Expression data from glioblastoma tissue and normal brain tissue samples (from epilepsy surgery)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE90886 | GEO | 2017/02/10
SECONDARY ACCESSION(S): PRJNA356279
REPOSITORIES: GEO
Similar Datasets
Project description:Mesial temporal lobe epilepsy (mTLE) is a chronic neurological disease characterized by recurrent seizures. The pathogenic mechanisms underlying TLE involve defects in post-transcriptional regulation of gene expression. So far, transcriptome profiles from epileptic tissue have been performed using whole cells, thereby lacking information on RNA localization and function at a subcellular level. In this project, we set out to understand the compartment-specific total RNA profile of human mTLE tissue samples. For this, we had established a protocol to isolate cytoplasmic and nuclear compartments from human hippocampal tissue. Subcellular RNA was isolated from resected hippocampal (HC) and neo-cortical (Cx) tissue from mTLE no hippocampal sclerosis (non-HS) and mTLE HS International League Against Epilepsy (ILAE) Type 1 or mTLE+HS patients and postmortem control tissue. Later, we used total RNA sequencing (RNA-seq) to profile for the distinct RNA localization in mTLE in comparison to postmortem control tissue and identified disease related pathways in individual cell compartments. Here we report the total RNAseq (coding and non-coding) data.
2022-03-31 | GSE186334 | GEO
Project description:A total of 5762.0 proteins were identified in this study, of which 4891.0 proteins contained quantitative information. If a 1.2-fold differential expression change threshold is used and a statistical test t-test p-value < 0.05 is used as the significance threshold, then among the proteins quantified, we found that 95 proteins were up-regulated and 45 proteins were down-regulated in the treatvscontrol comparison group.
2023-05-10 | PXD040967 | Pride
Project description:Gene expression profiling revealed over-representation of a distinct (proneural-like) expression signature in long-term survivors that was linked to IDH1/2 mutation. However, among the IDH1/2-wildtype patients, tumors from long-term survivors did not show distinct gene expression profiles and included proneural, classical and mesenchymal glioblastoma subtypes. We performed genome- and/or transcriptome-wide molecular profiling of primary tumor samples from 70 glioblastoma patients of the German Glioma Network, including 23 longterm survivors with >36 months overall survival (OS), 16 short-term survivors with <12 months OS, and 31 patients with intermediate OS For this study, we screened prospectively recruited patients with a histopathological reference diagnosis of glioblastoma, known KPS at diagnosis, information on extent of resection by early postoperative neuroimaging, available frozen tissue specimens from the initial operation, and documented clinical outcome.
2014-03-27 | E-GEOD-53733 | biostudies-arrayexpress
Project description:Glioblastoma is a grade IV glioma of heterogeneous nature which complicates disease pathophysiology and biomarker research. Thus, the aim of our meta-analysis is to identify long noncoding RNAs (lncRNAs) and protein coding genes (PCGs) that are differentially expressed over different glioblastoma tissue datasets. Small RNA-seq of glioblastoma tissues was also performed to identify differentially expressed microRNAs (miRNAs) relative to paired controls.
2023-01-05 | GSE214252 | GEO
Project description:Human Chromosome 11 brain tissue disease database; alzheimer, epilepsy, and normal.
2022-02-28 | PXD000803 | Pride
Project description:Unveiling the regulatory network controlling natural transformation in lactococci
| PRJNA1076222 | ENA
Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity. Four condition experiment with five samples per condition. The samples include right dentate gyrus from animals with seizures, left dentate gyrus from animals with seizures, right dentate gyrus from animals without seizures, and left dentate gyrus from animals without seizures. A dye swap was included.
2011-02-13 | E-GEOD-27015 | biostudies-arrayexpress
Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity. Four condition experiment with five samples per condition. The samples include right dentate gyrus from animals with seizures, left dentate gyrus from animals with seizures, right dentate gyrus from animals without seizures, and left dentate gyrus from animals without seizures.
2011-02-13 | E-GEOD-27166 | biostudies-arrayexpress
Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity.
2011-02-13 | GSE27166 | GEO
Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity.
2011-02-13 | GSE27015 | GEO