Besides the established selection criteria based on embryo morphology and blastomere number, new parameters for embryo viability are needed to improve the clinical outcome of in vitro fertilization (IVF) and more particular of elective single embryo transfer (eSET). The aim of the study was to analyse genome-wide whether the embryo viability was reflected by the expression of genes in the oocyte surrounding cumulus cells. Early cleavage (EC) was chosen as a parameter for embryo viability.
Differential gene expression in cumulus cells as a prognostic indicator of embryo viability: a microarray analysis.
No sample metadata fields
View SamplesThe 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.
A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo.
Cell line, Time
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.
Specimen part, Compound
View SamplesThe 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.
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.
Specimen part, Compound
View SamplesThe 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
No associated publication
Specimen part, Cell line
View SamplesThe 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.
Time series analysis of oxidative stress response patterns in HepG2: a toxicogenomics approach.
Cell line
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.
Specimen part, Compound
View SamplesWe evaluated transcriptional profiles in peripheral blood mononuclear cells (PBMCs) from 54 pregnant women in Kenya, 19 of whom delivered preterm.
Influenza-Induced Interferon Lambda Response Is Associated With Longer Time to Delivery Among Pregnant Kenyan Women.
Specimen part, Treatment
View SamplesThe 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
Classification of hepatotoxicants using HepG2 cells: A proof of principle study.
Specimen part, Cell line
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Integrating multiple omics to unravel mechanisms of Cyclosporin A induced hepatotoxicity in vitro.
Specimen part, Cell line, Time
View Samples