Application of human induced pluripotent stem cells for tissue modeling and therapy: are we on track?

Le résumé fourni par la source

Stem cells are key for development of disease modeling and therapies. While promising, however, current application of cutting-edge hiPSC technologies is, among others, confounded by cellular heterogeneity leading to concerns about their suitability for experimental and clinical applications. Variations across donors, tissue sources, methodologies, and analytical challenges, together contribute to the observed heterogeneity. Hence, increased understanding of heterogeneity in stem cell research is essential to advance development of reliable tissue models and effective therapies. In this review, we summarize current knowledge regarding the origins of cellular heterogeneity in hiPSC-derivatives. Differentiation protocols can be improved through the application of novel media morphogens, integration with new biomaterials and physical strategies (eg, 3D culture, mechanical stimulation). Additionally, standardization of methods and regulations for generation and application of cell lines and neo-tissues, thorough characterization, central banking, and registration of cells will reduce variation and increase experimental reproducibility. As reliable reference datasets become more abundant the continuous development of analytical tools as well as advanced application of artificial intelligence to analyze omics datasets will become more refined. This will aid identification of different cell types in heterogeneous cell populations and key factors driving off-target differentiation. We provide recommendations for best practices throughout the stem cell research pipeline and discuss opportunities to advance broad applicability of stem cells for disease modeling and beyond through concerted efforts to improve experimental robustness and analytical accuracy. Finally, we advocate that certain heterogeneity may be essential in development of laboratory models to faithfully mimic the in vivo situation.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.