This research demonstrates high-throughput transcriptomic approaches to assess nephrotoxicity in human kidney cells, indicating advancements in chemical safety assessment.
Traditional animal-based chemical safety assessments often fall short in accurately predicting human toxicities, highlighting the need for more human-relevant testing strategies. In response to this challenge, new approach methodologies have emerged, with high-throughput in vitro transcriptomic screening playing a pivotal role in elucidating mechanisms of toxicity. In this study, we developed the first human kidney in vitro toxicogenomic co-expression network using transcriptomic profiles from immortalized human renal proximal tubule epithelial cells (RPTEC/TERT1) exposed to a curated panel of nephrotoxicants. Through weighted correlation network analysis, we identified distinct gene co-expression modules and conducted comprehensive downstream analyses at the module, sample, and transcription factor levels. We integrated these insights into the human in vitro RPTEC/TERT1 TXG-MAPr, an interactive R Shiny platform designed to facilitate the interpretation of gene co-expression networks. Our findings demonstrate that module-based analysis enables the differentiation of distinct mechanisms of action. By linking transcriptional modules to KE within the nephrotoxicity adverse outcome pathway network, we reinforce the potential of gene co-expression network approaches to advance mechanism-based risk assessment and support next-generation chemical safety assessment.
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Kessel et al. (2025) studied this question.
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