Targeted cellular depletion in an immune-liver-on-a-chip platform elucidates cell-type-specific heterogeneity in drug-induced hepatotoxicity

Drug-induced hepatotoxicity remains a critical challenge in pharmacological safety evaluation; however, the lack of analytical tools to distinguish cell-type-specific hepatotoxic responses hinders mechanistic understanding of toxicity pathways. Herein, we provide proof-of-principle for using an immunocompetent liver-on-a-chip platform that integrates six distinct cell models with a targeted cell depletion strategy to rapidly assess pharmaceutical candidates' hepatotoxic profiles. The platform recapitulated immune cell migration dynamics and stress-responsive behaviors under chemokine induction, while integrated fluidic characterization ensured physiologically relevant microenvironmental control. We applied the targeted depletion strategy to resolve cell population-specific contributions to hepatotoxic outcomes using four mechanistically diverse compounds: acetaminophen, ethinyl estradiol, sulfamethoxazole, and abacavir. Our findings reveal coordinated participation of multiple hepatic cell populations in toxicological processes and identify dominant hepatotoxicity-inducing factors. The immune-dependent toxicity resolution was further validated using a known immune-mediated drug-induced liver injury drug, allopurinol. Overall, this study establishes a targeted cell depletion strategy integrated within an immunocompetent liver-on-a-chip platform, enabling rapid identification of hepatotoxic determinants, and represents a significant advancement in predictive toxicology systems, while providing strategic insights for subsequent pathway analysis.

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Publication Details

Journal
Communications Biology
Published
2025-11-13
DOI
https://doi.org/10.1038/s42003-025-08928-6
Citations
2
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
1.35

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article

Targeted cellular depletion in an immune-liver-on-a-chip platform elucidates cell-type-specific heterogeneity in drug-induced hepatotoxicity

Jiu Deng, Peng Zhang, Juan Chen, Shuai Yuan et al.
2 citations
Communications Biology
3D Printing in Biomedical Research
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article

Targeted cellular depletion in an immune-liver-on-a-chip platform elucidates cell-type-specific heterogeneity in drug-induced hepatotoxicity

Jiu Deng, Peng Zhang, Juan Chen, Shuai Yuan, Shangwen Yang, Xiaofeng Mu, Chengjun Wu
article en
2 citations

Abstract

Drug-induced hepatotoxicity remains a critical challenge in pharmacological safety evaluation; however, the lack of analytical tools to distinguish cell-type-specific hepatotoxic responses hinders mechanistic understanding of toxicity pathways. Herein, we provide proof-of-principle for using an immunocompetent liver-on-a-chip platform that integrates six distinct cell models with a targeted cell depletion strategy to rapidly assess pharmaceutical candidates' hepatotoxic profiles. The platform recapitulated immune cell migration dynamics and stress-responsive behaviors under chemokine induction, while integrated fluidic characterization ensured physiologically relevant microenvironmental control. We applied the targeted depletion strategy to resolve cell population-specific contributions to hepatotoxic outcomes using four mechanistically diverse compounds: acetaminophen, ethinyl estradiol, sulfamethoxazole, and abacavir. Our findings reveal coordinated participation of multiple hepatic cell populations in toxicological processes and identify dominant hepatotoxicity-inducing factors. The immune-dependent toxicity resolution was further validated using a known immune-mediated drug-induced liver injury drug, allopurinol. Overall, this study establishes a targeted cell depletion strategy integrated within an immunocompetent liver-on-a-chip platform, enabling rapid identification of hepatotoxic determinants, and represents a significant advancement in predictive toxicology systems, while providing strategic insights for subsequent pathway analysis.

Communications BiologyVol. 8(1)
Qingdao University (CN), Politecnico di Torino (IT), Affiliated Hospital of Qingdao University (CN), Qingdao Municipal Hospital (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Openalex Percentile: Top 17%
3D Printing in Biomedical Research
1.35
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