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Innovative three-dimensional models for understanding mechanisms underlying lung diseases : powerful tools for translational research

Nizamoglu, Mehmet ; Joglekar, Mugdha M. ; Almeida, Catarina R. ; Callerfelt, Anna Karin Larsson LU orcid ; Dupin, Isabelle ; Guenat, Olivier T. ; Henrot, Pauline ; van Os, Lisette ; Otero, Jorge and Elowsson, Linda LU , et al. (2023) In European Respiratory Review 32(169).
Abstract

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.... (More)

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.

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organization
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type
Contribution to journal
publication status
published
subject
in
European Respiratory Review
volume
32
issue
169
article number
230042
publisher
European Respiratory Society
external identifiers
  • pmid:37495250
  • scopus:85165878104
ISSN
0905-9180
DOI
10.1183/16000617.0042-2023
language
English
LU publication?
yes
id
2781db9c-42dd-4be0-9a5c-066a2bbbb4e6
date added to LUP
2023-10-24 14:54:54
date last changed
2024-04-19 02:50:58
@article{2781db9c-42dd-4be0-9a5c-066a2bbbb4e6,
  abstract     = {{<p>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.</p>}},
  author       = {{Nizamoglu, Mehmet and Joglekar, Mugdha M. and Almeida, Catarina R. and Callerfelt, Anna Karin Larsson and Dupin, Isabelle and Guenat, Olivier T. and Henrot, Pauline and van Os, Lisette and Otero, Jorge and Elowsson, Linda and Farre, Ramon and Burgess, Janette K.}},
  issn         = {{0905-9180}},
  language     = {{eng}},
  month        = {{09}},
  number       = {{169}},
  publisher    = {{European Respiratory Society}},
  series       = {{European Respiratory Review}},
  title        = {{Innovative three-dimensional models for understanding mechanisms underlying lung diseases : powerful tools for translational research}},
  url          = {{http://dx.doi.org/10.1183/16000617.0042-2023}},
  doi          = {{10.1183/16000617.0042-2023}},
  volume       = {{32}},
  year         = {{2023}},
}