Integrated clinical genomic analysis reveals xenobiotic metabolic genes are downregulated in meningiomas of current smokers.

INTRODUCTION: Meningiomas are the most common primary intracranial tumor. Recently, various genetic classification systems for meningioma have been described. We sought to identify clinical drivers of different molecular changes in meningioma. As such, clinical and genomic consequences of smoking in patients with meningiomas remain unexplored. METHODS: 88 tumor samples were analyzed in this study. Whole exome sequencing (WES) was used to assess somatic mutation burden. RNA sequencing data was used to identify differentially expressed genes (DEG) and genes sets (GSEA). RESULTS: Fifty-seven patients had no history of smoking, twenty-two were past smokers, and nine were current smokers. The clinical data showed no major differences in natural history across smoking status. WES revealed absence of AKT1 mutation rate in current or past smokers compared to non-smokers (p = 0.046). Current smokers had increased mutation rate in NOTCH2 compared to past and never smokers (p < 0.05). Mutational signature from current and past smokers showed disrupted DNA mismatch repair (cosine-similarity = 0.759 and 0.783). DEG analysis revealed the xenobiotic metabolic genes UGT2A1 and UGT2A2 were both significantly downregulated in current smokers compared to past (Log2FC = - 3.97, padj = 0.0347 and Log2FC = - 4.18, padj = 0.0304) and never smokers (Log2FC = - 3.86, padj = 0.0235 and Log2FC = - 4.20, padj = 0.0149). GSEA analysis of current smokers showed downregulation of xenobiotic metabolism and enrichment for G2M checkpoint, E2F targets, and mitotic spindle compared to past and never smokers (FDR < 25% each). CONCLUSION: In this study, we conducted a comparative analysis of meningioma patients based on their smoking history, examining both their clinical trajectories and molecular changes. Meningiomas from current smokers were more likely to harbor NOTCH2 mutations, and AKT1 mutations were absent in current or past smokers. Moreover, both current and past smokers exhibited a mutational signature associated with DNA mismatch repair. Meningiomas from current smokers demonstrate downregulation of xenobiotic metabolic enzymes UGT2A1 and UGT2A2, which are downregulated in other smoking related cancers. Furthermore, current smokers exhibited downregulation xenobiotic metabolic gene sets, as well as enrichment in gene sets related to mitotic spindle, E2F targets, and G2M checkpoint, which are hallmark pathways involved in cell division and DNA replication control. In aggregate, our results demonstrate novel alterations in meningioma molecular biology in response to systemic carcinogens.

Identification of novel fusion transcripts in meningioma.

INTRODUCTION: Meningiomas are the most common primary intracranial tumor. Recent next generation sequencing analyses have elaborated the molecular drivers of this disease. We aimed to identify and characterize novel fusion genes in meningiomas. METHODS: We performed a secondary analysis of our RNA sequencing data of 145 primary meningioma from 140 patients to detect fusion genes. Semi-quantitative rt-PCR was performed to confirm transcription of the fusion genes in the original tumors. Whole exome sequencing was performed to identify copy number variations within each tumor sample. Comparative RNA seq analysis was performed to assess the clonality of the fusion constructs within the tumor. RESULTS: We detected six fusion events (NOTCH3-SETBP1, NF2-SPATA13, SLC6A3-AGBL3, PHF19-FOXP2 in two patients, and ITPK1-FBP2) in five out of 145 tumor samples. All but one event (NF2-SPATA13) led to extremely short reading frames, making these events de facto null alleles. Three of the five patients had a history of childhood radiation. Four out of six fusion events were detected in expression type C tumors, which represent the most aggressive meningioma. We validated the presence of the RNA transcripts in the tumor tissue by semi-quantitative RT PCR. All but the two PHF19-FOXP2 fusions demonstrated high degrees of clonality. CONCLUSIONS: Fusion genes occur infrequently in meningiomas and are more likely to be found in tumors with greater degree of genomic instability (expression type C) or in patients with history of cranial irradiation.

A patient with a novel homozygous missense mutation in FTO and concomitant nonsense mutation in CETP.

