Gene expression profiles of meningiomas are associated with tumor cytogenetics and patient outcome

Plasma extracellular vesicles proteomics in meningioma patients

Tumor derived Extracellular vesicles (EVs) in circulating system may contain tumor-specific markers, and EV detection in body fluids could become an important tool for early tumor diagnosis, prognosis assessment. Meningiomas are the most common benign intracranial tumors, few studies have revealed specific protein markers for meningiomas from patients' body fluids. In this study, using proximity labeling technology and non-tumor patient plasma as a control, we detected protein levels of EVs in plasma samples from meningioma patients before and after surgery. Through bioinformatics analysis, we discovered that the levels of EV count and protein count in meningioma patients were significantly higher than those in healthy controls, and were significantly decreased postoperatively. Among EV proteins in meningioma patients, the levels of MUC1, SIGLEC11, E-Cadherin, KIT, and TASCTD2 were found not only significantly elevated than those in healthy controls, but also significantly decreased after tumor resection. Moreover, using publicly available GEO databases, we verified that the mRNA level of MUC1, SIGLEC11, and CDH1 in meningiomas were significantly higher in comparison with normal dura mater tissues. Additionally, by analyzing human meningioma specimens collected in this study, we validated the protein levels of MUC1 and SIGLEC11 were significantly increased in WHO grade 2 meningiomas and were positively correlated with tumor proliferation levels. This study indicates that meningiomas secret EV proteins into circulating system, which may serve as specific markers for diagnosis, malignancy predicting and tumor recurrent assessment.

The Natural History and Treatment of Meningiomas: An Update

Meningiomas are the most frequent nonmalignant tumors of the central nervous system (CNS). Despite their benign nature and slow-growing pattern, if not diagnosed early, these tumors may reach relatively large sizes causing significant morbidity and mortality. Some variants are located in hard-to-access locations, compressing critical neurovascular structures, and making the surgical management even more challenging. Although most meningiomas have a good long-term prognosis after treatment, there are still controversies over their management in a subset of cases. While surgery is the first-line treatment, the use of fractionated radiotherapy or stereotactic radiosurgery is indicated for residual or recurrent tumors, small lesions, and tumors in challenging locations. Advances in molecular genetics and ongoing clinical trial results have recently helped both to refine the diagnosis and provide hope for effective biomolecular target-based medications for treatment. This article reviews the natural history and current therapeutic options for CNS meningiomas.

Domestic Animal Models of Central Nervous System Tumors: Focus on Meningiomas

Intracranial primary tumors (IPTs) are aggressive forms of malignancies that cause high mortality in both humans and domestic animals. Meningiomas are frequent adult IPTs in humans, dogs, and cats, and both benign and malignant forms cause a decrease in life quality and survival. Surgery is the primary therapeutic approach to treat meningiomas, but, in many cases, it is not resolutive. The chemotherapy and targeted therapy used to treat meningiomas also display low efficacy and many side effects. Therefore, it is essential to find novel pharmacological approaches to increase the spectrum of therapeutic options for meningiomas. This review analyzes the similarities between human and domestic animal (dogs and cats) meningiomas by evaluating the molecular and histological characteristics, diagnosis criteria, and treatment options and highlighting possible research areas to identify novel targets and pharmacological approaches, which are useful for the diagnosis and therapy of this neoplasia to be used in human and veterinary medicine.

The role of m6A RNA methylation regulator in meningioma

Meningiomas are common intracranial tumors, and the effect of surgical resection is often unsatisfactory. N6-Methyladenosine (m6A)-related regulator expression levels are related to cancer occurrence and development. This study aimed to investigate the roles of m6A RNA methylation regulators in meningiomas, as these are currently unclear. Two m6A methylation-regulated genes (METTL3 and IGF2BP2) were identified as survival-associated linear models for RiskScore through bioinformatics analysis. Univariate and multivariate Cox regression analyses showed that the overall survival of patients with meningioma in the high-risk group was substantially shorter than that in the low-risk group. Weighted gene co-expression network analysis constructed a co-expression network based on the m6A methylation model (RiskScore). Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analyses identified the biological processes of hub module gene behavior, and Cytoscape constructed an m6A methylation-related gene regulatory network. In vitro experiments verified that the mRNA and protein expression levels of METTL3 and IGF2BP2 were lower in meningioma cells than in normal meningioma cells. Therefore, central regulators of m6A methylation (METTL3 and IGF2BP2) could potentially serve as novel therapeutic targets in meningioma. Subsequently, a novel methylation signature (RiskScore) was developed for prognostic prediction in patients with meningioma.

Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis

Meningioma is one of the most common primary tumors in the central nervous system (CNS). A deeper understanding of its molecular characterization could provide potential therapeutic targets to reduce recurrence. In this study, we attempted to identify specific gene mutations in meningioma for immunotherapy. One GSE43290 dataset was obtained from the Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs) between meningioma tissues and normal meninges. In total, 420 DEGs were identified, including 15 up-regulated and 405 down-regulated genes. Functional enrichment analysis showed that these DEGs were mainly enriched in PI3K-Akt signaling pathway, Focal adhesion, and MAPK signaling pathway. We identified 20 hub genes by protein-protein interaction (PPI) analysis. Among the hub genes, the expression of FLT1, CXCL8, JUN, THBS1, FECAM1, CD34, and FGF13 were negatively correlated with Programmed Death Ligand-1 (PD-L1). Additionally, the expression of those genes was co-regulated by miR-155-5p. The findings suggest that miR-155-5p play an important role in the pathogenesis of meningioma and may represent potential therapeutic targets for its anti-PD-L1 immunotherapy.

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.

Gene Expression Signatures Identify Biologically Homogenous Subgroups of Grade 2 Meningiomas

Introduction

Meningiomas are the most common brain tumor, with prevalence of approximately 3%. Histological grading has a major role in determining treatment choice and predicting outcome. While indolent grade 1 and aggressive grade 3 meningiomas exhibit relatively homogeneous clinical behavior, grade 2 meningiomas are far more heterogeneous, making outcome prediction challenging. We hypothesized two subgroups of grade 2 meningiomas which biologically resemble either World Health Organization (WHO) grade 1 or WHO grade 3. Our aim was to establish gene expression signatures that separate grade 2 meningiomas into two homogeneous subgroups: a more indolent subtype genetically resembling grade 1 and a more aggressive subtype resembling grade 3.

Methods

We carried out an observational meta-analysis on 212 meningiomas from six distinct studies retrieved from the open-access platform Gene Expression Omnibus. Microarray data was analyzed with systems-level gene co-expression network analysis. Fuzzy C-means clustering was employed to reclassify 34 of the 46 grade 2 meningiomas (74%) into a benign “grade 1-like” (13/46), and malignant “grade 3-like” (21/46) subgroup based on transcriptomic profiles. We verified shared biology between matching subgroups based on meta-gene expression and recurrence rates. These results were validated further using an independent RNA-seq dataset with 160 meningiomas, with similar results.

Results

Recurrence rates of “grade 1-like” and “grade 3- like” tumors were 0 and 75%, respectively, statistically similar to recurrence rates of grade 1 (17%) and 3 (85%). We also found overlapping biological processes of new subgroups with their adjacent grades 1 and 3.

Conclusion

These results underpin molecular signatures as complements to histological grading systems. They may help reshape prediction, follow-up planning, treatment decisions and recruitment protocols for future and ongoing clinical trials.

Meta-gene markers predict meningioma recurrence with high accuracy

Meningiomas, the most common adult brain tumors, recur in up to half of cases. This requires timely intervention and therefore accurate risk assessment of recurrence is essential. Our current practice relies heavily on histological grade and extent of surgical excision to predict meningioma recurrence. However, prediction accuracy can be as poor as 50% for low or intermediate grade tumors which constitute the majority of cases. Moreover, attempts to find molecular markers to predict their recurrence have been impeded by low or heterogenous genetic signal. We therefore sought to apply systems-biology approaches to transcriptomic data to better predict meningioma recurrence. We apply gene co-expression networks to a cohort of 252 adult patients from the publicly available genetic repository Gene Expression Omnibus. Resultant gene clusters (“modules”) were represented by the first principle component of their expression, and their ability to predict recurrence assessed with a logistic regression model. External validation was done using two independent samples: one merged microarray-based cohort with a total of 108 patients and one RNA-seq-based cohort with 145 patients, using the same modules. We used the bioinformatics database Enrichr to examine the gene ontology associations and driver transcription factors of each module. Using gene co-expression analysis, we were able predict tumor recurrence with high accuracy using a single module which mapped to cell cycle-related processes (AUC of 0.81 ± 0.09 and 0.77 ± 0.10 in external validation using microarray and RNA-seq data, respectively). This module remained predictive when controlling for WHO grade in all cohorts, and was associated with several cancer-associated transcription factors which may serve as novel therapeutic targets for patients with this disease. With the easy accessibility of gene panels in healthcare diagnostics, our results offer a basis for routine molecular testing in meningioma management and propose potential therapeutic targets for future research.

Integrated Transcriptomic Analysis Reveals the Molecular Mechanism of Meningiomas by Weighted Gene Coexpression Network Analysis

Meningiomas are the most common primary intracranial tumor in adults. However, to date, systemic coexpression analyses for meningiomas fail to explain its pathogenesis. The aim of the present study was to construct coexpression modules and identify potential biomarkers associated with meningioma progression. Weighted gene coexpression network analysis (WGCNA) was performed based on GSE43290, and module preservation was tested by GSE74385. Functional annotations were performed to analyze biological significance. Hub genes were selected for efficacy evaluations and correlation analyses using two independent cohorts. A total of 14 coexpression modules were identified, and module lightcyan was significantly associated with WHO grades. Functional enrichment analyses of module lightcyan were associated with tumor pathogenesis. The top 10 hub genes were extracted. Ten biomarkers, particularly AHCYL2, FGL2, and KCNMA1, were significantly related to grades and prognosis of meningioma. These findings not only construct coexpression modules leading to the better understanding of its pathogenesis but also provide potential biomarkers that represent specific on tumor grades and identify recurrence, predicting prognosis and progression of meningiomas.

