Engineering approaches for cardiac organoid formation and their characterization

Published:August 19, 2022DOI:
      Cardiac organoids are 3-dimensional (3D) structures composed of tissue or niche-specific cells, obtained from diverse sources, encapsulated in either a naturally derived or synthetic, extracellular matrix scaffold, and include exogenous biochemical signals such as essential growth factors. The overarching goal of developing cardiac organoid models is to establish a functional integration of cardiomyocytes with physiologically relevant cells, tissues, and structures like capillary-like networks composed of endothelial cells. These organoids used to model human heart anatomy, physiology, and disease pathologies in vitro have the potential to solve many issues related to cardiovascular drug discovery and fundamental research. The advent of patient-specific human-induced pluripotent stem cell-derived cardiovascular cells provide a unique, single-source approach to study the complex process of cardiovascular disease progression through organoid formation and incorporation into relevant, controlled microenvironments such as microfluidic devices. Strategies that aim to accomplish such a feat include microfluidic technology-based approaches, microphysiological systems, microwells, microarray-based platforms, 3D bioprinted models, and electrospun fiber mat-based scaffolds. This article discusses the engineering or technology-driven practices for making cardiac organoid models in comparison with self-assembled or scaffold-free methods to generate organoids. We further discuss emerging strategies for characterization of the bio-assembled cardiac organoids including electrophysiology and machine-learning and conclude with prospective points of interest for engineering cardiac tissues in vitro.



      ALP (alkaline phosphatase), α-SMA (alpha-smooth muscle actin), BECs (blood vascular endothelial cells), bFGF (basic fibroblast growth factor), CFs (cardiac fibroblasts), CMs (cardiomyocytes), CVD (cardiovascular diseases), Cx43 (connexin 43), DE (differential expression), ECs (endothelial cells), ECM (extracellular matrix), EMT (epithelial to mesenchymal), EPHYS (electrophysiology), FTIR (fourier transformed infrared), GelMA (gelatin methacryloyl), GLMs (generalized linear models), GO (gene ontology), GSEA (gene set enrichment analysis), hCS (human cerebral cortex), hiPSC (human induced pluripotent stem cell), hMSCs (human mesenchymal stem cells), hSpS (human hindbrain/cerebral cortex), HUVECs (human umbilical vein endothelial cells), HyA (hyaluronic acid), LECs (lymphatic endothelial cells), LV (left ventricle), MEA (microelectrode arrays), MPSs (microphysiological systems), NIPAAM (N-isopropyl acrylamide), PCL (Poly(ε-caprolactone)), PDMS (polydimethylsiloxane), PEDOT (Poly(3,4- ethylenedioxythiophene)), PEG (polyethylene glycol), PGA (polyglycolide), PGS (polyglycerol sebacate), PLA (Poly(L-lactide)), PLGA (Poly(lactide-co-glycolide)), PSS (polystyrene sulfonate), PPy (polypyrrole), RNA (ribonucleic acid), RNA-seq (RNA sequencing), SEM (scanning electron microscopy), scRNA-seq (single-cell RNA sequencing), SLA (stereolithography), TEM (transmission electron microscopy), TGF β (transforming growth factor), VEGF (vascular endothelial growth factor)
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