Innovative three-dimensional models for understanding mechanisms underlying lung diseases: powerful tools for translational research - Mehmet Nizamoglu; Mugdha M. Joglekar; Catarina R. Almeida; Anna-Karin Larsson Callerfelt; Isabelle Dupin; Olivier T. Guenat; Pauline Henrot; Lisette van Os; Jorge Otero; Linda Elowsson; Ramon Farre; Janette K. Burgess (European Respiratory Review, 2023)
Chronic lung diseases result from alteration and/or destruction of lung tissue, inevitably causing decreased breathing capacity and quality of life for patients. While animal models have paved the way for our understanding of pathobiology and the development of therapeutic strategies for disease management, their translational capacity is limited. There is, therefore, a well-recognised need for innovative in vitro models to reflect chronic lung diseases, which will facilitate mechanism investigation and the advancement of new treatment strategies. In the last decades, lungs have been modelled in healthy and diseased conditions using precision-cut lung slices, organoids, extracellular matrix-derived hydrogels and lung-on-chip systems. These three-dimensional models together provide a wide spectrum of applicability and mimicry of the lung microenvironment. While each system has its own limitations, their advantages over traditional two-dimensional culture systems, or even over animal models, increases the value of in vitro models. Generating new and advanced models with increased translational capacity will not only benefit our understanding of the pathobiology of lung diseases but should also shorten the timelines required for discovery and generation of new therapeutics. This article summarises and provides an outline of the European Respiratory Society research seminar “Innovative 3D models for understanding mechanisms underlying lung diseases: powerful tools for translational research”, held in Lisbon, Portugal, in April 2022. Current in vitro models developed for recapitulating healthy and diseased lungs are outlined and discussed with respect to the challenges associated with them, efforts to develop best practices for model generation, characterisation and utilisation of models and state-of-the-art translational potential.