Maturation is required to model ischemia-reperfusion injury in engineered human cardiac tissues
Year: 2026
Type: article
Abstract: Introduction Myocardial infarction remains a leading cause of mortality worldwide, with reperfusion therapy as the clinical standard of care. However, its efficacy is limited by the paradoxical injury caused by ischemia-reperfusion (I/R). Methods Micro-sized human engineered cardiac tissues (hECTs) were fabricated using induced pluripotent stem cell (iPSC)-derived cardiomyocytes and primary human cardiac fibroblasts in the previously published milliPillar platform and cultured under four conditions integrating metabolic and electrical maturation strategies: standard B27 medium or metabolic maturation medium (MM), each with or without frequency-ramped electrical stimulation. After 28 days of maturation, tissues were subjected to 6 hours of simulated ischemia followed by reperfusion and were assessed for LDH release, cardiac troponin T (cTnT) release, and contractile function over 7 days post-reperfusion. Results Here, we demonstrate that maturation of a human tissue-engineered cardiac model of I/R injury can recapitulate key features of acute ischemic damage, reperfusion injury, and sustained contractile dysfunction. Modulation of engineered tissue phenotype results in distinct differences in susceptibility to injury and pathological fidelity. Discussion Notably, electrical stimulation emerges as a critical determinant of I/R injury response, whereas metabolic maturation alone is insufficient to reproduce comparable pathological outcomes. Together, these findings define the structural and functional parameters required to prime cardiac muscle tissues to recapitulate a biologically relevant in vitro model of myocardial I/R injury and provide a framework for improving the translational fidelity of engineered cardiac systems.
Institution: Columbia University
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7168137774
