Advancing transcriptomics-based mechanistic assessment of nephrotoxicity in vitro using the human RPTEC/TERT1 TXG-MAPr gene co-expression network

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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Publication Details

Journal
Toxicological Sciences
Published
2025-11-20
DOI
https://doi.org/10.1093/toxsci/kfaf159
Primary Topic
Acute Kidney Injury Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Advancing transcriptomics-based mechanistic assessment of nephrotoxicity in vitro using the human RPTEC/TERT1 TXG-MAPr gene co-expression network

Giulia Callegaro, Steven J. Kunnen, Bob van de Water, Hugo W van Kessel
Toxicological Sciences
Acute Kidney Injury Research
article

Advancing transcriptomics-based mechanistic assessment of nephrotoxicity in vitro using the human RPTEC/TERT1 TXG-MAPr gene co-expression network

Giulia Callegaro, Steven J. Kunnen, Bob van de Water, Hugo W van Kessel
article en

Abstract

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.

Toxicological SciencesVol. 209(1)
Centre for Human Drug Research (NL)
European Commission, Vrije Universiteit Amsterdam, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 58%
Acute Kidney Injury Research
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Advancing transcriptomics-based mechanistic assessment of nephrotoxicity in vitro using the human RPTEC/TERT1 TXG-MAPr gene co-expression network — Giulia Callegaro, Steven J. Kunnen, et al. · Toxicological Sciences (2025) | TGRS Research Map | TGRS