Transcriptomics data from human, mouse, rat in vitro liver models

Abstract:
In this case study a transcriptomics-based hazard prediction model for identification of specific molecular initiating events (MIE) was foreseen based on (A) top-down and (B) bottom-up approaches. The MIEs can include, but are not limited to: (1) Genotoxicity (p53 activation), (2) Oxidative stress (Nrf2 activation), (3) Endoplasmic Reticulum Stress (unfolded protein response), (4) Dioxin-like activity (AhR receptor activation), (5) HIF1 alpha activation and (6) Nuclear receptor activation (e.g. for endocrine disruption). This case study focussed on two top-down approaches for genotoxicity prediction. The first approach resulted in the creation of a Nextflow-based workflow from the publication “A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo” by Magkoufopoulou et al. (2012), thereby reproducing their work as proof of principle. The Nextflow-based workflow has been translated into a more generic approach, especially for step 1, forming the basis of the second top-down approach. In this approach transcriptomics data together with toxicological compound information were collected from multiple toxicogenomics studies and used for building a metadata genotoxicity prediction model.