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A Multi-Omics Human Liver Organoid Screening Platform for DILI Risk Prediction

View ORCID ProfileCharles J. Zhang, View ORCID ProfileMatthew J. O’Meara, View ORCID ProfileSophia R. Meyer, Sha Huang, View ORCID ProfileMeghan M. Capeling, View ORCID ProfileDaysha Ferrer-Torres, View ORCID ProfileCharlie J. Childs, View ORCID ProfileJason R. Spence, View ORCID ProfileRobert J. Fontana, View ORCID ProfileJonathan Z. Sexton
doi: https://doi.org/10.1101/2021.08.26.457824
Charles J. Zhang
1Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, MI, 48109, USA
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Matthew J. O’Meara
2Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
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Sophia R. Meyer
1Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, MI, 48109, USA
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Sha Huang
3Department of Internal Medicine, Gastroenterology and Hepatology, Michigan Medicine at the University of Michigan, Ann Arbor, MI, 48109, USA
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Meghan M. Capeling
3Department of Internal Medicine, Gastroenterology and Hepatology, Michigan Medicine at the University of Michigan, Ann Arbor, MI, 48109, USA
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Daysha Ferrer-Torres
3Department of Internal Medicine, Gastroenterology and Hepatology, Michigan Medicine at the University of Michigan, Ann Arbor, MI, 48109, USA
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Charlie J. Childs
4Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
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Jason R. Spence
3Department of Internal Medicine, Gastroenterology and Hepatology, Michigan Medicine at the University of Michigan, Ann Arbor, MI, 48109, USA
4Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
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Robert J. Fontana
3Department of Internal Medicine, Gastroenterology and Hepatology, Michigan Medicine at the University of Michigan, Ann Arbor, MI, 48109, USA
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Jonathan Z. Sexton
1Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, MI, 48109, USA
3Department of Internal Medicine, Gastroenterology and Hepatology, Michigan Medicine at the University of Michigan, Ann Arbor, MI, 48109, USA
5U-M Center for Drug Repurposing, University of Michigan, Ann Arbor, MI, 48109, USA
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  • For correspondence: jzsexton@med.umich.edu
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Abstract

Background and Aims Drug-induced liver injury (DILI) is a prominent failure mode in drug development resulting in clinical trial failures and post-approval withdrawal. Improved in vitro models for DILI risk prediction that can model diverse genetics are needed to improve safety and reduce high attrition rates in drug development. In this study, we evaluated the utility of human liver organoids (HLOs) for high-throughput DILI risk prediction and in an organ-on-chip system. The recent clinical failure of inarigivir soproxil due to DILI underscores the need for improved models.

Methods HLOs were adapted for high-throughput drug screening in dispersed-cell 384-well format and a collection of DILI-associated drugs were screened. HLOs were also adapted to a liver-chip system to investigate enhanced in vivo-like function. Both platforms were benchmarked for their ability to predict DILI using combined biochemical assays, microscopy-based morphological profiling, and transcriptomics.

Results Dispersed HLOs retained DILI predictive capacity of intact HLOs and are amenable to high-throughput screening allowing for measurable IC50 values for cytotoxicity. Distinct morphological differences were observed in cells treated with drugs exerting differing mechanisms of action. HLOs on chips were shown to increase albumin production, CYP450 expression and also release ALT/AST when treated with known DILI drugs. Importantly, HLO liver chips were able to predict hepatotoxicity of tenofovir-inarigivir and showed steatosis and mitochondrial perturbation via phenotypic and transcriptomic analysis.

Conclusions The high throughput and liver-on-chip system exhibit enhanced in vivo-like function and demonstrate the utility of the platforms in early and late-stage drug development. Tenofovir-inarigivr associated hepatotoxicity was observed and highly correlates with the clinical manifestation of DILI.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Conflicts of interest: The authors declare no conflicts of interest.

  • Abbreviations

    DILI
    drug-induced liver injury
    ALT
    alanine aminotransferase
    HLO
    human liver organoid
    iPSC
    induced-pluripotent stem cells
    HLA
    human leukocyte antigen
    PaDLOC
    patient-derived liver-on-chip
    scRNAseq
    Single cell RNA sequencing
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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    Posted August 28, 2021.
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    A Multi-Omics Human Liver Organoid Screening Platform for DILI Risk Prediction
    Charles J. Zhang, Matthew J. O’Meara, Sophia R. Meyer, Sha Huang, Meghan M. Capeling, Daysha Ferrer-Torres, Charlie J. Childs, Jason R. Spence, Robert J. Fontana, Jonathan Z. Sexton
    bioRxiv 2021.08.26.457824; doi: https://doi.org/10.1101/2021.08.26.457824
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    A Multi-Omics Human Liver Organoid Screening Platform for DILI Risk Prediction
    Charles J. Zhang, Matthew J. O’Meara, Sophia R. Meyer, Sha Huang, Meghan M. Capeling, Daysha Ferrer-Torres, Charlie J. Childs, Jason R. Spence, Robert J. Fontana, Jonathan Z. Sexton
    bioRxiv 2021.08.26.457824; doi: https://doi.org/10.1101/2021.08.26.457824

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