Utilizing rat kidney gene co-expression networks to enhance safety assessment biomarker identification and human translation

Toxicogenomic data provide key insights into molecular mechanisms underlying drug-induced organ toxicities. To simplify transcriptomic data interpretation, we applied weighted gene co-expression network analysis (WGCNA) to rat kidney transcriptomics data from TG-GATEs (TG) and DrugMatrix (DM), cover...

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Hauptverfasser: Kunnen, Steven J. (VerfasserIn) , Callegaro, Giulia (VerfasserIn) , Sutherland, Jeffrey J. (VerfasserIn) , Trairatphisan, Panuwat (VerfasserIn) , van Kessel, Hugo W. (VerfasserIn) , Wijaya, Lukas S. (VerfasserIn) , Chung, Git (VerfasserIn) , Pye, Keith (VerfasserIn) , Goldstein, Keith M. (VerfasserIn) , Teague, Claire R. (VerfasserIn) , Fisher, Ciaran P. (VerfasserIn) , Sáez Rodríguez, Julio (VerfasserIn) , Brown, Colin (VerfasserIn) , Elmore, Susan A. (VerfasserIn) , Heinz-Taheny, Kathleen M. (VerfasserIn) , Stevens, James L. (VerfasserIn) , van de Water, Bob (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 18 July 2025
In: iScience
Year: 2025, Jahrgang: 28, Heft: 7, Pages: 1-21, e1-e4
ISSN:2589-0042
DOI:10.1016/j.isci.2025.112978
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.isci.2025.112978
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2589004225012398
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Verfasserangaben:Steven J. Kunnen, Giulia Callegaro, Jeffrey J. Sutherland, Panuwat Trairatphisan, Hugo W. van Kessel, Lukas S. Wijaya, Git Chung, Keith Pye, Keith M. Goldstein, Claire R. Teague, Ciaran P. Fisher, Julio Saez-Rodriguez, Colin Brown, Susan A. Elmore, Kathleen M. Heinz-Taheny, James L. Stevens, and Bob van de Water
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Zusammenfassung:Toxicogenomic data provide key insights into molecular mechanisms underlying drug-induced organ toxicities. To simplify transcriptomic data interpretation, we applied weighted gene co-expression network analysis (WGCNA) to rat kidney transcriptomics data from TG-GATEs (TG) and DrugMatrix (DM), covering time- and dose-response data for 180 compounds. A total of 347 gene modules were incorporated into the rat kidney TXG-MAPr web-tool, that interactively visualizes and quantifies module activity using eigengene scores (EGSs). Several modules annotated for cellular stress, injury, and inflammation were associated with renal pathologies and included established and candidate biomarker genes. Many rat kidney modules were preserved across transcriptome datasets, suggesting potential applicability to other kidney injury contexts. Cross-species preservation analysis using human kidney data further supported the translational potential of these rat-derived modules. The TXG-MAPr platform facilitates upload and analysis of gene expression data in the context of rat kidney co-expression networks, which could identify mechanisms and safety liabilities of chemical or drug exposures.
Beschreibung:Gesehen am 10.12.2025
Beschreibung:Online Resource
ISSN:2589-0042
DOI:10.1016/j.isci.2025.112978