic meningioma as a WHO grade 1 meningioma subtype.

OBJECTIVE: To evaluate the clinicopathological characteristics, radiology, and long-term outcomes of microcystic meningiomas (MM) and compare it with other subtypes of meningiomas managed at a single neurosurgical center. METHODS: A total of 87 consecutive patients who underwent surgical resection and were diagnosed as MM between 2005 and 2016 were enrolled for analysis. Clinicopathological, radiology, and prognostic information was collected and analyzed. Progression free survival (PFS) was compared with 659 patients with other subtypes of WHO grade 1 meningiomas and 167 patients with atypical meningiomas treated during the same period. RESULTS: Fifty six females and 31 males with MM were analyzed. Peri-tumor brain edema was frequent on T2 WI (85%).12 patients (13.8%) experienced tumor progression during the mean follow-up of 101.66 ± 40.92 months. The median PFS was unavailable, and the 5, 10, and 15 year progression-free rates were 96.9%, 84.0%, and 73.9%, respectively. Univariate COX analysis demonstrated skull base location and higher Ki-67 index as significant negative prognostic factors for PFS (P < 0.05); multivariate analysis identified tumor location and Ki-67 index as independent factors (P < 0.01), as well. Of note, the PFS of MM was worse than other WHO grade 1 subtypes (P < 0.001), but better than atypical meningiomas (P < 0.001), and the PFS differences were retained even when the analysis was limited to the patients receiving GTR (P < 0.05). CONCLUSION: The PFS of MM was worse than other WHO grade 1 subtypes and better than atypical meningiomas. Skull base location and higher Ki-67 index were independent negative prognostic factors in MM.

Favorable Long-Term Outcomes of Chordoid Meningioma Compared With the Other WHO Grade 2 Meningioma Subtypes.

BACKGROUND: WHO grade 2 meningiomas, including atypical, chordoid, and clear cell subtypes, form a heterogenous group of meningiomas with varying aggressiveness and clinical behavior. OBJECTIVE: To demonstrate the differences of clinical-histopathological characteristics and long-term outcomes among these 3 subtypes. METHODS: A total of 609 consecutive patients diagnosed with WHO grade 2 meningiomas (543 atypical meningiomas [AMs], 36 chordoid meningiomas [CMs], and 30 clear cell meningiomas [CCMs]) from 2010 to 2018 were enrolled in this study. We compared the clinical-histopathological characteristics and long-term outcomes in these 3 subtypes and assessed survival differences among the subtypes. Targeted panel sequencing of meningioma-relevant genes was performed in the cases of CM. RESULTS: The patients with CCM were significantly younger than those with AM ( P < .001) and CM ( P = .016). CMs were more likely to receive gross total resection than AMs and CCMs ( P = .033). The Ki-67 index was lower ( P < .001) while the progesterone receptors-positive rate was higher ( P = .034) in CM than in AM and CCM. Importantly, survival analysis demonstrated that CM had better progression-free survival ( P = .022) and overall survival ( P = .0056) than non-CM tumors. However, the PFS of CM was still worse than WHO grade 1 meningiomas ( P < .001). Alterations in NF2 (20.6%) and KMT2C (26.5%) were associated with poorer PFS in CM ( P = .013 for NF2 ; P = .021 for KMT2C ). CONCLUSION: Patients with CM had better long-term postoperative outcomes than the other WHO grade 2 subtypes. A lower Ki-67 index, higher PR status, higher extent of resection, and lower frequency of NF2 alteration might contribute to favorable clinical outcomes of CM.

Loss of H3K27me3 expression enriches in recurrent grade 1&2 meningiomas and maintains as a biomarker stratifying progression risk.

