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GSE12337
Mus musculus
16 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Findings suggest that PPARalpha plays a decisive role in the development of hypertrophy, affecting the functional outcome of the heart. Unfortunately, information on the nature of PPARalpha-dependent processes in cardiac hypertrophy is fragmentary and incomplete.
Publication Title
Transcriptomic analysis of PPARalpha-dependent alterations during cardiac hypertrophy.
Sample Metadata Fields
No sample metadata fields
View Samples- Saccharomyces cerevisiae
- 10 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
Diclofenac is a widely used analgesic drug that can cause serious adverse drug reactions. We used Saccharomyces cerevisiae as model eukaryote to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Although most yeast cells died during initial diclofenac treatment, some survived and started growing again. Microarray analysis of the adapted cells identified three major processes involved in diclofenac detoxification and tolerance. Especially pleiotropic drug resistance genes and genes under control of Rlm1p, a transcription factor in the protein kinase C (PKC) pathway, were upregulated in diclofenac-adapted cells. Genes involved in ribosome biogenesis and rRNA processing were downregulated, as well as zinc-responsive genes.
Publication Title
Involvement of the pleiotropic drug resistance response, protein kinase C signaling, and altered zinc homeostasis in resistance of Saccharomyces cerevisiae to diclofenac.
Sample Metadata Fields
Treatment
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- Homo sapiens
- 124 Downloadable Samples
- Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)
Description
The transcriptomic changes induced in the human liver cell line HepG2 by 100M menadione, 200M TBH or 50M H2O2 after treatment for 0.5, 1, 2, 4, 6, 8 and 24h.
Publication Title
Time series analysis of oxidative stress response patterns in HepG2: a toxicogenomics approach.
Sample Metadata Fields
Cell line
View Samples- Mus musculus
- 56 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
Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.
Sample Metadata Fields
Specimen part, Compound
View Samples- Homo sapiens
- 92 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
We evaluated transcriptional profiles in peripheral blood mononuclear cells (PBMCs) from 54 pregnant women in Kenya, 19 of whom delivered preterm.
Publication Title
Influenza-Induced Interferon Lambda Response Is Associated With Longer Time to Delivery Among Pregnant Kenyan Women.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Homo sapiens
- 97 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The transcriptomics changes induced in the human liver cell line HepG2 by 17 hepatotoxic compounds, 5 non-hepatotoxic compounds and solvent controls after treatment for 24h
Publication Title
Classification of hepatotoxicants using HepG2 cells: A proof of principle study.
Sample Metadata Fields
Specimen part, Cell line
View Samples