Human Cell Modeling for Cardiovascular Diseases
- PMID: 32887493
- PMCID: PMC7503257
- DOI: 10.3390/ijms21176388
Human Cell Modeling for Cardiovascular Diseases
Abstract
The availability of appropriate and reliable in vitro cell models recapitulating human cardiovascular diseases has been the aim of numerous researchers, in order to retrace pathologic phenotypes, elucidate molecular mechanisms, and discover therapies using simple and reproducible techniques. In the past years, several human cell types have been utilized for these goals, including heterologous systems, cardiovascular and non-cardiovascular primary cells, and embryonic stem cells. The introduction of induced pluripotent stem cells and their differentiation potential brought new prospects for large-scale cardiovascular experiments, bypassing ethical concerns of embryonic stem cells and providing an advanced tool for disease modeling, diagnosis, and therapy. Each model has its advantages and disadvantages in terms of accessibility, maintenance, throughput, physiological relevance, recapitulation of the disease. A higher level of complexity in diseases modeling has been achieved with multicellular co-cultures. Furthermore, the important progresses reached by bioengineering during the last years, together with the opportunities given by pluripotent stem cells, have allowed the generation of increasingly advanced in vitro three-dimensional tissue-like constructs mimicking in vivo physiology. This review provides an overview of the main cell models used in cardiovascular research, highlighting the pros and cons of each, and describing examples of practical applications in disease modeling.
Keywords: cardiovascular disease; co-cultures; disease modeling; embryonic stem cells; engineered 3D tissue; heterologous system; human cell model; human induced pluripotent stem cell; primary cells.
Conflict of interest statement
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
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