Large animal models for cardiac remuscularization studies: A methodological review

Front Cardiovasc Med. 2023 Mar 15:10:1011880. doi: 10.3389/fcvm.2023.1011880. eCollection 2023.

Abstract

Myocardial infarction is the most common cause of heart failure, one of the most fatal non-communicable diseases worldwide. The disease could potentially be treated if the dead, ischemic heart tissues are regenerated and replaced with viable and functional cardiomyocytes. Pluripotent stem cells have proven the ability to derive specific and functional cardiomyocytes in large quantities for therapy. To test the remuscularization hypothesis, the strategy to model the disease in animals must resemble the pathophysiological conditions of myocardial infarction as in humans, to enable thorough testing of the safety and efficacy of the cardiomyocyte therapy before embarking on human trials. Rigorous experiments and in vivo findings using large mammals are increasingly important to simulate clinical reality and increase translatability into clinical practice. Hence, this review focus on large animal models which have been used in cardiac remuscularization studies using cardiomyocytes derived from human pluripotent stem cells. The commonly used methodologies in developing the myocardial infarction model, the choice of animal species, the pre-operative antiarrhythmics prophylaxis, the choice of perioperative sedative, anaesthesia and analgesia, the immunosuppressive strategies in allowing xenotransplantation, the source of cells, number and delivery method are discussed.

Keywords: cardiac regeneration; cardiac remuscularization; cardiomyocytes; large animal models; myocardial infarction; pluripotent stem cells (PSC).

Publication types

  • Review

Grants and funding

ZG and JJT are funded by Zhengzhou Cardiovascular Hospital, Zhengzhou Seventh People's Hospital and the Key Laboratory of Cardiac Function and Structure Function Project Fund (2019KFK001, 304/CIPPT/6501080/A150). JJT is also a recipient of the Fundamental Research Grant Scheme (FRGS/1/2018/STG05/USM/03/3) and USM Research University Grant (1001/CIPPT/8011102).