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Cardiomyocytes (CMs) generated from human pluripotent stem cells (hPSCs) are immature in their structure and function, limiting their potential in disease modeling, drug screening, and cardiac cellular therapies. Prior studies have demonstrated that coculture of hPSC‐derived CMs with other cardiac cell types, including endothelial cells (ECs), can accelerate CM maturation. To address whether the CM differentiation stage at which ECs are introduced affects CM maturation, the authors coculture hPSC‐derived ECs with hPSC‐derived cardiac progenitor cells (CPCs) and CMs and analyze the molecular and functional attributes of maturation. ECs have a more significant effect on acceleration of maturation when cocultured with CPCs than with CMs. EC coculture with CPCs increases CM size, expression of sarcomere, and ion channel genes and proteins, the presence of intracellular membranous extensions, and chronotropic response compared to monoculture. Maturation is accelerated with an increasing EC:CPC ratio. This study demonstrates that EC incorporation at the CPC stage of CM differentiation expedites CM maturation, leading to cells that may be better suited for in vitro and in vivo applications of hPSC‐derived CMs.
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This content will become publicly available on December 1, 2025
Data-Driven Maturity Level Evaluation for Cardiomyocytes Derived from Human Pluripotent Stem Cells (Invited Paper)
Cardiovascular disease is a leading cause of death worldwide. The differentiation of human pluripotent stem cells (hPSCs) into functional cardiomyocytes offers significant potential for disease modeling and cell-based cardiac therapies. However, hPSC-derived cardiomyocytes (hPSC-CMs) remain largely immature, limiting their experimental and clinical applications. A critical challenge in current in vitro culture systems is the absence of standardized metrics to quantify maturity. This study presents a data-driven pipeline to quantify hPSC-CM maturity using gene expression data across various stages of cardiac development. We determined that culture time serves as a feasible proxy for maturity. To improve prediction accuracy, machine learning algorithms were employed to identify heart-related genes whose expression strongly correlates with culture time. Our results reduced the average discrepancy between predicted and observed culture time to 4.461 days and CASQ2 (Calsequestrin 2), a gene involved in calcium ion storage and transport, was identified as the most critical cardiac gene associated with culture duration. This novel framework for maturity assessment moves beyond traditional qualitative methods, providing deeper insights into hPSC-CM maturation dynamics. It establishes a foundation for developing advanced lab-on-chip devices capable of real-time maturity monitoring and adaptive stimulus selection, paving the way for improved maturation strategies and broader experimental/clinical applications.
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- PAR ID:
- 10616020
- Editor(s):
- Jeong, Jichai; Mongan, William M
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Electronics
- Volume:
- 13
- Issue:
- 24
- ISSN:
- 2079-9292
- Page Range / eLocation ID:
- 4985
- Subject(s) / Keyword(s):
- cardiovascular diseases hPSC-CM maturity gene expression cardiac gene selection culture time prediction
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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