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Glioblastoma, from disease understanding towards optimal cell-based in vitro models
BACKGROUND: Glioblastoma (GBM) patients are notoriously difficult to treat and ultimately all succumb to disease. This unfortunate scenario motivates research into better characterizing and understanding this disease, and into developing novel research tools by which potential novel therapeutics and...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424171/ https://www.ncbi.nlm.nih.gov/pubmed/35763242 http://dx.doi.org/10.1007/s13402-022-00684-7 |
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author | Boccellato, Chiara Rehm, Markus |
author_facet | Boccellato, Chiara Rehm, Markus |
author_sort | Boccellato, Chiara |
collection | PubMed |
description | BACKGROUND: Glioblastoma (GBM) patients are notoriously difficult to treat and ultimately all succumb to disease. This unfortunate scenario motivates research into better characterizing and understanding this disease, and into developing novel research tools by which potential novel therapeutics and treatment options initially can be evaluated pre-clinically. Here, we provide a concise overview of glioblastoma epidemiology, disease classification, the challenges faced in the treatment of glioblastoma and current novel treatment strategies. From this, we lead into a description and assessment of advanced cell-based models that aim to narrow the gap between pre-clinical and clinical studies. Such in vitro models are required to deliver reliable and meaningful data for the development and pre-validation of novel therapeutics and treatments. CONCLUSIONS: The toolbox for GBM cell-based models has expanded substantially, with the possibility of 3D printing tumour tissues and thereby replicating in vivo tissue architectures now looming on the horizon. A comparison of experimental cell-based model systems and techniques highlights advantages and drawbacks of the various tools available, based on which cell-based models and experimental approaches best suited to address a diversity of research questions in the glioblastoma research field can be selected. |
format | Online Article Text |
id | pubmed-9424171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-94241712022-08-31 Glioblastoma, from disease understanding towards optimal cell-based in vitro models Boccellato, Chiara Rehm, Markus Cell Oncol (Dordr) Review BACKGROUND: Glioblastoma (GBM) patients are notoriously difficult to treat and ultimately all succumb to disease. This unfortunate scenario motivates research into better characterizing and understanding this disease, and into developing novel research tools by which potential novel therapeutics and treatment options initially can be evaluated pre-clinically. Here, we provide a concise overview of glioblastoma epidemiology, disease classification, the challenges faced in the treatment of glioblastoma and current novel treatment strategies. From this, we lead into a description and assessment of advanced cell-based models that aim to narrow the gap between pre-clinical and clinical studies. Such in vitro models are required to deliver reliable and meaningful data for the development and pre-validation of novel therapeutics and treatments. CONCLUSIONS: The toolbox for GBM cell-based models has expanded substantially, with the possibility of 3D printing tumour tissues and thereby replicating in vivo tissue architectures now looming on the horizon. A comparison of experimental cell-based model systems and techniques highlights advantages and drawbacks of the various tools available, based on which cell-based models and experimental approaches best suited to address a diversity of research questions in the glioblastoma research field can be selected. Springer Netherlands 2022-06-28 2022 /pmc/articles/PMC9424171/ /pubmed/35763242 http://dx.doi.org/10.1007/s13402-022-00684-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Boccellato, Chiara Rehm, Markus Glioblastoma, from disease understanding towards optimal cell-based in vitro models |
title | Glioblastoma, from disease understanding towards optimal cell-based in
vitro models |
title_full | Glioblastoma, from disease understanding towards optimal cell-based in
vitro models |
title_fullStr | Glioblastoma, from disease understanding towards optimal cell-based in
vitro models |
title_full_unstemmed | Glioblastoma, from disease understanding towards optimal cell-based in
vitro models |
title_short | Glioblastoma, from disease understanding towards optimal cell-based in
vitro models |
title_sort | glioblastoma, from disease understanding towards optimal cell-based in
vitro models |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424171/ https://www.ncbi.nlm.nih.gov/pubmed/35763242 http://dx.doi.org/10.1007/s13402-022-00684-7 |
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