ReviewJournal of the American Society of Nephrology : JASN2026
Toward Physiologically Relevant Organoid Models of Polycystic Kidney Disease through Microenvironment Reconstruction.
Review in Journal of the American Society of Nephrology : JASN, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The tissue microenvironment plays a pivotal role in polycystic kidney disease (PKD) progression, orchestrating cyst initiation and expansion through dynamic interactions among kidney epithelial, stromal, and immune cells, alongside systemic factors. Accurately reconstructing this complex in vivo milieu is essential to elucidate the mechanisms of PKD pathogenesis and to develop effective therapeutics. Human pluripotent stem cell-derived kidney organoids and patient-specific tubuloids have emerged as powerful platforms for modeling PKD within defined genetic contexts, faithfully recapitulating key pathological features of tubular cystogenesis. However, current organoid culture systems remain limited in their ability to replicate the full complexities of the native disease niche. Integrating bioengineering with developmental and biological insights will be essential to recreating physiologically relevant microenvironments. Such innovations will enhance the fidelity, predictive power, and translational utility of PKD organoid models, ultimately enabling more accurate drug testing and personalized therapeutics.
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Registered trials
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