PURPOSE: To determine if loss of H3K27me3 could predict higher risk of re-recurrence in recurrent meningiomas. METHODS: A retrospective, single-center cohort study was performed for patients who underwent resection of recurrent grade 1 (N = 132) &2 (N = 32) meningiomas from 2009 to 2013. Association of H3K27me3 staining and clinical parameters was analyzed. Additionally, H3K27me3 staining was performed from 45 patients whose tumors recurred and were resected during the follow-up, to evaluate H3K27me3 change during tumor progression. Survival analysis was performed as well. RESULTS: Loss of H3K27me3 expression was observed in 83 patients, comprising 63 grade 1 (47.7%) and 20 grade 2 patients (62.5%). Both grade 1 (p < 0.001) and grade 2 recurrent meningiomas (p < 0.001) had a higher frequency of H3K27me3 loss, compared to de novo meningiomas. 8 of 27 tumors with retained H3K27me3 lost H3K27me3 during re-recurrence (29.6%), while no gain of H3K27me3 was observed in progressive disease from 18 tumors with H3K27me3 loss. Loss of H3K27me3 expression was associated with an earlier re-recurrence in recurrent meningiomas grade 1 and 2 (p < 0.001), and was an independent prognostic factor for PFS in recurrent grade 1 meningiomas (p = 0.005). CONCLUSION: Compared to primary meningiomas, recurrent meningiomas more predominantly had loss of H3K27me3 expression, and further loss can occur during the progression of recurrent tumors. Our results further demonstrated that loss of H3K27me3 predicted shorter PFS in recurrent grade 1 and grade 2 meningiomas. Our work thus supports clinical testing of H3K27me3 in recurrent meningiomas WHO grade 1 and 2.

Progesterone receptor expression and prediction of benefits of adjuvant radiotherapy in de novo atypical meningiomas after gross-total resection.

OBJECTIVE: Benefits of adjuvant radiotherapy (ART) after gross-total resection (GTR) of de novo atypical meningiomas (AMs) are controversial, and factors predictive of radiotherapy benefits in patients with de novo AMs after GTR are unknown. The authors aimed to evaluate the benefits of ART and explore potential factors sensitizing AMs to ART. METHODS: A total of 231 consecutive patients who were pathologically diagnosed with de novo AMs and treated with GTR (Simpson class I-III resections) from 2010 to 2018 were enrolled in the study. Clinicopathological and prognostic information was collected and analyzed. Univariate and multivariate Cox analyses were used to evaluate prognostic predictors and compare the response to radiotherapy. Propensity score matching (PSM) was used to balance the confounding bias in subgroups. RESULTS: A total of 138 patients (59.74%) received ART. Progesterone receptor (PR) expression was positive in 157 patients (67.97%). During the mean follow-up period of 76.25 months, 65 patients (28.14%) experienced recurrence and 38 (16.45%) died of tumor progression. For disease-specific survival (DSS), ART was a better prognostic factor via univariate (p = 0.003) and multivariate (p = 0.025) analyses. For progression-free survival (PFS), univariate Cox analysis showed that ART improved PFS (p = 0.013), but multivariate analysis did not (p = 0.068). Positive PR expression (p = 0.019), age 53.5 years or younger (p = 0.012), and Ki-67 7.5% or lower (p = 0.025) were independent prognostic predictors for better PFS. In the subcohort analysis, the beneficial impact of ART was observed in the PR-negative cohort (p = 0.002) but not in the PR-positive cohort (p = 0.86). The heterogeneity analysis demonstrated that the PR-negative cohort was more sensitive to ART than the PR-positive cohort (p = 0.036). ART was not found to be associated with better PFS in younger patients (≤ 53.5 years, p = 0.14), older patients (> 53.5 years, p = 0.085), those with a Ki-67 index ≤ 7.5% (p = 0.068), or those with a Ki-67 > 7.5% (p = 0.13). The contrasting effects of ART in the PR-negative versus PR-positive cohorts remained true even after PSM, confirming that PR-negative, but not PR-positive, de novo AMs benefited from ART after GTR. CONCLUSIONS: ART was an independent prognostic factor for DSS of patients with de novo AMs treated with GTR (p = 0.025), but not for PFS (p = 0.068). Negative PR expression was a radiosensitive biomarker on PFS for de novo AM patients after GTR.