Identification of epithelial membrane protein 2 (EMP2) as a molecular marker and correlate for angiogenesis in meningioma

PURPOSE

Although intracranial meningiomas are the most common primary brain tumor in adults, treatment options are few and have traditionally been limited to surgical resection and radiotherapy. Additional targeted therapies and biomarkers are needed, especially as complete surgical resection is frequently not feasible in many patients.

METHODS

Non-pathologic brain tissue from 3 patients undergoing routine autopsies and tumor specimens from 16 patients requiring surgical resection for meningioma were collected. EMP2 protein expression was evaluated by immunohistochemistry and western blot analysis. EMP2 mRNA expression was also investigated using surgical specimens and validated by analysis of several independent NCBI GEO databases.

RESULTS

EMP2 mRNA expression levels were found to be higher in meningioma relative to non-pathologic meninges (P = 0.0013) and brain (P = 0.0011). Concordantly, strong EMP2 protein expression was demonstrated in 100% of meningioma specimens from all 16 patients, with no observable protein expression in normal brain tissue samples from 3 subjects (P < 0.001). EMP2 expression was confirmed by western blot analysis in five samples, with EMP2 protein intensity positively correlating with histologic staining score (R² = 0.780; P = 0.047). No association was found between EMP2 mRNA or protein levels and WHO grade or markers of proliferation. However, EMP2 expression was positively associated with an angiomatous pattern on histologic evaluation (P = 0.0597), VEGF-A mRNA expression (P < 0.001), and clinical markers of tumor vascularity such as operative blood loss (P = 0.037).

CONCLUSIONS

EMP2 is not found in normal brain tissue, yet has shown consistently high mRNA and protein expression in meningiomas, and may serve as a useful molecular marker for these tumors.

Leveraging the Role of the Metastatic Associated Protein Anterior Gradient Homologue 2 in Unfolded Protein Degradation: A Novel Therapeutic Biomarker for Cancer

Effective diagnostic, prognostic and therapeutic biomarkers can help in tracking disease progress, predict patients’ survival, and considerably affect the drive for successful clinical management. The present review aims to determine how the metastatic-linked protein anterior gradient homologue 2 (AGR2) operates to affect cancer progression, and to identify associated potential diagnostic, prognostic and therapeutic biomarkers, particularly in central nervous system (CNS) tumors. Studies that show a high expression level of AGR2, and associate the protein expression with the resilience to chemotherapeutic treatments or with poor cancer survival, are reported. The primary protein structures of the seven variants of AGR2, including their functional domains, are summarized. Based on experiments in various biological models, this review shows an orchestra of multiple molecules that regulate AGR2 expression, including a feedback loop with p53. The AGR2-associated molecular functions and pathways including genomic integrity, proliferation, apoptosis, angiogenesis, adhesion, migration, stemness, and inflammation, are detailed. In addition, the mechanisms that can enable the rampant oncogenic effects of AGR2 are clarified. The different strategies used to therapeutically target AGR2-positive cancer cells are evaluated in light of the current evidence. Moreover, novel associated pathways and clinically relevant deregulated genes in AGR2 high CNS tumors are identified using a meta-analysis approach.

Identification of key genes and pathways in meningioma by bioinformatics analysis

Meningioma is the most frequently occurring type of brain tumor. The present study aimed to conduct a comprehensive bioinformatics analysis of key genes and relevant pathways involved in meningioma, and acquire further insight into the underlying molecular mechanisms. Initially, differentially expressed genes (DEGs) in 47 meningioma samples as compared with 4 normal meninges were identified. Subsequently, these DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. In addition, a protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. In total, 1,683 DEGs were identified, including 66 upregulated and 1,617 downregulated genes. The GO analysis results revealed that the DEGs were significantly associated with the ‘protein binding’, ‘cytoplasm’, ‘extracellular matrix (ECM) organization’ and ‘cell adhesion’ terms. The KEGG analysis results demonstrated the significant pathways included ‘AGE-RAGE signaling pathway in diabetic complications’, ‘PI3K-Akt signaling pathway’, ‘ECM-receptor interaction’ and ‘cell adhesion molecules’. The top five hub genes obtained from the PPI network were JUN, PIK3R1, FOS, AGT and MYC, and the most enriched KEGG pathways associated with the four obtained modules were ‘chemokine signaling pathway’, ‘cytokine-cytokine receptor interaction’, ‘allograft rejection’, and ‘complement and coagulation cascades’. In conclusion, bioinformatics analysis identified a number of potential biomarkers and relevant pathways that may represent key mechanisms involved in the development and progression of meningioma. However, these findings require verification in future experimental studies.

