Gene expression microarrays were used to compare gene alterations induced by exposure to equitoxic doses of crocidolite asbestos and cristobalite silica in an isolate of normal human bronchial epithelial cells.
Indications for distinct pathogenic mechanisms of asbestos and silica through gene expression profiling of the response of lung epithelial cells.
Specimen partView Samples
To more concretely elucidate the long-term effects of chronic SSRI exposure during adulthood, the long-term consequences of chronic fluoxetine (12 mg/kg) versus vehicle treatment during adulthood (postnatal day (PND) 67-88) on gene expression in the hippocampus were investigated. The study showed that adult chronic fluoxetine exposure causes on the long-term changes in the expression of genes related to, amongst others, myelination Overall design: Comparison of gene expression in hippocampus tissue of fluoxetine and methylcellulose-exposed rats (postnatal day 128). 2 rats pooled per sample, 2 samples per treatment group
Long-term consequences of chronic fluoxetine exposure on the expression of myelination-related genes in the rat hippocampus.
No sample metadata fieldsView Samples
A genetic association between the ANP32A gene and osteoarthritis has been suggested. We compared transcriptome profiles of the articular cartilage and subchondral bone from mice deficient in ANP32A with wild-type mice to get insights into the role of ANP32A in the pathogenesis of ostearthritis.
ANP32A regulates ATM expression and prevents oxidative stress in cartilage, brain, and bone.
Age, Specimen partView Samples
Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histological subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was performed on 26 glioblastomas, 22 oligodendrogliomas and 6 control brain samples. Our results demonstrate that Human Exon arrays can identify subgroups of gliomas based on their histological appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas a subset of which (47% and 33%) were confirmed by RT-PCR. In addition, exon-level expression profiling also identified >700 novel exons. Expression of ~67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon-level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants and can identify novel exons. The splice variants identified by exon-level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets.
Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon expression arrays.
No sample metadata fieldsView Samples
M端ller cells (MCs) play a crucial role in the retina, and cultured MC lines are an important tool with which to study MC function. Transformed MC lines have been widely used; however, the transformation process can also lead to unwanted changes compared to the primary cells from which they were derived. A monoclonal spontaneously immortalized rat M端ller cell line, SIRMu-1, was derived from primary rat MCs and characterized by RNA-sequencing (in addition to immunofluorescence and western blotting) in comparison to primary MCs and the SV40-immortalized MC line, rMC-1. Overall design: RNA-seq was performed on enriched polyA RNA from primary M端ller cells (4 biological replicates of passage numbers 3-4), SIRMu-1 cells (5 biological replicates of passage numbers 6-20, two of which were cultured in the presence of the antibiotic gentamicin and the antifungal amphotericin B to match the culture conditions of the primary MCs), and rMC-1 cells (3 biological replicates of passage numbers 23-26).
RNA sequencing data of cultured primary rat Müller cells, the spontaneously immortalized rat Müller cell line, SIRMu-1, and the SV40-transformed rat Müller cell line, rMC-1.
Specimen part, Cell line, SubjectView Samples
These arrays contain data from the livers of 10 week old L-Pex5 -/- male mice
Carbohydrate metabolism is perturbed in peroxisome-deficient hepatocytes due to mitochondrial dysfunction, AMP-activated protein kinase (AMPK) activation, and peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α) suppression.
Sex, Age, Specimen partView Samples
CHEK2 1100delC is a moderate-risk cancer susceptibility allele that confers a high breast cancer risk in a polygenic setting. Gene expression profiling of CHEK2 1100delC breast cancers may reveal clues to the nature of the polygenic CHEK2 model and its genes involved. Here, we report global gene expression profiles of a cohort of 155 familial breast cancers, including 26 CHEK2 1100delC mutant tumors. A 40-gene CHEK2 signature was defined that significantly associated with CHEK2 1100delC breast cancers. The identification of a CHEK2 gene signature implies an unexpected biological homogeneity among the CHEK2 1100delC breast cancers. In addition, all 26 CHEK2 1100delC tumors classified as luminal intrinsic subtype breast cancers, with 8 luminal A and 18 luminal B tumors. This biological make-up of CHEK2 1100delC breast cancers suggests that a relatively limited number of additional susceptibility alleles are involved in the polygenic CHEK2 model. Identification of these as-yet-unknown susceptibility alleles should be aided by clues from the 40-gene CHEK2 signature.
Gene expression profiling assigns CHEK2 1100delC breast cancers to the luminal intrinsic subtypes.
Specimen partView Samples
In order to identify relevant, molecularly defined subgroups in Multiple Myeloma (MM), gene expression profiling (GEP) was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/ GMMG-HD4 trial using Affymetrix GeneChip U133 plus 2.0 arrays. Hierarchical clustering identified 10 distinct subgroups. Using this dataset as training data, a prognostic signature was built. The dataset consists of 282 CEL files previously used in the hierarchical clustering study of Broyl et al (Blood, 116(14):2543-53, 2010) outlined above. To this set 8 CEL-files/gene expression profiles were added. Using this set of 290 CEL-files, a prognostic signature of 92 genes (EMC-92-genesignature) was generated by supervised principal components analysis combined with simulated annealing (Kuiper et al.).
Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients.
Specimen partView Samples
Microarrays were used to analyze the gene expression in endoscopic-derived intestinal mucosal biopsies from patients with inflammatory bowel disease (IBD) and controls
Strong Upregulation of AIM2 and IFI16 Inflammasomes in the Mucosa of Patients with Active Inflammatory Bowel Disease.
Specimen part, DiseaseView Samples
Context: Despite the well-recognized clinical features due to insufficient or excessive thyroid hormone (TH) levels in humans, it is largely unknown which genes are regulated by TH in human tissues. objective: To study the effect of TH on human gene expression profiles in whole blood, mainly consisting of TRa-expressing cells. Methods: We performed next-generation RNA sequencing on whole blood samples from 8 athyroid patients (4 females) on and after 4 weeks off levothyroxine replacement. Gene expression changes were analyzed through paired differential expression analysis and confirmed in a validation cohort. Weighted gene co-expression network analysis (WGCNA) was applied to identify thyroid state-related networks. Results: We detected 486 differentially expressed (DE) genes (fold-change above 1.5; multiple testing corrected P-value <0.05), of which 76 % were positively and 24 % were negatively regulated. Gene ontology (GO) enrichment analysis revealed that 3 biological processes were significantly overrepresented of which the process translational elongation showed the highest fold enrichment (7.3 fold, P=1.8 x 10-6). Comparative transcriptome analysis revealed significant overlap with DE-genes in muscle samples upon different thyroid state (1.7-fold enrichment; P=0.02). WGCNA analysis independently identified various gene clusters that correlated with thyroid state. Further GO-analysis suggested that thyroid state regulates platelet function. Conclusions: Changes in thyroid state regulate numerous genes in human whole blood, predominantly TRa-expressing leukocytes. In addition, TH may regulate gene expression in platelets. Whole blood samples might potentially be used as a proxy for other TRa-expressing tissues in humans. Overall design: Transcriptome profiling (RNA-Seq) of 8 thyroidectomized human whole blood samples, sequenced first in hypothyroid state and after levothyroxine supplementation sequenced in a hypothyroid (mild thyreotoxic state) state on a Illumina HiSeq 2500 system.
Thyroid State Regulates Gene Expression in Human Whole Blood.
Specimen part, SubjectView Samples