Organoid-on-a-chip model of human ARPKD reveals mechanosensing pathomechanisms for drug discovery
Open accessAbstract
Organoids serve as a novel tool for disease modeling in three-dimensional multicellular contexts. Static organoids, however, lack the requisite biophysical microenvironment such as fluid flow, limiting their ability to faithfully recapitulate disease pathology. Here, we unite organoids with organ-on-a-chip technology to unravel disease pathology and develop therapies for autosomal recessive polycystic kidney disease. PKHD1 -mutant organoids-on-a-chip are subjected to flow that induces clinically relevant phenotypes of distal nephron dilatation. Transcriptomics discover 229 signal pathways that are not identified by static models. Mechanosensing molecules, RAC1 and FOS, are identified as potential therapeutic targets and validated by patient kidney samples. On the basis of this insight, we tested two U.S. Food and Drug Administration–approved and one investigational new drugs that target RAC1 and FOS in our organoid-on-a-chip model, which suppressed cyst formation. Our observations highlight the vast potential of organoid-on-a-chip models to elucidate complex disease mechanisms for therapeutic testing and discovery.
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The use of siRNA technology in 3D organoid cultures has been very limited.
“The use of siRNA technology in 3D organoid cultures has been very limited [48,49,50], likely also due to the technical challenge of delivering siRNAs through the extracellular matrix to organoids in situ [49].”
From Regulation of Enterocyte Brush Border Membrane Primary Na-Absorptive Transporters in Human Intestinal Organoid-Derived Monolayers (2024) · cites this paper as [48]
The Results section (“Mechanosensing signals are activated by fluid flow”; page unavailable) reports siRNA knockdown in kidney organoids, so this paper is an example of siRNA use in organoid culture. It does not assess how common that use is across 3D organoid research and therefore does not establish that it has been “very limited.” (LLM, conf=0.82)
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- Authors
- Hiratsuka, K., Miyoshi, T., Kroll, K. T., Gupta, N. R., Valerius, M. T., Ferrante, T., Yamashita, M., Lewis, J. A., & Morizane, R.
- Affiliations
- Brigham and Women's Hospital (US)
- Harvard University (US)
- Cedars-Sinai Medical Center (US)
- Corresponding author
- Hiratsuka, Ken
- Miyoshi, Tomoya
- Lewis, Jennifer A.
- Morizane, Ryuji
- ORCID
- Venue
- Science Advances
- Published
- 2022-09-23
- Volume
- 8
- Issue
- 38
- Pages
- eabq0866-eabq0866
- ISSN
- 2375-2548 (ISSN-L)
- PMC
- PMC9491724
- OpenAlex
- W4296564551
- Cited by
- 140
- References
- 76
- Citations by year
- 2026: 34 · 2025: 35 · 2024: 38 · 2023: 29 · 2022: 3 · 2012: 1
- FWCI
- 15.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Science Advances (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (UH3TR002155)
- National Institute of Diabetes and Digestive and Kidney Diseases (UC2DK126023, DP2DK133821, U01DK127587, R21DK129909)
- National Institute of Biomedical Imaging and Bioengineering (U01EB028899)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and Kidney Cyst Diseases
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Physical Sciences › Engineering › Biomedical Engineering › Microfluidic and Capillary Electrophoresis Applications
- Keywords
- autosomal recessive polycystic kidney disease, PKHD1, mechanosensing, fluid flow, Rac1, FOS, drug target identification, drug screening, kidney cyst formation, disease modeling
- MeSH terms
- Humans, Organoids, Drugs, Investigational, Polycystic Kidney, Autosomal Recessive, Drug Discovery, Lab-On-A-Chip Devices
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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