A gene expression signature predicts recurrence-free survival in meningioma

BACKGROUND

Meningioma is the most common primary brain tumor and has a variable risk of local recurrence. While World Health Organization (WHO) grade generally correlates with recurrence, there is substantial within-grade variation of recurrence risk. Current risk stratification does not accurately predict which patients are likely to benefit from adjuvant radiation therapy (RT). We hypothesized that tumors at risk for recurrence have unique gene expression profiles (GEP) that could better select patients for adjuvant RT.

METHODS

We developed a recurrence predictor by machine learning modeling using a training/validation approach.

RESULTS

Three publicly available AffymetrixU133 gene expression datasets (GSE9438, GSE16581, GSE43290) combining 127 primary, non-treated meningiomas of all grades served as the training set. Unsupervised variable selection was used to identify an 18-gene GEP model (18-GEP) that separated recurrences. This model was validated on 62 primary, non-treated cases with similar grade and clinical variable distribution as the training set. When applied to the validation set, 18-GEP separated recurrences with a misclassification error rate of 0.25 (log-rank p=0.0003). 18-GEP was predictive for tumor recurrence [p=0.0008, HR=4.61, 95%CI=1.89-11.23)] and was predictive after adjustment for WHO grade, mitotic index, sex, tumor location, and Simpson grade [p=0.0311, HR=9.28, 95%CI=(1.22-70.29)]. The expression signature included genes encoding proteins involved in normal embryonic development, cell proliferation, tumor growth and invasion (FGF9, SEMA3C, EDNRA), angiogenesis (angiopoietin-2), cell cycle regulation (CDKN1A), membrane signaling (tetraspanin-7, caveolin-2), WNT-pathway inhibitors (DKK3), complement system (C1QA) and neurotransmitter regulation (SLC1A3, Secretogranin-II).

CONCLUSIONS

18-GEP accurately stratifies patients with meningioma by recurrence risk having the potential to guide the use of adjuvant RT.

New drug candidates for treatment of atypical meningiomas: An integrated approach using gene expression signatures for drug repurposing

Background

Atypical meningiomas are common central nervous system neoplasms with high recurrence rate and poorer prognosis compared to their grade I counterparts. Surgical excision and radiotherapy remains the mainstay therapy but medical treatments are limited. We explore new drug candidates using computational drug repurposing based on the gene expression signature of atypical meningioma tissue with subsequent analysis of drug-generated expression profiles. We further explore possible mechanisms of action for the identified drug candidates using ingenuity pathway analysis (IPA).

Methods

We extracted gene expression profiles for atypical meningiomas (12 samples) and normal meningeal tissue (4 samples) from the Gene Expression Omnibus, which were then used to generate a gene signature comprising of 281 differentially expressed genes. Drug candidates were explored using both the Board Institute Connectivity Map (cmap) and Library of Integrated Network-Based Cellular Signatures (LINCS). Functional analysis of significant differential gene expression for drug candidates was performed with IPA.

Results

Using our integrated approach, we identified multiple, already licensed, drug candidates such as emetine, verteporfin, phenoxybenzamine and trazodone. Analysis with IPA revealed that these drugs target signal cascades potentially relevant in pathogenesis of meningiomas, particular examples are the effect on ERK by trazodone, MAP kinases by emetine, and YAP-1 protein by verteporfin.

Conclusion

Gene expression profiling and use of drug expression profiles have yielded several plausible drug candidates for treating atypical meningioma, some of which have already been suggested by preceding studies. Although our analyses suggested multiple anti-tumour mechanisms for these drugs, further in vivo studies are required for validation.

Importance of the study

To our knowledge this is the first study which combines relatively new, yet established computational techniques to identify additional treatments for a difficult to manage cerebral neoplasm. Beyond proposing already approved drug candidates in the management of atypical meningioma the study highlights the promise held by computational techniques in improving our management strategies.

Evaluation of autoantibody signatures in meningioma patients using human proteome arrays

Meningiomas are one of the most common tumors of the Central nervous system (CNS). This study aims to identify the autoantibody biomarkers in meningiomas using high-density human proteome arrays (~17,000 full-length recombinant human proteins). Screening of sera from 15 unaffected healthy individuals, 10 individuals with meningioma grade I and 5 with meningioma grade II was performed. This comprehensive proteomics based investigation revealed the dysregulation of 489 and 104 proteins in grades I and II of meningioma, respectively, along with the enrichment of several signalling pathways, which might play a crucial role in the manifestation of the disease. Autoantibody targets like IGHG4, CRYM, EFCAB2, STAT6, HDAC7A and CCNB1 were significantly dysregulated across both the grades. Further, we compared this to the tissue proteome and gene expression profile from GEO database. Previously reported upregulated proteins from meningioma tissue-based proteomics obtained from high-resolution mass spectrometry demonstrated an aggravated autoimmune response, emphasizing the clinical relevance of these targets. Some of these targets like SELENBP1 were tested for their presence in tumor tissue using immunoblotting. In the light of highly invasive diagnostic modalities employed to diagnose CNS tumors like meningioma, these autoantibody markers offer a minimally invasive diagnostic platform which could be pursued further for clinical translation.

