Publication | Open Access
A patterned human primitive heart organoid model generated by pluripotent stem cell self-organization
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Citations
55
References
2023
Year
Pluripotent stem cell–derived organoids can recapitulate key aspects of organ development in vitro. The study aimed to generate human heart organoids by mimicking in‑utero conditions to enhance physiological and anatomical relevance. They employed a self‑organization–driven developmental induction strategy, adding metabolic and hormonal cues, and demonstrated the system’s utility by testing ondansetron’s teratogenic effects. The resulting organoids were transcriptionally and morphologically indistinguishable from age‑matched human embryonic hearts, displayed key developmental features such as large chambers and proepicardial organ formation, and proved useful for disease modeling.
Abstract Pluripotent stem cell-derived organoids can recapitulate significant features of organ development in vitro. We hypothesized that creating human heart organoids by mimicking aspects of in utero gestation (e.g., addition of metabolic and hormonal factors) would lead to higher physiological and anatomical relevance. We find that heart organoids produced using this self-organization-driven developmental induction strategy are remarkably similar transcriptionally and morphologically to age-matched human embryonic hearts. We also show that they recapitulate several aspects of cardiac development, including large atrial and ventricular chambers, proepicardial organ formation, and retinoic acid-mediated anterior-posterior patterning, mimicking the developmental processes found in the post-heart tube stage primitive heart. Moreover, we provide proof-of-concept demonstration of the value of this system for disease modeling by exploring the effects of ondansetron, a drug administered to pregnant women and associated with congenital heart defects. These findings constitute a significant technical advance for synthetic heart development and provide a powerful tool for cardiac disease modeling.
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