Human meningioma culture
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE55609 | GEO | 2014/03/06
SECONDARY ACCESSION(S): PRJNA240215
REPOSITORIES: GEO
Similar Datasets
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: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:Meningiomas are the most common primary intracranial tumor. However, surgical resection and radiation frequently fail to eliminate high grade tumors, leading to significant morbidity and mortality. Predicting which tumors will recur rapidly is critical to effective treatment strategies. To address the prognostic challenges and dearth of therapeutic targets, we interrogated the enhancer landscape of a diverse cohort of meningiomas. Enhancers robustly stratified meningiomas into three biologically distinct groups and identified a subset of tumors with a poor prognosis, independent of histological grading. Integrating enhancer networks with transcriptional profiles revealed unique lineage transcriptional regulators associated with each subgroup. A strong hormonal epidemiologic association is well-characterized in meningiomas, but mechanistic insight remains lacking. We identified differential hormonal regulators that stratified between subgroups, and implicated progesterone receptor in maintaining the super enhancer network of a subset of tumors. Super enhancers marked critical and druggable dependencies across a panel of meningioma models.
2021-01-01 | GSE139650 | GEO
Project description:Meningiomas are the most common primary intracranial tumor. However, surgical resection and radiation frequently fail to eliminate high grade tumors, leading to significant morbidity and mortality. Predicting which tumors will recur rapidly is critical to effective treatment strategies. To address the prognostic challenges and dearth of therapeutic targets, we interrogated the enhancer landscape of a diverse cohort of meningiomas. Enhancers robustly stratified meningiomas into three biologically distinct groups and identified a subset of tumors with a poor prognosis, independent of histological grading. Integrating enhancer networks with transcriptional profiles revealed unique lineage transcriptional regulators associated with each subgroup. A strong hormonal epidemiologic association is well-characterized in meningiomas, but mechanistic insight remains lacking. We identified differential hormonal regulators that stratified between subgroups, and implicated progesterone receptor in maintaining the super enhancer network of a subset of tumors. Super enhancers marked critical and druggable dependencies across a panel of meningioma models.
2021-01-01 | GSE139651 | GEO
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.
2011-01-02 | GSE19720 | GEO
Project description:Meningiomas are typically considered a benign tumor that can be cured by complete surgical resection; however, a percentage of patients have recurrent disease, even after apparently complete resections. These patients require additional surgeries, radiation therapy, chemotherapy, or a combination of all three. The ability to recognize these patients prior to recurrence would promote earlier use of adjuvant therapy, thus improving overall patient outcome. Unfortunately, identification of meningiomas with this more aggressive phenotype is difficult, and standard histopathological techniques rarely suffice. The identification of genetic and molecular parameters that can help to define these more aggressive tumors would improve prognostication and treatment planning for patients with meningiomas. 1. Establish gene profiles for benign (grade 1) and aggressive (grades 2 and 3) meningiomas. 2. Determine if there are particular expression profiles that can help differentiate between benign and aggressive meningiomas. 3. Determine if there is/are specific gene(s) whose expression is/are altered in benign vs aggressive tumors. 4. Determine if there is a correlation between specific genetic abnormalities in these tumors (as analyzed by fluorescent in situ hybridization; FISH) and gene expression profiles. Our overall hypothesis is that there are molecular and biochemical changes that can be used to identify meningiomas that will have a more aggressive clinical course. Specific Aims 1 and 2: RNA from flash frozen or RNA-later preserved tissue (from all three grades of meningiomas) has been used for RNA isolation using standard protocols. RNA quantity has been determined using a RiboGreen RNA quantitation Kit (Molecular Probes), and RNA quality has been demonstrated using standard formaldehyde gels. These samples will be sent to the NINDS/NIMH microarray consortium for Affymetrix microarray analyses. Data analysis will be done using GeneSpring software (Silicon Genetics, Inc.) with assistance from consortium personnel. Specific Aim 3: Differentially expressed genes identified through microarray analyses will be analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Real time qRT-PCR is a standard technique used in our laboratory for gene expression analysis. Specific Aim 4: FISH analyses of paraffin-embedded tissue has been completed for 77 tumors. We have frozen tissue from a number of these patients. RNA from these samples will be used for microarray analyses (Specific Aims 1-3). The results of Speicifc Aims 1 and 2 will affect how we perform our correlation analyses. This will be done with the assistance of contracted statistical personnel
2008-06-13 | E-GEOD-4780 | biostudies-arrayexpress
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:Meningiomas account for roughly one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system, there remains considerable uncertainty in predicting tumor behavior. Here we analyzed 160 tumors from all three WHO grades (I-III) using clinical, gene expression and sequencing data. Unsupervised clustering analysis identified three molecular groups that reliably predicted clinical severity. These groups did not directly correlate with the WHO grading system, which would classify more than half of the tumors in the most aggressive molecular group as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, resulting in cell cycle activation, and only tumors in this group tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.
2019-11-13 | GSE136661 | GEO
Project description:Cytogenetic profiles of 50 meningiomas using high-density GeneChip Mapping 500K set and Genome-Wide Human SNP 6.0 Array in the tumor tissues and in the peripheral blood of the same patients. A total of two hundred 500k arrays (100 tumor samples and 100 blood samples) and 14 SNP6.0 arrays (7 tumour samples and 7 peripheral blood samples) were studied to explore the most common recurrent chromosomal abnormalities (gains and losses) in meningiomas. 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 abnormalities. Additionally, recurrent monosomy 14 (8%), del(6p) (10%), del(7p) (10%) and del(19p) (6%) were also observed, while copy number variation (CNV) patterns consistent with recurrent chromosome gains, gene amplification was absent or rare. Based on their overall SNP profiles meningiomas could be classified into: i) diploid cases, ii) meningiomas with a single chromosome change (e.g. monosomy 22/del(22q) and iii) tumours with ≥2 altered chromosomes.
2012-11-30 | GSE42624 | GEO
Project description:Cytogenetic profiles of 50 meningiomas using high-density GeneChip Mapping 500K set and Genome-Wide Human SNP 6.0 Array in the tumor tissues and in the peripheral blood of the same patients. A total of two hundred 500k arrays (100 tumor samples and 100 blood samples) and 14 SNP6.0 arrays (7 tumour samples and 7 peripheral blood samples) were studied to explore the most common recurrent chromosomal abnormalities (gains and losses) in meningiomas. 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 abnormalities. Additionally, recurrent monosomy 14 (8%), del(6p) (10%), del(7p) (10%) and del(19p) (6%) were also observed, while copy number variation (CNV) patterns consistent with recurrent chromosome gains, gene amplification was absent or rare. Based on their overall SNP profiles meningiomas could be classified into: i) diploid cases, ii) meningiomas with a single chromosome change (e.g. monosomy 22/del(22q) and iii) tumours with M-bM-^IM-%2 altered chromosomes. 500K SNP mapping set array and Genome-Wide Human SNP 6.0 Array were used to profile 50 meningiomas with matched blood DNA samples. Loss of heterozygosity (LOH) and copy number abnormality (CNA) profiles were derived from each tumour-blood pair. In seven tumors, both types of arrays were assessed.
2012-11-30 | E-GEOD-42624 | biostudies-arrayexpress