Application of MRI-Based Radiomics in Preoperative Prediction of NF2 Alteration in Intracranial Meningiomas.

Purpose: This study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma. Methods: This retrospective study included 105 patients with meningiomas, including 60 NF2-mutant samples and 45 wild-type samples. Radiomic features were extracted from magnetic resonance imaging scans, including T1-weighted, T2-weighted, and contrast T1-weighted images. Student's t-test and LASSO regression were performed to select the radiomic features. All patients were randomly divided into training and validation cohorts in a 7:3 ratio. Five linear models (RF, SVM, LR, KNN, and xgboost) were trained to predict the NF2 mutational status. Receiver operating characteristic curve and precision-recall analyses were used to evaluate the model performance. Student's t-tests were then used to compare the posterior probabilities of NF2 mut/loss prediction for patients with different NF2 statuses. Results: Nine features had nonzero coefficients in the LASSO regression model. No significant differences was observed in the clinical features. Nine features showed significant differences in patients with different NF2 statuses. Among all machine learning algorithms, SVM showed the best performance. The area under curve and accuracy of the predictive model were 0.85; the F1-score of the precision-recall curve was 0.80. The model risk was assessed by plotting calibration curves. The p-value for the H-L goodness of fit test was 0.411 (p> 0.05), which indicated that the difference between the obtained model and the perfect model was statistically insignificant. The AUC of our model in external validation was 0.83. Conclusion: A combination of radiomic analysis and machine learning showed potential clinical utility in the prediction of preoperative NF2 status. These findings could aid in developing customized neurosurgery plans and meningioma management strategies before postoperative pathology.

Histone deacetylase inhibitors enhance oncolytic herpes simplex virus therapy for malignant meningioma.

Approximately 20% of meningiomas are not benign (higher grade) and tend to relapse after surgery and radiation therapy. Malignant (anaplastic) meningioma (MM) is a minor subset of high-grade meningioma that is lethal with no effective treatment options currently. Oncolytic herpes simplex virus (oHSV) is a powerful anti-cancer modality that induces both direct cell death and anti-tumor immunity, and has shown activity in preclinical models of MM. However, clinically meaningful efficacy will likely entail rational mechanistic combination approaches. We here show that epigenome modulator histone deacetylase inhibitors (HDACi) increase anti-cancer effects of oHSV in human MM models, IOMM-Lee (NF2 wild-type) and CH157 (NF2 mutant). Minimally toxic, sub-micromolar concentrations of pan-HDACi, Trichostatin A and Panobinostat, substantively increased the infectability and spread of oHSV G47Δ within MM cells in vitro, resulting in enhanced oHSV-mediated killing of target cells when infected at low multiplicity of infection (MOI). Transcriptomics analysis identified selective alteration of mRNA processing and splicing modules that might underlie the potent anti-MM effects of combining HDACi and oHSV. In vivo, HDACi treatment increased intratumoral oHSV replication and boosted the capacity of oHSV to control the growth of human MM xenografts. Thus, our work supports further translational development of the combination approach employing HDACi and oHSV for the treatment of MM.

Molecular diagnosis and treatment of meningiomas: an expert consensus (2022).

ABSTRACT: Meningiomas are the most common primary intracranial neoplasm with diverse pathological types and complicated clinical manifestations. The fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), published in 2021, introduces major changes that advance the role of molecular diagnostics in meningiomas. To follow the revision of WHO CNS5, this expert consensus statement was formed jointly by the Group of Neuro-Oncology, Society of Neurosurgery, Chinese Medical Association together with neuropathologists and evidence-based experts. The consensus provides reference points to integrate key biomarkers into stratification and clinical decision making for meningioma patients. REGISTRATION: Practice guideline REgistration for transPAREncy (PREPARE), IPGRP-2022CN234.

LncRNA-IMAT1 Promotes Invasion of Meningiomas by Suppressing KLF4/hsa-miR22-3p/Snai1 Pathway.

