Three-Dimensional Cultures of Human Subcutaneous Adipose Tissue-Derived Progenitor Cells Based on RAD16-I Self-Assembling Peptide

Cristina Castells-Sala, Lourdes Recha-Sancho, Aida Llucià-Valldeperas, Carolina Soler-Botija, Antoni Bayes-Genis, Carlos E Semino

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The prolonged ischemia after myocardial infarction leads to a high degree of cardiomyocyte death, which leads to a reduction of normal heart function. Valuable lessons can be learnt from human myocardium and stem cell biology that would help scientists to develop new, effective, safe, and affordable regenerative therapies. In vivo models are of high interest, but their high complexity limits the possibility to analyze specific factors. In vitro models permit analyzing specific factors of tissue physiology or pathophysiology providing accurate approaches that may guide the creation of three-dimensional (3D) engineered cell aggregates. These systems provide a simplistic way to examine individual factors as compared to animal models, and better mimic the reality than 2D models. In this sense, the objective of this work is to better understand the behavior of a human mesenchymal stem cell-like cell line (subcutaneous adipose tissue-derived progenitor cells [subATDPCs], susceptible to be used in cell therapies) when they are embedded in the 3D environment provided by RAD16-I self-assembling peptide (SAP). Specifically, we study the effect in subATDPCs viability, morphology, proliferation, and protein and gene expression of matrix composition (i.e., RGD motif and heparin polysaccharide modifications) in RAD16-I matrix under different media conditions. Results demonstrated that the 3D environment provided by RAD16-I SAP is able to maintain subATDPCs in this new milieu and at the same time its cardiac commitment. Additionally, it has been observed that chemical induction can induce upregulation of cardiac markers, such as TBX5, MEF2C, ACTN1, and GJA1. Therefore, we propose this 3D model as a promising platform to analyze the effect of specific cues that can help improve cell performance for future cell therapy.

Original languageEnglish
JournalTissue Engineering Part C. Methods
DOIs
Publication statusE-pub ahead of print - 7 Jan 2016

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