The fat mass and obesity associated (FTO) gene has previously been associated with a variety of diseases and conditions, notably obesity, acute coronary syndrome and metabolic syndrome. Reports describing mutations in FTO as well as in FTO animal models have further demonstrated a role for FTO in the development of the brain and other organs. Here, we describe a patient born of consanguineous union who presented with microcephaly, developmental delay, behavioral abnormalities, dysmorphic facial features, hypotonia and other various phenotypic abnormalities. Whole-exome sequencing revealed a novel homozygous missense mutation in FTO and a nonsense mutation in the cholesteryl ester transfer protein (CETP). Exome copy number variation analysis revealed no disease-causing large duplications or deletions within coding regions. Patient's, her parents' and non-related control' fibroblasts were analyzed for morphologic defects, abnormal proliferation, apoptosis and transcriptome profile. We have shown that FTO is located in the nucleus of cells from each tested sample. Western blot analysis demonstrated no changes in patient FTO. Quantitative (qPCR) analysis revealed slightly decreased levels of FTO expression in patient cells compared with controls. No morphological or proliferation differences between the patient and control fibroblasts were observed. There is still much to be learned about the molecular mechanisms by which mutations in FTO contribute to such severe phenotypes.

Hypermitotic meningiomas harbor DNA methylation subgroups with distinct biological and clinical features.

BACKGROUND: Meningiomas, the most common primary intracranial tumors, can be separated into 3 DNA methylation groups with distinct biological drivers, clinical outcomes, and therapeutic vulnerabilities. Alternative meningioma grouping schemes using copy number variants, gene expression profiles, somatic short variants, or integrated molecular models have been proposed. These data suggest meningioma DNA methylation groups may harbor subgroups unifying contrasting theories of meningioma biology. METHODS: A total of 565 meningioma DNA methylation profiles from patients with comprehensive clinical follow-up at independent discovery (n = 200) or validation (n = 365) institutions were reanalyzed and classified into Merlin-intact, Immune-enriched, or Hypermitotic DNA methylation groups. RNA sequencing from the discovery (n = 200) or validation (n = 302) cohort were analyzed in the context of DNA methylation groups to identify subgroups. Biological features and clinical outcomes were analyzed across meningioma grouping schemes. RESULTS: RNA sequencing revealed differential enrichment of FOXM1 target genes across two subgroups of Hypermitotic meningiomas. Differential expression and ontology analyses showed the subgroup of Hypermitotic meningiomas without FOXM1 target gene enrichment was distinguished by gene expression programs driving macromolecular metabolism. Analysis of genetic, epigenetic, gene expression, or cellular features revealed Hypermitotic meningioma subgroups were concordant with Proliferative or Hypermetabolic meningiomas, which were previously reported alongside Merlin-intact and Immune-enriched tumors using an integrated molecular model. The addition of DNA methylation subgroups to clinical models refined the prediction of postoperative outcomes compared to the addition of DNA methylation groups. CONCLUSIONS: Meningiomas can be separated into three DNA methylation groups and Hypermitotic meningiomas can be subdivided into Proliferative and Hypermetabolic subgroups, each with distinct biological and clinical features.

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses.

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses.

Multiple approaches converge on three biological subtypes of meningioma and extract new insights from published studies.

One-fifth of meningiomas classified as benign by World Health Organization (WHO) histopathological grading will behave malignantly. To better diagnose these tumors, several groups turned to DNA methylation, whereas we combined RNA-sequencing (RNA-seq) and cytogenetics. Both approaches were more accurate than histopathology in identifying aggressive tumors, but whether they revealed similar tumor types was unclear. We therefore performed unbiased DNA methylation, RNA-seq, and cytogenetic profiling on 110 primary meningiomas WHO grade I and II). Each technique distinguished the same three groups (two benign and one malignant) as our previous molecular classification; integrating these methods into one classifier further improved accuracy. Computational modeling revealed strong correlations between transcription and cytogenetic changes, particularly loss of chromosome 1p, in malignant tumors. Applying our classifier to data from previous studies also resolved certain anomalies entailed by grouping tumors by WHO grade. Accurate classification will therefore elucidate meningioma biology as well as improve diagnosis and prognosis.

