Expression data from different grades (WHO) of astrocytomas (ACM)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE19728 | GEO | 2010/01/05
SECONDARY ACCESSION(S): PRJNA122181
REPOSITORIES: GEO
Similar Datasets
Project description:The aim of the study was to identify significant alterations in genes and molecular functional pathways in comparison with normal and ACM tissue, and detect the marker genes to differentiate the different stage astrocytomas Total RNA was isolated from Seventeen tumor tissue of patients, which included two WHO grade I(T1) and five WHO grade II(T2), III(T3) and IV(T4) samples, and four pooled normal tissue samples. The genome-wide expression analysis was first performed by directly comparing the expression profile of highly enriched different grade astrocytomas and pooled normal tissues, we then applied various data-mining methods to process the 15 different grades tumor tissues sample. Paired T-test and Q-cluster method was performed to explore mark genes validated by qRT-PCR. This study utilized a pathway-specific enrichment analysis of the microarray data and quantified the gene expression difference between astrocytomas tumor and pooled normal tissues. BioCarta and KEGG pathways of the ACM compared to normal tissue were identified through enrichment tests on gene lists obtained using SAM, while GO is organized into hierarchical annotations in the context of normal cellular function, the BioCarta and KEGG database organizes the genes(gen products) into pathway reaction maps and functional complexes, including some disease-specific pathway
2010-01-05 | E-GEOD-19728 | biostudies-arrayexpress
Project description:The aim of the study was to identify significant alterations in genes and molecular functional pathways in comparison with normal and ACM tissue, and detect the marker genes to differentiate the different stage astrocytomas Total RNA was isolated from Seventeen tumor tissue of patients, which included two WHO grade I(T1) and five WHO grade II(T2), III(T3) and IV(T4) samples, and four pooled normal tissue samples. The genome-wide expression analysis was first performed by directly comparing the expression profile of highly enriched different grade astrocytomas and pooled normal tissues, we then applied various data-mining methods to process the 15 different grades tumor tissues sample. Paired T-test and Q-cluster method was performed to explore mark genes validated by qRT-PCR. This study utilized a pathway-specific enrichment analysis of the microarray data and quantified the gene expression difference between astrocytomas tumor and pooled normal tissues. BioCarta and KEGG pathways of the ACM compared to normal tissue were identified through enrichment tests on gene lists obtained using SAM, while GO is organized into hierarchical annotations in the context of normal cellular function, the BioCarta and KEGG database organizes the genes(gen products) into pathway reaction maps and functional complexes, including some disease-specific pathway
| S-ECPF-GEOD-19728 | biostudies-other
Project description:Paediatric low-grade gliomas (LGGs) account for about a third of all brain tumours in children. We conducted a detailed study of DNA methylation to improve our understanding of the biology of pilocytic and diffuse astrocytomas. Comparisons were performed between tumours and normal brain controls from matching location, and between pilocytic and diffuse astrocytomas. Pilocytic astrocytomas were found to have a distinctive signature involving 315 CpG sites, with the majority of the sites (312 CpG sites) hypomethylated in pilocytic astrocytomas. Additionally many of the sites were located within annotated enhancers. The distinct signature in pilocytic astrocytomas was not present in diffuse astrocytomas or in published profiles of other brain tumours and normal brain tissue. On further analysis of the 315 CpG sites, the AP-1 transcription factor complex was predicted to bind within 200bp of a subset of teh 315 differentially methylated CpG sites. We also observed up-regulation of the AP-1 factors, FOS and FOSL1 in pilocytic astrocytomas. Our findings highlight novel epigenetic differences between pilocytic and diffuse astrocytomas, in addition to well-described alterations involving BRAF, MYB and FGFR1.
2016-05-10 | GSE77241 | GEO
Project description:Arrhythmogenic cardiomyopathy (ACM) is a genetic disorder, characterized by ventricular ar-rhythmias, contractile dysfunctions and fibro-adipose replacement of the myocardium. Cardiac mesenchymal stromal cells (CMSC) participate to disease pathogenesis by differentiating towards adipocytes and myofibroblasts. Some altered pathways in ACM are known, but many are yet to be discovered. In order to define changes in the gene expression profiles between ACM- and HC-CMSC, we performed a high throughput RNA-seq on 6 ACM and 6 HC samples. Out of 15031 expressed genes, 529 resulted differentially expressed. Through enrichment and gene network analyses, we identified differentially regulated pathways, some of which never associated with ACM, including mitochondrial functioning and chromatin organization. Functional validations confirmed that ACM-CMSC exhibited a higher amount of active mitochondria and ROS production, a lower proliferation rate and a more pronounced epicardial-to-mesenchymal transition, compared to controls. In conclusion, ACM-CMSC -omics revealed some additional altered molecular pathways, relevant in the disease pathogenesis, which may constitute novel targets for specific therapies.