Rac1-Mediated DNA Damage and Inflammation Promote Nf2 Tumorigenesis but Also Limit Cell-Cycle Progression

Merlin encoded by the Nf2 gene is a bona fide tumor suppressor that has been implicated in regulation of both the Hippo-Yap and Rac1-Pak1 pathways. Using genetically engineered murine liver models, we show that co-deletion of Rac1 with Nf2 blocks tumor initiation but paradoxically exacerbates hepatomegaly induced by Nf2 loss, which can be suppressed either by treatment with pro-oxidants or by co-deletion of Yap. Our results suggest that while Yap acts as the central driver of proliferation during Nf2 tumorigenesis, Rac1 primarily functions as an inflammation switch by inducing reactive oxygen species that, on one hand, induce nuclear factor κB signaling and expression of inflammatory cytokines, and on the other activate p53 checkpoint and senescence programs dampening the cyclin D1-pRb-E2F1 pathway. Interestingly, senescence markers are associated with benign NF2 tumors but not with malignant NF2 mutant mesotheliomas, suggesting that senescence may underlie the benign nature of most NF2 tumors.

Molecular Genetics of Intracranial Meningiomas with Emphasis on Canonical Wnt Signalling

Research over the last decade recognized the importance of novel molecular pathways in pathogenesis of intracranial meningiomas. In this review, we focus on human brain tumours meningiomas and the involvement of Wnt signalling pathway genes and proteins in this common brain tumour, describing their known functional effects. Meningiomas originate from the meningeal layers of the brain and the spinal cord. Most meningiomas have benign clinical behaviour and are classified as grade I by World Health Organization (WHO). However, up to 20% histologically classified as atypical (grade II) or anaplastic (grade III) are associated with higher recurrent rate and have overall less favourable clinical outcome. Recently, there is emerging evidence that multiple signalling pathways including Wnt pathway contribute to the formation and growth of meningiomas. In the review we present the synopsis on meningioma histopathology and genetics and discuss our research regarding Wnt in meningioma. Epithelial-to-mesenchymal transition, a process in which Wnt signalling plays an important role, is shortly discussed.

Genetic/molecular alterations of meningiomas and the signaling pathways targeted

Meningiomas are usually considered to be benign central nervous system tumors; however, they show heterogenous clinical, histolopathological and cytogenetic features associated with a variable outcome. In recent years important advances have been achieved in the identification of the genetic/molecular alterations of meningiomas and the signaling pathways involved. Thus, monosomy 22, which is often associated with mutations of the NF2 gene, has emerged as the most frequent alteration of meningiomas; in addition, several other genes (e.g., AKT1, KLF4, TRAF7, SMO) and chromosomes have been found to be recurrently altered often in association with more complex karyotypes and involvement of multiple signaling pathways. Here we review the current knowledge about the most relevant genes involved and the signaling pathways targeted by such alterations. In addition, we summarize those proposals that have been made so far for classification and prognostic stratification of meningiomas based on their genetic/genomic features.

The protein expression profile of meningioma cells is associated with distinct cytogenetic tumour subgroups

AIMS

Limited information exists about the impact of cytogenetic alterations on the protein expression profiles of individual meningioma cells and their association with the clinicohistopathological characteristics of the disease. The aim of this study is to investigate the potential association between the immunophenotypic profile of single meningioma cells and the most relevant features of the tumour.

METHODS

Multiparameter flow cytometry (MFC) was used to evaluate the immunophenotypic profile of tumour cells (n = 51 patients) and the Affymetrix U133A chip was applied for the analysis of the gene expression profile (n = 40) of meningioma samples, cytogenetically characterized by interphase fluorescence in situ hybridization.

RESULTS

Overall, a close association between the pattern of protein expression and the cytogenetic profile of tumour cells was found. Thus, diploid tumours displayed higher levels of expression of the CD55 complement regulatory protein, tumours carrying isolated monosomy 22/del(22q) showed greater levels of bcl2 and PDGFRβ and meningiomas carrying complex karyotypes displayed a greater proliferation index and decreased expression of the CD13 ectoenzyme, the CD9 and CD81 tetraspanins, and the Her2/neu growth factor receptor. From the clinical point of view, higher expression of CD53 and CD44 was associated with a poorer outcome.

CONCLUSIONS

Here we show that the protein expression profile of individual meningioma cells is closely associated with tumour cytogenetics, which may reflect the involvement of different signalling pathways in the distinct cytogenetic subgroups of meningiomas, with specific immunophenotypic profiles also translating into a different tumour clinical behaviour.

