Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1203745 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
| 2612481 | ecrin-mdr-crc
Project description:In the current work, we present the first proteogenomic dataset of GBM clinical samples to date. We have assembled a cohort of 87 GBM patients of varying survival rates and performed MS-based proteomics analysis as well as RNA-seq in order to identify the molecular differences associated with survival and examine the contribution of each layer to GBM landscape. We show that each layer alone only partially reflects patient survival, but RNA-protein integration identifies clear patterns of layer-specific and layer-common processes specifically contributing to either short-term or long-term survival of patients. Furthermore, we compare our data to published single-cell RNA-seq of GBM tumors and evaluate the RNA-protein variability within single-cell based tumor subpopulations. We found that while all signatures of the four subpopulations tend to have high RNA-protein correlation, each signature is associated differently with survival. Altogether, these results highlight the potential of proteogenomics to further stratify heterogeneity in GBM tumors and identify processes contributing to poorer survival.
2021-04-16 | PXD018024 | Pride
Project description:Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across primary GBM biopsies, normal brain tissues, and cell line counterparts. Analysis of differentially regulated enhancers, especially super-enhancers between GBM and normal brain tissues, as well as among GBM samples with matched RNA-sequencing data, uncovered unrecognized layers of oncogenic core transcriptional dependency and inter-tumor heterogeneity. Moreover, we demonstrate the functional relevance of leading candidates of super-enhancer-driven transcriptional factors, long non-coding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, our integrative study provides clinically relevant insights into GBM molecular classification, pathogenesis, and therapeutic innovations.
2021-05-05 | GSE145644 | GEO
Project description:Glioblastoma Multiforme (GBM) is the most deadly brain tumor, and currently lacks effective treatment options. Brain tumor initiating cells (BTICs) and orthotopic xenografts are widely used in investigating GBM biology and new therapies for this aggressive disease. However, the genomic characteristics and molecular resemblance of these models to GBM tumors remain undetermined. We used massively parallel sequencing technology to decode the genomes and transcriptomes of BTICs and xenografts and their matched tumors in order to delineate the potential impacts of the distinct growth environments. Using data generated from whole‐genome sequencing of 201 samples and RNA sequencing of 118 samples, we showed that typical GBM genomic driver alterations found in the tumors were retained in BTICs and xenografts. In contrast, gene expression and methylation profiles indicated higher levels of divergence, likely due to the different growth environment for each sample type. These findings suggest that a comprehensive genomic understanding of in vitro and in vivo GBM model systems is crucial for interpreting data from drug‐screens, and can help control for biases introduced by cell culture conditions and the microenvironment in mouse models.
2019-03-22 | GSE128654 | GEO
Project description:Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across primary GBM biopsies, normal brain tissues, and cell line counterparts. Analysis of differentially regulated enhancers, especially super-enhancers between GBM and normal brain tissues, as well as among GBM samples with matched RNA-sequencing data, uncovered unrecognized layers of oncogenic core transcriptional dependency and inter-tumor heterogeneity. Moreover, we demonstrate the functional relevance of leading candidates of super-enhancer-driven transcriptional factors, long non-coding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, our integrative study provides clinically relevant insights into GBM molecular classification, pathogenesis, and therapeutic innovations.
2021-05-05 | GSE145645 | GEO
Project description:To investigate the role of mitochondrial metabolic pathways in glioma radioresistance, we established the radioresistant (RR) glioblastoma (GBM) cells in vitro and collected 2 self-pairs of primary and recurrent GBM samples. We then performed gene expression profiling analysis using data obtained from RNA-seq of GBM cells and tissue samples.
2023-06-01 | GSE206917 | GEO
Project description:GBM samples (FFPE tissue) obtained from patients treated in clinical trials according to pre-specified clinical criteria (Nordic, n=116).
2022-03-31 | GSE195684 | GEO
Project description:<p>Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties. We also identified enhancers and their associated transcription factors that regulate genes characteristic of each known GBM subtype, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.</p>
| phs001646 | dbGaP
Project description:Epidermal Growth Factor Receptor (EGFR) gene amplification and mutations are the most common oncogenic events in Glioblastoma (GBM), but the mechanisms by which they promote aggressive tumor growth are not well understood. Here, through integrated epigenome and transcriptome analyses of cell lines, genotyped clinical samples and TCGA data, we show that EGFR mutations remodel the activated enhancer landscape of GBM, promoting tumorigenesis through a SOX9 and FOXG1-dependent transcriptional regulatory network in vitro and in vivo. The most common EGFR mutation, EGFRvIII, sensitizes GBM cells to the BET-bromodomain inhibitor JQ1 in a SOX9, FOXG1-dependent manner. These results identify the role of transcriptional/epigenetic remodeling in EGFR-dependent pathogenesis and suggest a mechanistic basis for epigenetic therapy. ChIP-Seq for H3K27ac, H3K4me1, and H3K4me3, and RNA-seq for Glioblastoma (GBM) cells and/or tissues with or without EGFRvIII mutation.
2015-09-14 | E-GEOD-72468 | biostudies-arrayexpress
Project description:Genome-wide DNA methylation and trancription profiling of different subtypes in GBM (TCGA) and glioma stem cells (GSCs) were carried out using Illumina BeadChip HumanMethylation 450K array (450K array) to analyse over 485K CpG sites accross each samples. 450K array data for 94 GBM samples comprising 4 different subtypes i.e. Proneural (PN), Mesenchymal (MES), Classical (CL) and Neural (N) were used for GBM analysis. Similarly, 450K array for 23 GSCs and 1NHA, RNA seq for 29 GSCs and affimetrix microarray gene expression array for 12 GSCs were used for GBM data analyses.
2017-11-22 | GSE90498 | GEO