TY - JOUR T1 - The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment JF - bioRxiv DO - 10.1101/2021.05.17.444463 SP - 2021.05.17.444463 AU - Giulia Callegaro AU - Steven J. Kunnen AU - Panuwat Trairatphisan AU - Solène Grosdidier AU - Marije Niemeijer AU - Wouter den Hollander AU - Emre Guney AU - Janet Piñero Gonzalez AU - Laura Furlong AU - Yue W. Webster AU - Julio Saez-Rodriguez AU - Jeffrey J. Sutherland AU - Jennifer Mollon AU - James L. Stevens AU - Bob van de Water Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/05/18/2021.05.17.444463.abstract N2 - Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of comprehensive and mechanisms-revealing data, but analysis tools to interpret mechanisms of toxicity and specific for the testing systems (e.g. hepatocytes) are lacking. In this study we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/), an R-Shiny-based implementation of weighted gene co-expression networks (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. Gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, are perturbed by specific stressors and show preserved in rat systems (rat primary hepatocytes and rat in vivo liver), highlighting stress responses that translate across species/testing systems. The TXG-MAPr tool was successfully applied to investigate the mechanism of toxicity of TG-GATEs compounds and using external datasets obtained from different hepatocyte cells and microarray platforms. Additionally, we suggest that module responses can be calculated from targeted RNA-seq data therefore imputing biological responses from a limited gene. By analyzing 50 different PHH donors’ responses to a common stressor, tunicamycin, we were able to suggest modules associated with donor’s traits, e.g. pre-existing disease state, therefore connected to donors’ variability. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data.Competing Interest StatementThe authors have declared no competing interest.APAPacetaminophenavgAbsEGaverage absolute eigengene scorecorEGcorrelation eigengene scoreCSAcyclosporine ADILIdrug?induced liver injuryDDRDNA damage responseEGseigengene scoreEREndoplasmic ReticulumGOgene ontologyISRintegrated stress responseMoAMode of ActionPHHprimary human hepatocytesRPHrat primary hepatocytesTFtranscription factorTGTG?GATEsTUNtunicamycinTXGtoxicogenomicWGCNAweighted gene co?expression network analysis ER -