Anaplastic Meningioma WGS X10
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ABSTRACT:
PROVIDER: EGAS00001000859 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Genomic profiling of anaplastic meningioma can inform prognostic gene level alterations in lower-grade meningiomas, potentially reflecting evolution of anaplastic meningioma from lowergrade precursor tumours. Larger scale studies in paired primary and recurrent meningiomas are warranted to unravel the evolutionary path to anaplastic meningiomas and prognostic genomic alterations in detail
2021-05-04 | GSE173825 | GEO
Project description:Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.
| EGAD00001001267 | EGA
Project description:Meningiomas are common brain tumors that are classified into three World Health Organization grades (Grade I: benign, Grade II: atypical and Grade III: malignant) and are molecularly ill-defined tumors. The purpose of this study was identify microRNA (miRNA) molecular signatures unique to the different grades of meningiomas correlating them to prognosis. We have used a miRNA expression microarray to show that meningiomas of all three grades fall into two main molecular groups designated “benign” and “malignant” meningiomas. While all typical meningiomas fall into the benign group and all anaplastic meningiomas fall into the malignant group, atypical meningiomas distribute into either one of these groups. We have identified a miRNA signature that distinguishes benign meningiomas from malignant meningiomas. We studied the gene expression profiles of 340 mammalian miRNAs in 37 primary meningioma tumors by means of DNA microarrays.
2011-01-02 | E-GEOD-19720 | biostudies-arrayexpress
Project description:Comparison of the gene expression profiles with meningiomas of different grading. 24 primary meningioma cultures from surgical specimen were maintained to primary meningioma cultures.
2014-03-06 | E-GEOD-55609 | biostudies-arrayexpress
Project description:Multiple stereotatically separate sites from human meningioma were processed for methlyation profiling Meningiomas are the most common primary intracranial tumors, but the molecular drivers of meningioma tumorigenesis are poorly understood. We hypothesized that investigating intratumor heterogeneity in meningiomas would elucidate biologic drivers and reveal new targets for molecular therapy. To test this hypothesis, we performed multiplatform molecular profiling of 86 spatially-distinct samples from 13 human meningiomas. Our data reveal that regional alterations in chromosome structure underlie clonal transcriptomic, epigenomic, and histopathologic signatures in meningioma. Stereotactic co-registration of sample coordinates to preoperative magnetic resonance images further demonstrated that high apparent diffusion coefficient (ADC) distinguished meningioma regions with proliferating cells enriched for developmental gene expression programs. To understand the function of these genes in meningioma, we developed a human cerebral organoid model of meningioma and validated the high ADC marker genes CDH2 and PTPRZ1 as potential targets for meningioma therapy using live imaging, single cell RNA sequencing, CRISPR interference, and pharmacology.
2020-06-17 | GSE151067 | GEO
Project description:Background: Meningiomas account for about 27% of primary brain tumors, making them one of the most common brain tumor. They are most common in people between the ages of 40 and 70 and are more common in women than in men. Most meningiomas (90%) are categorized as benign tumors, with the remaining 10% being atypical or malignant. Multiple classifications exist today, but the most commonly used is the World Health Organization’s (WHO) which classifies meningiomas into three histological grades: grade I (benign), grade II (atypical), and grade III (anaplastic) in accordance with the clinical prognosis. Most of these subtypes behave similarly, however anaplastics are the most aggressive. The ability to distinguish benign from atypical and anaplastic tumors is important because of its impact on treatment decisions. A molecular based classification system has the likelihood of being a better prognostic indicator and is useful for identifying alterations in pathways and networks that drive tumor progression and growth. The information obtained can potentially be translated into more effective and less toxic targeted therapies. We tested a method for genome wide expression profiling of formalin-fixed, paraffin-embedded tissues. We applied the method to the analysis of the clinical outcome of meningioma tumor. Materials and Methods: The training set consisted of tissue samples from 63 patients who were consecutively treated with surgery for meningioma between 1990 and 2005. For each patient data on clinical outcomes and formalin-fixed, paraffin-embedded blocks of tumor were available. The validation set included tissue samples from 189 patients with meningioma who consecutively underwent surgery between 1992 and 2006. We used a custom 60-mer amino modified oligo- array, containing 912 probes, a lot of which specific for genes commonly altered in cancer. Functional annotation was performed by means of gene set enrichment analysis (GSEA, www. broad.mit.edu/gsea/). Survival analyses were performed with the use of the log-rank test and Cox regression modeling. All analyses were performed with the use of GenePattern. Results: We investigated whether gene-expression profiles of meningioma tumors were associated with the clinical outcome. Using a standard leaveone- out cross-validation procedure, we found the meningioma signature to be significantly correlated with survival (P = 0.0001). The survival correlated signature contained 219 genes and was tested in the validation set. Conclusion: These results support the validity of the survival signature and highlight the potential role of tumoral meningioma tissue in predicting the outcome for patients with meningioma tumors.
