Ontology highlight
ABSTRACT:
PROVIDER: PRJNA528564 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.
2021-09-30 | GSE184941 | GEO
Project description:Migrated from 1.6 id: 1015897590491013 GEDP id: 760 In current clinical practice, histology-based grading of diffuse infiltrative gliomas is the best predictor of patient survival time. Yet histology provides little insight into the underlying biology of gliomas and is limited in its ability to identify and guide new molecularly targeted therapies. We have performed large-scale gene expression analysis using the Affymetrix HG U133 oligonucleotide arrays on 85 diffuse infiltrating gliomas of all histologic types to assess whether a gene expression-based, histology-independent classifier is predictive of survival and to determine whether gene expression signatures provide insight into the biology of gliomas. We found that gene expression-based grouping of tumors is a more powerful survival predictor than histologic grade or age. The poor prognosis samples could be grouped into three different poor prognosis groups, each with distinct molecular signatures. We further describe a list of 44 genes whose expression patterns reliably classify gliomas into previously unrecognized biological and prognostic groups: these genes are outstanding candidates for use in histology-independent classification of high-grade gliomas. The ability of the large scale and 44 gene set expression signatures to group tumors into strong survival groups was validated with an additional external and independent data set from another institution composed of 50 additional gliomas. This demonstrates that large-scale gene expression analysis and subset analysis of gliomas reveals unrecognized heterogeneity of tumors and is efficient at selecting prognosis-related gene expression differences which are able to be applied across institutions. nelso-00262 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A, HG-U133B Organism: Homo sapiens (ncbitax) Material Types: total RNA, synthetic_RNA, organism_part, whole_organism Disease States: Glioma, Glioblastoma, Oligodendroglial Tumor, astrocytomas
2016-06-14 | E-GEOD-83294 | biostudies-arrayexpress
Project description:Glioblastoma (GBM) is the most frequent and most aggressive form of diffuse glioma. The prognosis is very poor, with a median overall survival of 15 months after maximum safe resection and radiochemotherapy.GBM is one of the most genetically unstable cancers. It is characterized by numerous chromosome (chr) copy number alterations (CNA), such as chr 7 gain, chr 9p loss, and chr 10 loss, along with CDKN2A homozygous deletion (chr 9p21) and EGFR amplification (chr 7p11).Chromosome instability (CIN) may be the cause or the consequence of GBM development. In high-grade diffuse gliomas (HGG), CIN may initiate tumorigenesis. To identify recurrent genomic abnormalities in IDH WT glioblastomas, SNP arrays (Illumina 850K CytoSNP) were analyzed for 123 IDH WT GBM cases.
2018-02-27 | E-MTAB-6371 | biostudies-arrayexpress
Project description:IDH and TP53 mutant gliomas are high recurrent tumor, and thus we aimed to detect malignant and recurent factors in this genetic type of gliomas
2017-09-01 | GSE94652 | GEO
Project description:Pediatric low-grade gliomas (PLGGs) are among the most common solid tumors in children but apart from BRAF mutations or duplications in specific subclasses, few genetic driver events are known. Diffuse PLGGs comprise a set of uncommon subtypes that exhibit invasive growth and are therefore especially challenging clinically. These tumors are particularly poorly understood. We performed high-resolution copy-number analysis of 44 diffuse PLGGs to identify recurrent alterations. Diffuse PLGGs exhibited fewer such alterations than adult low-grade gliomas, but we identified several significantly recurrent events. The most significant event, 8q13.1 gains, were observed in 28% of diffuse astrocytomas grade II (DA2s) and resulted in partial duplication of the transcription factor MYBL1 with truncation of its C-terminal negative-regulatory domain. A similar recurrent deletion-truncation breakpoint was identified in two angiocentric gliomas in the related gene MYB on 6q23.3. Whole-genome sequencing of a MYBL1-rearranged DA2 demonstrated MYBL1 tandem duplication, and few other events. Two novel, truncated MYBL1 transcripts identified in this tumor induced anchorage-independent growth when expressed in 3T3 cells and tumor formation in nude mice. Truncated transcripts were also expressed in two additional tumors with MYBL1 partial duplication. Our results define clinically relevant molecular subclasses of diffuse PLGGs and highlight a potential role for the MYB family in the biology of low-grade gliomas.
