E-MEXP-2351
Ontology highlight
ABSTRACT:
PROVIDER: E-MEXP-2351 | ExpressionAtlas | 2014-07-03
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:Gene expression profiling in human glial brain tumors
| PRJNA91477 | ENA
Project description:Transcription profiling by array of mouse male retinas to investigate IGF-I-induced chronic gliosis and retinal stress IGF-I exert multiple effects in different retinal cell populations in both physiological and pathological conditions. Transgenic mice overexpressing IGF-I in the retina showed impaired electroretinographic responses at 6-7 months of age that worsen with age. This retinal neuronal dysfunction was correlated with the loss of rod photoreceptors, bipolar, ganglion and amacrines cells. Neuronal alterations were preceded by the overexpression of retinal stress markers, acute phase proteins and gliosis-related genes. IGF-I overexpression leads to chronic gliosis and microgliosis in TgIGF-I retinas, with mild oxidative stress, impaired recycling of glutamate and defective potassium buffering. These impaired supportive functions can contribute to neurodegeneration in TgIGF-I retinas, together with the increased production of pro-inflammatory cytokines, potential mediators of neuronal death.
2013-04-30 | GSE46246 | GEO
Project description:<p>During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered <i>SOX2<sup>Cit/+</sup></i> and <i>DCX<sup>Cit/Y</sup></i> hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially be generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development.</p>
| phs001205 | dbGaP
Project description:Expression data from human brain tumors and human normal brain
| PRJNA216955 | ENA
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:<p>Alterations in cell metabolism, including changes in lipid composition occurring during malignancy, are well characterized for various tumor types. However, a significant part of studies that deal with brain tumors have been performed using cell cultures and animal models. Here, we present a dataset of 124 high-resolution negative ionization mode lipid profiles of human brain tumors resected during neurosurgery. The dataset is supplemented with 38 non-tumor pathological brain tissue samples resected during elective surgery. The change in lipid composition alterations of brain tumors enables the possibility of discriminating between malignant and healthy tissues with the implementation of ambient mass spectrometry. On the other hand, the collection of clinical samples allows the comparison of the metabolism alteration patterns in animal models or in vitro models with natural tumor samples ex vivo. The presented dataset is intended to be a data sample for bioinformaticians to test various data analysis techniques with ambient mass spectrometry profiles, or to be a source of clinically relevant data for lipidomic research in oncology.</p>
2021-11-18 | MTBLS1558 | MetaboLights
Project description:Blood-brain barrier alterations in human brain tumors revealed by genome-wide transcriptomic profiling
| PRJNA670696 | ENA
Project description:miRNA profiling by array of astrocytic tumors
| PRJNA577098 | ENA