Racial and Socioeconomic Disparities in Patients With Meningioma: A Retrospective Cohort Study.

BACKGROUND: Meningiomas are the most common intracranial neoplasms. Although genomic analysis has helped elucidate differences in survival, there is evidence that racial disparities may influence outcomes. African Americans have a higher incidence of meningiomas and poorer survival outcomes. The etiology of these disparities remains unclear, but may include a combination of pathophysiology and other factors. OBJECTIVE: To determine factors that contribute to different clinical outcomes in racial populations. METHODS: We retrospectively reviewed 305 patients who underwent resection for meningiomas at a single tertiary care facility. We used descriptive statistics and univariate, multivariable, and Kaplan-Meier analyses to study clinical, radiographical, and histopathological differences. RESULTS: Minority patients were more likely to present through the emergency department than an outpatient clinic (P < .0001). They were more likely to present with more advanced clinical symptoms with lower Karnofsky Performance scores, more frequently had peritumoral edema (P = .0031), and experienced longer postoperative stays in the hospital (P = .0053), and African-American patients had higher hospitalization costs (P = .046) and were more likely to be publicly insured. Extent of resection was an independent predictor of recurrence freedom (P = .039). Presentation in clinic setting trended toward an association with recurrence-free survival (P = .055). We observed no significant difference in gross total resection rates, postoperative recurrence, or recurrence-free survival. CONCLUSION: Minority patients are more likely to present with severe symptoms, require longer perioperative hospitalization, and generate higher hospitalization costs. This may be due to socioeconomic factors that affect access to health care. Targeting barriers to access, especially to subspecialty care, may facilitate more appropriate and timely diagnosis, thereby improving patient care and outcomes.

Predictors of postoperative seizure outcome in supratentorial meningioma.

OBJECTIVE: Meningiomas are the most common primary intracranial tumor. Seizures are common sequelae of meningioma development. Meningioma patients with seizures can be effectively treated with resection, with reports of seizure freedom of 60%-90%. Still, many patients manifest persistent epilepsy. Determining factors associated with worsened seizure outcomes remains critical in improving the quality of life for these patients. The authors sought to identify clinical, radiological, and histological factors associated with worse seizure outcomes in patients with supratentorial meningioma and preoperative seizures. METHODS: The authors retrospectively reviewed the charts of 384 patients who underwent meningioma resection from 2008 to 2020. The charts of patients with a documented history of preoperative seizures were further reviewed for clinical, radiological, operative, perioperative, histological, and postoperative factors associated with seizures. Engel class at last follow-up was retrospectively assigned by the authors and further grouped into favorable (class I) and worse (class II-IV) outcomes. Factors were subsequently compared by group using comparative statistics. Univariable and multivariable regression models were utilized to identify independent predictors of worse seizure outcome. RESULTS: Fifty-nine patients (15.4%) were found to have preoperative seizures, of whom 57 had sufficient postoperative data to determine Engel class outcome. Forty-two patients (74%) had Engel class I outcomes. The median follow-up was 17 months. Distinct margins on preoperative imaging (p = 0.012), Simpson grade I resection (p = 0.004), postresection ischemia (p = 0.019), WHO grade (p = 0.019), and recurrent disease (p = 0.015) were found to be the strongest predictors of Engel class outcome in univariable logistic regression. MIB-1 index (p = 0.001) and residual volume (p = 0.014) at last follow-up were found to be the strongest predictors of Engel class outcome in univariable generalized linear regression. Postresection ischemia (p = 0.012), WHO grade (p = 0.022), recurrent disease (p = 0.038), and MIB-1 index (p = 0.002) were found to be the strongest independent predictors of Engel class outcomes in multivariable analysis. CONCLUSIONS: Postresection ischemia, higher WHO grade, elevated MIB-1 index, and disease recurrence independently predict postresection seizure persistence in patients with supratentorial meningioma. Further understanding of the etiology of these markers may aid in elucidation of this complex disease process and guide management to prevent worse outcomes.