HiPSC-Derived Hepatocyte-like Cells Can Be Used as a Model for Transcriptomics-Based Study of Chemical Toxicity

Abstract

Traditional toxicity risk assessment approaches have until recently focussed mainly on histochemical readouts for cell death. Modern toxicology methods attempt to deduce a mechanistic understanding of pathways involved in the development of toxicity, by using transcriptomics and other big data-driven methods such as high-content screening. Here, we used a recently described optimised method to differentiate human induced pluripotent stem cells (hiPSCs) to hepatocyte-like cells (HLCs), to assess their potential to classify hepatotoxic and non-hepatotoxic chemicals and their use in mechanistic toxicity studies. The iPSC-HLCs could accurately classify chemicals causing acute hepatocellular injury, and the transcriptomics data on treated HLCs obtained by TempO-Seq technology linked the cytotoxicity to cellular stress pathways, including oxidative stress and unfolded protein response (UPR). Induction of these stress pathways in response to amiodarone, diclofenac, and ibuprofen, was demonstrated to be concentration and time dependent. The transcriptomics data on diclofenac-treated HLCs were found to be more sensitive in detecting differentially expressed genes in response to treatment, as compared to existing datasets of other diclofenac-treated in vitro hepatocyte models. Hence iPSC-HLCs generated by transcription factor overexpression and in metabolically optimised medium appear suitable for chemical toxicity detection as well as mechanistic toxicity studies.

iPSCs as a groundbreaking tool for the study of adverse drug reactions: A new avenue for personalized therapy

“…Nonetheless, current in vitro models, especially hepatocarcinoma-derived cell lines, have some limitations (Kuna et al, 2018), which can be overcome by iPSC-derived hepatocytes. In this regard, Ghosh et al (2021) differentiated iPSCs into hepatocyte-like cells (HLCs) and used these cells for toxicity studies. The authors first added Wnt, activin A, and BMP4 to the culture medium, and used increasing concentrations of DMSO (from 0.6% to 2%), followed by an omission of DMSO starting from day 14.…”

Current Status and Challenges of Human Induced Pluripotent Stem Cell-Derived Liver Models in Drug Discovery

“…In addition, 2D hPSC-HLC models also allow studying infectious liver diseases caused by Hepatitis B, C and E (reviewed in [135]) or malaria [136]. Finally, such 2D differentiation cultures could be upscaled and automated such that screening of toxicity or efficacy of drugs can be conducted at a medium throughput level (100-3000 compounds) and have been used for drug testing and liver toxicity screenings by different research groups, but are to the best of our knowledge not yet implemented in industrial testing platforms [71,128,[137][138][139].…”

Capturing time-dependent activation of genes and stress-response pathways using transcriptomics in iPSC-derived renal proximal tubule cells

“…BMT was calculated using BMDExpress software from the best fit-ted model; log2FoldChange was calculated in R using the weighted 5 − P logistic regression/progression model using transcriptomics. Other iPSC-derived systems for different cell types had been successfully used in TempO-Seq transcriptomic studies, including iPSCderived hepatocytes (ter Braak et al 2021;Ghosh et al 2021) and neurons (Dreser et al 2020), and recently, we have reported a study employing iPSCderived systems that were differentiated into kidney (podocyte-like and PTL cells), liver (hepatocyte-like cells), vasculature (endothelial-like cells), and brain (blood-brain-barrier-like cells, neuronal-like cells, and brain spheres) using TempO-Seq transcriptomics to predict mechanisms of toxicity in response to paraquat (Nunes et al, 2022). Paraquat is a well-described herbicide toxin that induces oxidative stress in the neurons, liver, and kidney (McCarthy et al 2004;Onur et al 2022) that was also picked up by iPSCderived models in that study (Nunes et al 2022).…”

“…In addition, animal and in vitro studies in the liver, kidney, and endothelial cells reported the involvement of oxidative stress (Sarma et al 1997;Golli-Bennour et al 2012). Furthermore, in iPSC-derived hepatocytes, the UPR pathway was one of the major impacted stress response pathways (Ghosh et al 2021). PTL treated with amiodarone induced mainly pathways involved in inflammation, including interleukin 18and NF-ΚB signaling and cytokine-cytokine receptor interaction (Fig.…”

“…Furthermore, several pathway analysis tools have been developed to cope with the analysis of such big datasets, including Consen-susPathDB (Kamburov et al 2013;Kamburov and Herwig 2022), Ingenuity Pathway Analysis (Krämer et al 2014), Reactome Pathway Knowledgebase (Jassal et al 2020), and PathViso (Kutmon et al 2015). Numerous studies report the usefulness of the application of (transcript)omics coupled to cellular stress response pathway analysis for the prediction of wellcharacterized toxic compounds in various human cell-based in vitro models, including renal proximal tubular cells (Wilmes et al 2011(Wilmes et al , 2013(Wilmes et al , 2015Jennings et al 2012;Aschauer et al 2015;Crean et al 2015), hepatocytes (ter Braak et al 2021;Ghosh et al 2021;Grinberg et al 2014;Limonciel et al 2018), and neurons (Pallocca et al 2016;Dreser et al 2020;Delp et al 2021). The use of sophisticated human cell systems is a unique selling point (USP) of modern in vitro applications, especially when the cells do not display cancerous geno-and pheno-types.…”