Malignant meningiomas often show invasive growth that makes complete tumor resection challenging, and they are more prone to recur after radical resection. Invasive meningioma associated transcript 1 (IMAT1) is a long noncoding RNA located on Homo sapiens chromosome 17 that was identified by our team based on absolute expression differences in invasive and non-invasive meningiomas. Our studies indicated that IMAT1 was highly expressed in invasive meningiomas compared with non-invasive meningiomas. In vitro studies showed that IMAT1 promoted meningioma cell invasion through the inactivation of the Krüppel-like factor 4 (KLF4)/hsa-miR22-3p/Snai1 pathway by acting as a sponge for hsa-miR22-3p, and IMAT1 knockdown effectively restored the tumor suppressive properties of KLF4 by preserving its tumor suppressor pathway. In vivo experiments confirmed that IMAT1 silencing could significantly inhibit the growth of subcutaneous tumors and prolong the survival period of tumor-bearing mice. Our findings demonstrated that the high expression of IMAT1 is the inherent reason for the loss of the tumor suppressive properties of KLF4 during meningioma progression. Therefore, we believe that IMAT1 may be a potential biological marker and treatment target for meningiomas.

TERT Alterations Predict Tumor Progression in De Novo High-Grade Meningiomas Following Adjuvant Radiotherapy.

BACKGROUND: Adjuvant radiotherapy (RT) is one of the most commonly used treatments for de novo high-grade meningiomas (HGMs) after surgery, but genetic determinants of clinical benefit are poorly characterized. OBJECTIVE: We describe efforts to integrate clinical genomics to discover predictive biomarkers that would inform adjuvant treatment decisions in de novo HGMs. METHODS: We undertook a retrospective analysis of 37 patients with de novo HGMs following RT. Clinical hybrid capture-based sequencing assay covering 184 genes was performed in all cases. Associations between tumor clinical/genomic characteristics and RT response were assessed. Overall survival (OS) and progression-free survival (PFS) curves were plotted using the Kaplan-Meier method. RESULTS: Among the 172 HGMs from a single institution, 42 cases (37 WHO grade 2 meningiomas and five WHO grade 3 meningiomas) were identified as de novo HGMs following RT. Only TERT mutations [62.5% C228T; 25% C250T; 12.5% copy number amplification (CN amp.)] were significantly associated with tumor progression after postoperative RT (adjusted p = 0.003). Potential different somatic interactions between TERT and other tested genes were not identified. Furthermore, TERT alterations (TERT-alt) were the predictor of tumor progression (Fisher's exact tests, p = 0.003) and were associated with decreased PFS (log-rank test, p = 0.0114) in de novo HGMs after RT. CONCLUSION: Our findings suggest that TERT-alt is associated with tumor progression and poor outcome of newly diagnosed HGM patients after postoperative RT.

MEF2C silencing downregulates NF2 and E-cadherin and enhances Erastin-induced ferroptosis in meningioma.

BACKGROUND: Ferroptosis, a programmed cell death characterized by lipid peroxidation, is implicated in various diseases including cancer. Although cell density-dependent E-cadherin and Merlin/Neurofibromin (NF2) loss can modulate ferroptosis, the role of ferroptosis and its potential link to NF2 status and E-cadherin expression in meningioma remain unknown. METHODS: Relationship between ferroptosis modulators expression and NF2 mutational status was examined in 35 meningiomas (10 NF2 loss and 25 NF2 wild type). The impact of NF2 and E-cadherin on ferroptosis were examined by lactate dehydrogenase (LDH) release, lipid peroxidation, and western blot assays in IOMM-Lee, CH157, and patient-derived meningioma cell models. Luciferase reporter and chromatin immunoprecipitation assays were used to assess the ability of MEF2C (myocyte enhancer factor 2C) to drive expression of NF2 and CDH1 (E-cadherin). Therapeutic efficacy of Erastin-induced ferroptosis was tested in xenograft mouse models. RESULTS: Meningioma cells with NF2 inactivation were susceptible to Erastin-induced ferroptosis. Meningioma cells grown at higher density increased expression of E-cadherin, which suppressed Erastin-induced ferroptosis. Maintaining NF2 and E-cadherin inhibited ferroptosis-related lipid peroxidation and meningioma cell death. MEF2C was found to drive the expression of both NF2 and E-cadherin. MEF2C silencing enhanced Erastin-induced ferroptotic meningioma cell death and lipid peroxidation levels in vitro, which was limited by forced expression of MEF2C targets, NF2 and E-cadherin. In vivo, anti-meningioma effect of Erastin was augmented by MEF2C knockdown and was counteracted by NF2 or E-cadherin. CONCLUSIONS: NF2 loss and low E-cadherin create susceptibility to ferroptosis in meningioma. MEF2C could be a new molecular target in ferroptosis-inducing therapies for meningioma.