2024-06-30 | GSE233780 | GEO
Project description:Arrhythmogenic cardiomyopathy (ACM) is a genetic disorder, characterized by ventricular ar-rhythmias, contractile dysfunctions and fibro-adipose replacement of the myocardium. Cardiac mesenchymal stromal cells (CMSC) participate to disease pathogenesis by differentiating towards adipocytes and myofibroblasts. Some altered pathways in ACM are known, but many are yet to be discovered. In order to define changes in the gene expression profiles between ACM- and HC-CMSC, we performed a high throughput Bisulfite-seq on 6 ACM and 6 HC samples. Out of 12466 expressed peaks, 30 resulted differentially expressed. Through enrichment and gene network analyses, we identified differentially regulated pathways, some of which never associated with ACM, including mitochondrial functioning and chromatin organization. Functional validations confirmed that ACM-CMSC exhibited a higher amount of active mitochondria and ROS production, a lower proliferation rate and a more pronounced epicardial-to-mesenchymal transition, compared to controls. In conclusion, ACM-CMSC -omics revealed some additional altered molecular pathways, relevant in the disease pathogenesis, which may constitute novel targets for specific therapies.
2024-06-30 | GSE234183 | GEO
Project description:The goal of this experiment is to identify gene ontology pathways and differentially expressed genes that distinguish mature iPSC-aCM, immature iPSC-aCM, and human atrial tissue derived from the same patient.
2022-04-05 | GSE193856 | GEO
Project description:Analysis of grades II, II and iV pediatric astrocytomas. Results used to straify tumors into molecular subclasses representative of adult tumors. The mesenchymal subtype is associated with high expression of immune response-related genes. Gene expression of grade II, III and IV pediatric astrocytomas, 24 individual tumor samples were profiled
2012-08-24 | E-GEOD-38330 | biostudies-arrayexpress
Project description:DNA copy-number profiling of 66 astrocytomas of WHO °I or °II Keywords: Genetic modification
2007-08-10 | GSE8737 | GEO
Project description:Analysis of grades II, II and iV pediatric astrocytomas. Results used to straify tumors into molecular subclasses representative of adult tumors. The mesenchymal subtype is associated with high expression of immune response-related genes.
2012-08-24 | GSE38330 | GEO
Project description:Astrocytoma is the most common glioma, accounting for half of all primary brain and spinal cord tumors. Late detection and the aggressive nature of high-grade astrocytomas contribute to high mortality rates. Though many studies identify candidate biomarkers using high-throughput transcriptomic profiling to stratify grades and subtypes, few have resulted in clinically actionable results. This shortcoming can be attributed, in part, to pronounced lab effects that reduce signature robustness and varied individual gene expression among patients with the same tumor. We addressed these issues by uniformly preprocessing publicly available transcriptomic data, comprising 306 tumor samples from three astrocytoma grades (Grade 2, 3, and 4) and 30 non-tumor samples (normal brain as control tissues). Utilizing Differential Rank Conservation (DIRAC), a network-based classification approach, we examined the global and individual patterns of network regulation across tumor grades. Additionally, we applied gene-based approaches to identify genes whose expression changed consistently with increasing tumor grade and evaluated their robustness across multiple studies using statistical sampling. Applying DIRAC, we observed a global trend of greater network dysregulation with increasing tumor aggressiveness. Individual networks displaying greater differences in regulation between adjacent grades play well-known roles in calcium/PKC, EGF, and transcription signaling. Interestingly, many of the 90 individual genes found to monotonically increase or decrease with astrocytoma grade are implicated in cancer-affected processes such as calcium signaling, mitochondrial metabolism, and apoptosis. The fact that specific genes monotonically increase or decrease with increasing astrocytoma grade may reflect shared oncogenic mechanisms among phenotypically similar tumors. This work presents statistically significant results that enable better characterization of different human astrocytoma grades and hopefully can contribute towards improvements in diagnosis and therapy choices. Our results also identify a number of testable hypotheses relating to astrocytoma etiology that may prove helpful in developing much-needed biomarkers for earlier disease detection.
| S-EPMC3795736 | biostudies-literature