Global expression profile in low grade meningiomas and schwannomas shows upregulation of PDGFD, CDH1 and SLIT2 compared to their healthy tissue

Schwannomas and grade I meningiomas are non‑metastatic neoplasms that share the common mutation of gene NF2. They usually appear in neurofibromatosis type 2 patients. Currently, there is no drug treatment available for both tumors, thus the use of wide expression technologies is crucial to identify therapeutic targets. Affymetrix Human Gene 1.0 ST was used to test global gene expression in 22 meningiomas, 31 schwannomas and, as non-tumoral controls, 3 healthy meningeal tissues, 8 non-tumoral nerves and 1 primary Schwann cell culture. A non-stringent P-value cut-off and fold change were used to establish deregulated genes. We identified a subset of genes that were upregulated in meningiomas and schwannomas when compared to their respectively healthy tissues, including PDGFD, CDH1 and SLIT2. Thus, these genes should be thoroughly studied as targets in a possible combined treatment.

Gene expression profile for predicting survival of patients with meningioma

Current staging methods are inadequate for predicting the overall survival of meningioma. DNA microarray technologies improve the understanding of tumour progression. We analysed genome wide expression profiles of 119 meningioma samples from two previous published DNA microarray studies. The Cox proportional hazards regression models were applied to identify overall survival related gene signature. A total of 449 genes (109 upregulated and 340 downregulated) were identified as differentially expressed in meningioma. Among these differentially expressed genes, 37 genes were identified to be related to meningioma overall survival. Our 37-gene signature is closely associated with overall survival among patients with meningioma. This gene expression profile could provide an optimization of the clinical management and development of new therapeutic strategies for meningioma.

An integrative analysis of meningioma tumors reveals the determinant genes and pathways of malignant transformation

Meningiomas are frequent central nervous system neoplasms, which despite their predominant benignity, show sporadically malignant behavior. Type 2 neurofibromatosis and polymorphisms in several genes have been associated with meningioma risk and are probably involved in its pathogenesis. Although GWAS studies have found loci related to meningioma risk, little is known about the factors determining malignant transformation. Thus, this study is aimed to identify the genomic and transcriptomic factors influencing evolution from benignity toward aggressive phenotypes. By applying an integrative bioinformatics pipeline combining public information on a wealth of biological layers of complexity (from genetic polymorphisms to protein interactions), this study identified a module of co-expressed genes highly correlated with tumor stage and statistically linked to several genomic regions (module Quantitative Trait Loci, mQTLs). Ontology analysis of the transcription hub genes identified microtubule-associated cell-cycle processes as key drivers of such network. mQTLs and single nucleotide polymorphisms associated with meningioma stage were replicated in an alternative meningioma cohort, and integration of these results with up-to-date scientific literature and several databases retrieved a list of genes and pathways with a potentially important role in meningioma malignancy. As a result, cytoskeleton and cell-cell adhesion pathways, calcium-channels and glutamate receptors, as well as oxidoreductase and endoplasmic reticulum-associated degradation pathways were found to be the most important and redundant findings associated to meningioma progression. This study presents an integrated view of the pathways involved in meningioma malignant conversion and paves the way for the development of new research lines that will improve our understanding of meningioma biology.

Genetic profiling by single-nucleotide polymorphism-based array analysis defines three distinct subtypes of orbital meningioma

Orbital meningiomas can be classified as primary optic nerve sheath (ON) meningiomas, primary intraorbital ectopic (Ob) meningiomas and spheno-orbital (Sph-Ob) meningiomas based on anatomic site. Single-nucleotide polymorphism (SNP)-based array analysis with the Illumina 300K platform was performed on formalin-fixed, paraffin-embedded tissue from 19 orbital meningiomas (5 ON, 4 Ob and 10 Sph-Ob meningiomas). Tumors were World Health Organization (WHO) grade I except for two grade II meningiomas, and one was NF2-associated. We found genomic alterations in 68% (13 of 19) of orbital meningiomas. Sph-Ob tumors frequently exhibited monosomy 22/22q loss (70%; 7/10) and deletion of chromosome 1p, 6q and 19p (50% each; 5/10). Among genetic alterations, loss of chromosome 1p and 6q were more frequent in clinically progressive tumors. Chromosome 22q loss also was detected in the majority of Ob meningiomas (75%; 3/4) but was infrequent in ON meningiomas (20%; 1/5). In general, Ob tumors had fewer chromosome alterations than Sph-Ob and ON tumors. Unlike Sph-Ob meningiomas, most of the Ob and ON meningiomas did not progress even after incomplete excision, although follow-up was limited in some cases. Our study suggests that ON, Ob and Sph-Ob meningiomas are three molecularly distinct entities. Our results also suggest that molecular subclassification may have prognostic implications.

Masked hypodiploidy in anaplastic meningiomas by duplication of the original clone found in atypical meningiomas: illustration of the evolution of genetic alterations

Meningiomas are common, usually benign neoplasms of the central nervous system. Atypical and anaplastic meningiomas can be aggressive, show more rapid growth, and a greater propensity to recur following resection. General consensus believes that genetic abnormalities leading to anaplastic transformation are present at initial tumor presentation; however, this has not been demonstrated by array-comparative genome hybridization. We confirm the hypothesis by showing the evolution of genetic alterations in the transformation of an atypical meningioma to an anaplastic meningioma. Additionally, we provide potential genes responsible for malignant transformation of meningiomas, which, with further research, may provide diagnostic and therapeutic implications.