m6A Regulator Expression Segregates Meningiomas Into Biologically Distinct Subtypes.

BACKGROUND: Meningiomas are the most common primary intracranial tumors in adults. According to the 2021 World Health Organization (WHO) classification of central nervous system tumors, approximately 80% of meningiomas are WHO grade 1, that is, histopathologically benign, whereas about 20% are WHO grade 2 or grade 3, showing signs of atypia or malignancy. The dysregulation of N6-methylation (m6A) regulators is associated with disorders of diverse critical biological processes in human cancer. This study aimed to explore whether m6A regulator expression was associated with meningioma molecular subtypes and immune infiltration. METHODS: We evaluated the m6A modification patterns of 160 meningioma samples based on 19 m6A regulators and correlated them with immune infiltration characteristics. Novel molecular subtypes were defined based on prognostic hub gene expression. RESULTS: Two meningioma clusters were identified based on the expression of 19 m6A regulators. In cluster 1, 607 differentially expressed genes (DEGs) were upregulated and 519 were downregulated. A total of 1,126 DEGs comprised three gene expression modules characterized by turquoise, blue, and gray. Functional annotation suggested that the turquoise module was involved in Wnt-related and other important cancer-related pathways. We identified 32 hub genes in this module by constructing a protein-protein interaction network. The meningioma samples were divided into two molecular subtypes. EPN1, EXOSC4, H2AX, and MZT2B not only showed significant differences between meningioma molecular subtypes but also had the potential to be the marker genes of specific meningioma subtypes. CONCLUSION: m6A regulator gene expression may be a novel prognostic marker in meningioma.

Prognostic Model That Predicts Benefits of Adjuvant Radiotherapy in Patients With High Grade Meningioma.

OBJECTIVE: Adjuvant radiotherapy is the main treatment modality for high grade meningioma after surgical resection; however, recurrence and survival outcomes vary. The aim of this study was to create a new "prognostic score" that allows personalized recommendations for post-operative adjuvant radiotherapy in patients with high grade meningioma. METHODS: Clinical data were collected from 115 patients with high grade meningioma treated with surgical resection and adjuvant radiotherapy. A prognostic model was built based on the hazards ratios of independent prognostic factors yielded by multivariate cox proportional analysis. Calibration and discrimination of the prognostic score was evaluated using good of fit test and Harrel's C index, respectively. RESULTS: A total of 115 high grade meningioma patients (72 atypical and 43 anaplastic meningiomas) were enrolled. Three factors were independently associated with progression-free survival (PFS): extent of resection (GTR vs. STR), recurrent status (de novo vs. recurrent), and Ki-67 labeling index (<5% vs. ≥ 5%). The respective ß-coefficients were used to generate the "prognostic score". The cohort was divided into low-risk and high-risk groups based on the median prognostic score. Good of fit test showed strong calibration (P = 0.7133) and Harrel's C index 0.766 indicated a strong discrimination capability of the prognostic score. The Harrel's C index for OS was 0.60. CONCLUSIONS: Our prognostic model using three basic clinical parameters robustly separated high grade meningioma patients who benefit vs. do not benefit from adjuvant radiotherapy. External validation of our model is warranted to help improve patient selection suitable for adjuvant radiotherapy.