2011-05-11 | GSE16156 | GEO
Project description:Background: Meningiomas account for about 27% of primary brain tumors, making them one of the most common brain tumor. They are most common in people between the ages of 40 and 70 and are more common in women than in men. Most meningiomas (90%) are categorized as benign tumors, with the remaining 10% being atypical or malignant. Multiple classifications exist today, but the most commonly used is the World Health Organization’s (WHO) which classifies meningiomas into three histological grades: grade I (benign), grade II (atypical), and grade III (anaplastic) in accordance with the clinical prognosis. Most of these subtypes behave similarly, however anaplastics are the most aggressive. The ability to distinguish benign from atypical and anaplastic tumors is important because of its impact on treatment decisions. A molecular based classification system has the likelihood of being a better prognostic indicator and is useful for identifying alterations in pathways and networks that drive tumor progression and growth. The information obtained can potentially be translated into more effective and less toxic targeted therapies. We tested a method for genome wide expression profiling of formalin-fixed, paraffin-embedded tissues. We applied the method to the analysis of the clinical outcome of meningioma tumor. Materials and Methods: The training set consisted of tissue samples from 63 patients who were consecutively treated with surgery for meningioma between 1990 and 2005. For each patient data on clinical outcomes and formalin-fixed, paraffin-embedded blocks of tumor were available. The validation set included tissue samples from 189 patients with meningioma who consecutively underwent surgery between 1992 and 2006. We used a custom 60-mer amino modified oligo- array, containing 912 probes, a lot of which specific for genes commonly altered in cancer. Functional annotation was performed by means of gene set enrichment analysis (GSEA, www. broad.mit.edu/gsea/). Survival analyses were performed with the use of the log-rank test and Cox regression modeling. All analyses were performed with the use of GenePattern. Results: We investigated whether gene-expression profiles of meningioma tumors were associated with the clinical outcome. Using a standard leaveone- out cross-validation procedure, we found the meningioma signature to be significantly correlated with survival (P = 0.0001). The survival correlated signature contained 219 genes and was tested in the validation set. Conclusion: These results support the validity of the survival signature and highlight the potential role of tumoral meningioma tissue in predicting the outcome for patients with meningioma tumors.
2011-05-11 | GSE16153 | GEO
Project description:Although meningiomas are one of the most frequent primary intracranial tumors, there are only a few studies dealing with gene regulation processes in meningiomas. MiRNAs are key regulators of gene expression and regulation and miRNA profiles offer themselves as biomarkers for cancer development and progression. To investigate the role of miRNAs during meningioma growth and progression, we compared expression of 1205 miRNAs in 55 meningioma samples of different tumor grades and histological subtypes. We were able to classify histological subtypes in WHO grade I meningiomas with up to 97% accuracy (meningothelial versus fibroblastic) and different WHO grades with up to 93% accuracy (WHO I versus WHO III). We found significant downregulation of miRNAs on chromosome 1p36 and within two large miRNA clusters on 14q32 in high grade meningiomas, two regions that are yet associated with meningioma progression. We also identified several miRNAs associated with epithelial to mesenchymal transition differentially expressed in meningothelial meningioma compared to fibroblastic meningioma. Combined, our data show that meningiomas of different WHO grades and histological subtypes show a specific miRNA expression profile. Some individual miRNAs can also serve as potential biomarkers for meningioma progression.
2014-12-31 | GSE50641 | GEO
Project description:Global proteomic profiling of meningiomas using LFQ approach to identify biomarkers in meningioma patients
2020-08-27 | PXD014823 | Pride
Project description:Purpose: In this study, we try to investigate the possible signaling pathways involved in the tumorigenesis of fibroblastic and anaplastic meningiomas. We also attempt to investigate EGFL6 gene expression in brain arachnoidal tissues and various tumors and to measure EGFL6 levels in serum samples from healthy people and patients with various tumors by using ELISA. Experimental Design: Differential gene expression profiles between meningiomas and brain arachnoidal tissues were established by using Affymetrix GeneChip Human U133 Plus 2.0 Array. KEGG pathway analysis was performed to identify potential gene pathways that may be involved in the pathogenesis of meningiomas. Quantitative real-time PCR (qRT-PCR) was performed to validate the differentially expressed genes in the KEGG pathways. EGFL6 mRNA levels were also determined in brain arachnoidal tissues, meningiomas, and other tumors by qRT-PCR. EGFL6 levels were measured in serum samples from healthy people and patients with various tumors by using ELISA. Results: Fibroblastic meningioma exhibited upregulated PI3K/Akt and TGFβ signaling pathways, and accelerated G1/S progression cell cycle. KEGG analysis also demonstrated that focal adhesion and ECM-receptor interaction pathways were activated in anaplastic meningioma. Benign meningiomas had significantly higher levels of EGFL6 mRNA than brain arachnoidal tissues and atypical and anaplastic meningiomas (P<0.001). EGFL6 gene was also highly expressed in ovarian cancer, but expressed lowly in all other investigated tumors. EGFL6 was hardly detectable in serum samples of healthy people. The mean serum EGFL6 concentration was 675, 118, and 126 pg/ml in patients with benign, atypical, and anaplastic meningiomas respectively. Patients with ovarian cancers also had high serum EGFL6 levels (mean concentration: 617 pg/ml). Patients with all other investigated tumors, however, had low levels of serum EGFL6 with mean concentration less than 240 pg/ml. Conclusion: We proposed that deregulation of cell cycle and PI3K/Akt pathways might play important roles in the tumorigenesis of fibroblastic meningioma. It was also suggested that the activated integrin-mediated signaling pathways were involved in the pathogenesis of anaplastic meningioma. We presented evidence that EGFL6 might serve as a novel serum biomarker for benign meningioma and ovarian cancer. It was also suggested that EGFL6 could help discriminate benignancy or malignancy of meningiomas before surgery or at early time points. Differential gene expression profiles between meningiomas and brain arachnoidal tissues were established by using Affymetrix GeneChip Human U133 Plus 2.0 Array. KEGG pathway analysis was performed to identify potential gene pathways that may be involved in the pathogenesis of meningiomas. Quantitative real-time PCR (qRT-PCR) was performed to validate the differentially expressed genes in the KEGG pathways. EGFL6 mRNA levels were also determined in brain arachnoidal tissues, meningiomas, and other tumors by qRT-PCR. EGFL6 levels were measured in serum samples from healthy people and patients with various tumors by using ELISA.
2013-01-01 | E-GEOD-32197 | biostudies-arrayexpress