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Homo sapiens
3 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
Human intervention study with two doses of iron (as ferrous gluconate via intestinal perfusion) to study the effect on genome-wide gene expression in the small intestine, in order to obtain detailed information about intestinal transcriptomics in vivo.
Publication Title
Gene expression in human small intestinal mucosa in vivo is mediated by iron-induced oxidative stress.
Sample Metadata Fields
Sex, Disease, Disease stage, Subject
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SRP158719- Homo sapiens
- 6 Downloadable Samples
Illumina HiSeq 3000
Description
The goal of this study was to identify transcriptomic differences in A549 lung cancer cell line following knockout of the RPA1 gene. A549 cells, and many lung tumors, carry constitutive NRF2 activation. Understanding how RPA1 modulates transcription, particularly NRF2-mediated transcription, is relevant for future cancer therapeutics.
Publication Title
No associated publication
Sample Metadata Fields
Sex, Specimen part, Cell line
View Samples- Homo sapiens
- 32 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Intestinal perfusion of a 40-cm segment of the small intestine in 8 healthy volunteers. 2 test days, overnight fast. Gastroduodenoscopy for tissue sampling and positioning of perfusion catheter. Continuous injection of 0.055 M glutamine (10 ml/min) in saline at 10 cm distally from the pylorus for 4 h or continuous injection of 0.055 M glucose in saline. After the injection a second gastroduodenoscopy takes place for tissue sampling. In total we have 4 samples per individual (placebo-before; placebo-after; glutamine-before; and glutamine-after injection.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Disease, Subject, Compound, Time
View Samples- Homo sapiens
- 27 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Left ventricular mass (LVM) and cardiac gene expression are complex traits regulated by factors both intrinsic and extrinsic to the heart. To dissect the major determinants of LVM, we combined expression quantitative trait locus1 and quantitative trait transcript (QTT) analyses of the cardiac transcriptome in the rat. Using these methods and in vitro functional assays, we identified osteoglycin (Ogn) as a major candidate regulator of rat LVM, with increased Ogn protein expression associated with elevated LVM. We also applied genome-wide QTT analysis to the human heart and observed that, out of 22,000 transcripts, OGN transcript abundance had the highest correlation with LVM. We further confirmed a role for Ogn in the in vivo regulation of LVM in Ogn knockout mice. Taken together, these data implicate Ogn as a key regulator of LVM in rats, mice and humans, and suggest that Ogn modifies the hypertrophic response to extrinsic factors such as hypertension and aortic stenosis.
Publication Title
Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)
Description
To assess a potential role of transcription factor CREM in the long-term detrimental effects of beta1-adrenoceptor overexpression, four mouse lines were generated and studied: wild-type mice (WT), Crem-normal beta1AR-transgenic mice (beta1ARTG), Crem-deficient non-transgenic mice (Crem-/-) and Crem-deficient beta1AR-transgenic mice (beta1ARTG/Crem-/-). We focused on genes up- or down-regulated in transgenic mice due to the lacking of CREM (beta1ARTG/Crem-/- vs. beta1ARTG).
Publication Title
No associated publication
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Danio rerio
- 5 Downloadable Samples
- Affymetrix Zebrafish Genome Array (zebrafish)
Description
Zebrafish is an ideal model for the toxicity studies on medicines and environmental genetic toxicants.Different development defects were observed in zebrafish embryos exposed to -ray and heavy ion (carbon or iron) irradiation
Publication Title
No associated publication
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 560 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. The transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12h, 24h and 48h were used for the selection of gene-sets that can discriminate between in vivo genotoxins (GTX) and in vivo non-genotoxins (NGTX). By combining publicly available results for these chemicals from standard in vitro genotoxicity studies with transcriptomics, we developed several prediction models. These models were validated by means of an additional set of 28 chemicals.
Publication Title
A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo.
Sample Metadata Fields
Cell line, Time
View Samples- Mus musculus
- 177 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302), miRCURY LNA microRNA Array, 5th and 7th generation combined - hsa, mmu & rno (miRBase 19.0)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.
Sample Metadata Fields
Specimen part, Compound
View Samples- Mus musculus
- 177 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses.
Publication Title
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.
Sample Metadata Fields
Specimen part, Compound
View Samples- Homo sapiens
- 135 Downloadable Samples
- Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)
Description
The transcriptomic changes induced in the human liver cell line HepG2 by Azathriopine (250M, Sigma-Aldrich), Furan (2mM, Sigma-Aldrich), Tetradecanoyl phorbol acetate (500nM, Sigma-Aldrich), Tetrachloroethylene (2mM, Sigma-Aldrich), Diazinon (250M, Sigma-Aldrich) and Dmannitol (250M, Sigma-Aldrich) during 4, 8, 24, 48 and 72hrs
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Cell line
View Samples