Association between inflammatory infiltrates and isolated monosomy 22/del(22q) in meningiomas

Meningiomas contain highly variable levels of infiltrating tissue macrophages (TiMa) and other immune cells. In this study we investigated the potential association between the number and immunophenotype of inflammatory and other immune cells infiltrating the tumor as evaluated by multiparameter flow cytometry, and the clinico-biological, cytogenetic and gene expression profile (GEP) of 75 meningioma patients. Overall, our results showed a close association between the amount and cellular composition of the inflammatory and other immune cell infiltrates and the cytogenetic profile of the tumors. Notably, tumors with isolated monosomy 22/del(22q) showed greater numbers of TiMa, NK cells and (recently)-activated CD69(+) lymphocytes versus meningiomas with diploid and complex karyotypes. In addition, in the former cytogenetic subgroup of meningiomas, tumor-infiltrating TiMa also showed a more activated and functionally mature phenotype, as reflected by a greater fraction of CD69(+), CD63(+), CD16(+) and CD33(+) cells. GEP at the mRNA level showed a unique GEP among meningiomas with an isolated monosomy 22/del(22q) versus all other cases, which consisted of increased expression of genes involved in inflammatory/immune response, associated with an M1 TiMa phenotype. Altogether, these results suggest that loss of expression of specific genes coded in chromosome 22 (e.g. MIF) is closely associated with an increased homing and potentially also anti-tumoral effect of TiMa, which could contribute to explain the better outcome of this specific good-prognosis cytogenetic subgroup of meningiomas.

Immunophenotypic identification and characterization of tumor cells and infiltrating cell populations in meningiomas

Meningiomas are primary tumors of the central nervous system composed of both neoplastic and other infiltrating cells. We determined the cellular composition of 51 meningioma samples by multiparameter flow cytometric (MFC) immunophenotyping and investigated the potential relationship between mRNA and protein expression levels of neoplastic cells. For immunophenotypic, morphologic, and cytogenetic characterization of individual cell populations, a large panel of markers was used together with phagocytic/endocytic functional assays and MFC sorting. Overall, our results revealed coexistence of CD45(-) neoplastic cells and CD45(+) immune infiltrating cells in all meningiomas. Infiltrating cells included tissue macrophages, with an HLA-DR(+)CD14(+)CD45(+)CD68(+)CD16(-/+)CD33(-/+) phenotype and high phagocytic/endocytic activity, and a small proportion of cytotoxic lymphocytes (mostly T CD8(+) and natural killer cells). Tumor cells expressed multiple cell adhesion proteins, tetraspanins, HLA-I/HLA-DR molecules, complement regulatory proteins, cell surface ectoenzymes, and growth factor receptors. Noteworthy, the relationship between mRNA and protein levels was variable, depending on the proteins evaluated and the level of infiltration by immune cells. In summary, our results indicate that MFC immunophenotyping provides a reliable tool for the characterization of the patterns of protein expression of different cell populations coexisting in meningioma samples, with a more accurate measure of gene expression profiles of tumor cells at the functional/protein level than conventional mRNA microarray, independently of the degree of infiltration of the tumor by immune cells.

Delineation of commonly deleted chromosomal regions in meningiomas by high-density single nucleotide polymorphism genotyping arrays

Despite recent advances in the identification of the cytogenetic profiles of meningiomas, a significant group of tumors still show normal karyotypes or few chromosomal changes. The authors analyzed the cytogenetic profile of 50 meningiomas using fluorescence in situ hybridization and high-density (500 K) single nucleotide polymorphism (SNP) arrays. Our results confirm that del(22q) (52%) and del(1p) (16%) (common deleted regions: 22q11.21-22q13.3. and 1p31.2-p36.33) are the most frequent alterations. Additionally, recurrent monosomy 14 (8%), del(6q) (10%), del(7p) (10%), and del(19q) (4%) were observed, while copy number patterns consistent with recurrent chromosomal gains, gene amplification, and copy number neutral loss of heterozygosity (cnLOH) were either absent or rare. Based on their overall SNP profiles, meningiomas could be classified into: (i) diploid cases, (ii) meningiomas with a single chromosomal change [e.g., monosomy 22/del(22q)] and (iii) tumors with ≥2 altered chromosomes. In summary, our results confirm and extend on previous observations showing that the most recurrent chromosomal abnormalities in meningiomas correspond to chromosome losses localized in chromosomes 1, 22 and less frequently in chromosomes 6, 7, 14, and 19, while chromosomal gains and cnLOH are restricted to a small proportion of cases. Finally, a set of cancer-associated candidate genes associated with the TP53, MYC, CASP3, HDAC1, and TERT signaling pathways was identified, in cases with coexisting monosomy 14 and del(1p).