2013-04-23 | GSE45843 | GEO
Project description:Here, we report defining molecular signatures of immune-suppressive and inflammatory immune cells in human gliomas. We identified nine robust macrophage subtypes with distinct molecular signatures, each of which predicted good or poor survival for glioma patients. Our analysis of signature genes associated with immune suppressive macrophages, underscored S100A4 as a strong candidate for in vivo validation.
2021-12-15 | GSE182109 | GEO
Project description:Migrated from 1.6 id: 1015897590491013 GEDP id: 760 In current clinical practice, histology-based grading of diffuse infiltrative gliomas is the best predictor of patient survival time. Yet histology provides little insight into the underlying biology of gliomas and is limited in its ability to identify and guide new molecularly targeted therapies. We have performed large-scale gene expression analysis using the Affymetrix HG U133 oligonucleotide arrays on 85 diffuse infiltrating gliomas of all histologic types to assess whether a gene expression-based, histology-independent classifier is predictive of survival and to determine whether gene expression signatures provide insight into the biology of gliomas. We found that gene expression-based grouping of tumors is a more powerful survival predictor than histologic grade or age. The poor prognosis samples could be grouped into three different poor prognosis groups, each with distinct molecular signatures. We further describe a list of 44 genes whose expression patterns reliably classify gliomas into previously unrecognized biological and prognostic groups: these genes are outstanding candidates for use in histology-independent classification of high-grade gliomas. The ability of the large scale and 44 gene set expression signatures to group tumors into strong survival groups was validated with an additional external and independent data set from another institution composed of 50 additional gliomas. This demonstrates that large-scale gene expression analysis and subset analysis of gliomas reveals unrecognized heterogeneity of tumors and is efficient at selecting prognosis-related gene expression differences which are able to be applied across institutions.
2016-06-14 | GSE83294 | GEO
Project description:Glioblastoma (GBM) is the most aggressive cancer in brain and contains a high mortality ratedue to lack of effective treatment strategy. Molecular mechanisms of GBM characteristic invasive growth are urgently need to improve the poor prognosis. Via single nuclear-sequences of primary and recurrent GBM samples, level of the M3 muscarinic acetylcholine receptor (CHRM3) was significantly higher in recurrent samples. Moreover, immunohistochemical staining of an array of glioma samples showed that high levels of CHRM3 is correlated to poor prognosis of glioma, consistent with The Cancer Genome Atlas (TCGA) database. Knockdown of CHRM3 retarded glioma cell growth and invasion. In vivo assay of orthotopic glioma animal model indicated that inhibition of CHRM3 significantly suppressed glioma progression with prolonged survival time. Transcriptome analysis revealed that CHRM3 knockdown significantly reduced array of classic factors involved in cancer invasive growth including MMP1/MMP3/MMP10/MMP12 and CXCL1/CXCL5/CXCL8. Taken together, our study identified that CHRM3 is a new and important factor of GBM progression via regulation of multiple oncogenic genes and these results provide a new biomarker for prognosis and therapy of GBM patients.
2022-12-10 | GSE220083 | GEO
Project description:Glioblastoma is the deadliest brain tumor with median survival of 15 months due to diffusive growth and lack of efficient therapy. Recurrent mutations in genes coding for isocitrate dehydrogenases (IDH) 1 or 2 cause to a change in function of the enzymes, resulting in production of 2-hydroxyglutarate, which leads to DNA hypermethylation phenotype, affecting transcription activators/repressors binding to DNA and gene expression. REST is a canonical repressor of neuronal genes in non-neuronal cells, whose levels differ between IDH wt and mut gliomas and whose expression levels correlate with the patients’ survival probability.
2022-04-15 | GSE174308 | GEO