An in vitro model for the assessment of stem cell fate following implantation within the infarct microenvironment identifies ISL-1 expression as the strongest predictor of c-Kit(+) cardiac progenitor cells' therapeutic potential

用于评估梗塞微环境中植入后干细胞命运的体外模型表明 ISL-1 表达是 c-Kit(+) 心脏祖细胞治疗潜力的最强预测因子

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作者:Kelly E Sullivan, Laura J Burns, Lauren D Black 3rd

Abstract

Cell therapy has the potential to drastically improve clinical outcomes for the 1.45 million patients suffering from a myocardial infarction (MI) each year in the U.S. However, the limitations associated with this treatment - including poor engraftment, significant cell death and poor differentiation potential - have prevented its widespread application clinically. To optimize functional improvements provided by transplanted cells, there is a need to develop methods that increase cellular retention and viability, while supporting differentiation and promoting paracrine signaling. Current in vivo models are expensive, difficult to access and manipulate and are time consuming. We have developed an in vitro model of MI which allows for a straightforward, consistent and relatively accurate prediction of cell fate following injection in vivo. The model demonstrated how the infarct environment impairs cellular engraftment and differentiation, but identified an implantation strategy which enhanced cell fate in vitro. Multivariate linear regression identified variables within the model that regulated vascular differentiation potential including oxygen tension, stiffness and cytokine presence, while cardiac differentiation was more accurately predicted by Isl-1 expression in the original cell isolate than any other variable present within the model system. The model highlighted how the cells' sensitivity to the infarct variables varied from line to line, which emphasizes the importance of the model system for the prediction of cell fate on a patient specific basis. Further development of this model system could help predict the clinical efficacy of cardiac progenitor cell therapy at the patient level as well as identify the optimal strategy for cell delivery.

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