A human in vitro platform for the evaluation of pharmacology strategies in cardiac ischemia

用于评估心脏缺血药理学策略的人体体外平台

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作者:Carlota Oleaga, Golareh Jalilvand, Gregg Legters, Candace Martin, Gail Ekman, Christopher W McAleer, Christopher J Long, James J Hickman

Abstract

Cardiac ischemic events increase the risk for arrhythmia, heart attack, heart failure, and death and are the leading mortality condition globally. Reperfusion therapy is the first line of treatment for this condition, and although it significantly reduces mortality, cardiac ischemia remains a significant threat. New therapeutic strategies are under investigation to improve the ischemia survival rate; however, the current preclinical models to validate these fail to predict the human outcome. We report the development of a functional human cardiac in vitro system for the study of conduction velocity under ischemic conditions. The system is a bioMEMs platform formed by human iPSC derived cardiomyocytes patterned on microelectrode arrays and maintained in serum-free conditions. Electrical activity changes of conduction velocity, beat frequency, and QT interval (the QT-interval measures the period from onset of depolarization to the completion of repolarization) or action potential length can be evaluated over time and under the stress of ischemia. The optimized protocol induces >80% reduction in conduction velocity, after a 4 h depletion period, and a partial recovery after 72 h of oxygen and nutrient reintroduction. The sensitivity of the platform for pharmacological interventions was challenged with a gap junction modulator (ZP1609), known to prevent or delay the depression of conduction velocity induced by ischemic metabolic stress. ZP1609 significantly improved the drastic drop in conduction velocity and enabled a greater recovery. This model represents a new preclinical platform for studying cardiac ischemia with human cells, which does not rely on biomarker analysis and has the potential for screening novel cardioprotective drugs with readouts that are closer to the measured clinical parameters.

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