Identification of gene markers associated with aggressive meningioma by filtering across multiple sets of gene expression arrays

Meningiomas are common intracranial tumors, but relatively little is known about the genetic events responsible for their clinical diversity. Although recent genomic studies have provided clues, the genes identified often differ among publications. We used microarray expression profiling to identify genes that are differentially expressed, with at least a 4-fold change, between grade I and grade III meningiomas. We filtered this initial set of potential biomarkers through a second cohort of meningiomas and then verified the remaining genes by quantitative polymerase chain reaction followed by examination using a third microarray expression cohort. Using this approach, we identified 9 overexpressed (TPX2, RRM2, TOP2A, PI3, BIRC5, CDC2, NUSAP1, DLG7, SOX11) and 2 underexpressed (TIMP3, KCNMA1) genes in grade III versus grade I meningiomas. As a further validation step, we analyzed these genes in a fourth cohort and found that patients with grade II meningiomas with high topoisomerase 2-α protein expressions (>5% labeling index) had shorter times to death than patients with low expressions. We believe that this multistep multi-cohort approach provides a robust method for reducing false-positives while generating a list of reproducible candidate genes that are associated with clinically aggressive meningiomas and are suitable for analysis for their potential prognostic value.

Differential expression profiling analyses identifies downregulation of 1p, 6q, and 14q genes and overexpression of 6p histone cluster 1 genes as markers of recurrence in meningiomas

The majority of meningiomas are probably benign but a number of tumors display considerable histological and/or clinical aggressivity, sometimes with unexpectedly high recurrence rates after radical removal. Understanding the potential behavior of these tumors in individual patients is critical for rational therapeutic decision-making. This study aimed to identify gene expression profiles and candidate markers associated with original and recurrent meningiomas. Unsupervised hierarchical clustering of the samples confirmed 2 main groups of meningiomas with distinct clinical behaviors. The gene expression profiling study identified genes and pathways potentially associated with meningioma recurrence, revealing an overall lower level of gene expression. The differential gene expression profiling analyses of original and recurrent meningiomas identified 425 known genes and expressed sequence tags related to meningioma recurrence, with SFRP1 (8p12), TMEM30B (14q23), and CTGF (6q23) showing the most disparate expression. Most of the differentially expressed genes were located at 1p, 6q, and 14q and were underexpressed in recurrences. Loss of such chromosomal regions has previously been associated with a higher risk of meningioma recurrence or malignant progression. Thus, at these locations, we propose the existence of novel candidate genes that could be involved in meningioma recurrence. In addition, the overexpression of genes of histone cluster 1 (6p) in recurrent meningiomas is reported here for the first time. Finally, the altered genes related to meningioma recurrence are involved in pathways such as Notch, TGFβ, and Wnt, as described previously, and in other pathways such as cell cycle, oxidative phosphorylation, PPAR, and PDGF, not related before to meningioma recurrence.

Genomic profiling distinguishes familial multiple and sporadic multiple meningiomas

Background

Meningiomas may occur either as familial tumors in two distinct disorders, familial multiple meningioma and neurofibromatosis 2 (NF2), or sporadically, as either single or multiple tumors in individuals with no family history. Meningiomas in NF2 and approximately 60% of sporadic meningiomas involve inactivation of the NF2 locus, encoding the tumor suppressor merlin on chromosome 22q. This study was undertaken to establish whether genomic profiling could distinguish familial multiple meningiomas from sporadic solitary and sporadic multiple meningiomas.

Methods

We compared 73 meningiomas presenting as sporadic solitary (64), sporadic multiple (5) and familial multiple (4) tumors using genomic profiling by array comparative genomic hybridization (array CGH).

Results

Sporadic solitary meningiomas revealed genomic rearrangements consistent with at least two mechanisms of tumor initiation, as unsupervised cluster analysis readily distinguished tumors with chromosome 22 deletion (associated with loss of the NF2 tumor suppressor) from those without chromosome 22 deletion. Whereas sporadic meningiomas without chromosome 22 loss exhibited fewer chromosomal imbalance events overall, tumors with chromosome 22 deletion further clustered into two major groups that largely, though not perfectly, matched with their benign (WHO Grade I) or advanced (WHO Grades II and III) histological grade, with the latter exhibiting a significantly greater degree of genomic imbalance (P < 0.001). Sporadic multiple meningiomas showed a frequency of genomic imbalance events comparable to the atypical grade solitary tumors. By contrast, familial multiple meningiomas displayed no imbalances, supporting a distinct mechanism for the origin for these tumors.

Conclusion

Genomic profiling can provide an unbiased adjunct to traditional meningioma classification and provides a basis for exploring the different genetic underpinnings of tumor initiation and progression. Most importantly, the striking difference observed between sporadic and familial multiple meningiomas indicates that genomic profiling can provide valuable information for differential diagnosis of subjects with multiple meningiomas and for considering the risk for tumor occurrence in their family members.