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https://hdl.handle.net/1822/78568
Title: | The tumor microenvironment: an introduction to the development of microfluidic devices |
Author(s): | Kundu, Banani Caballero, David Abreu, Catarina M. Reis, R. L. Kundu, Subhas C |
Keywords: | Biosensors Microfluidics Tumor microenvironment Three-dimensions In vitro tumor models Metastasis |
Issue date: | Jun-2022 |
Publisher: | Springer |
Journal: | Advances in Experimental Medicine and Biology |
Citation: | Kundu B., Caballero D., Abreu C. M., Reis R. L., Kundu S. C. The Tumor Microenvironment: An Introduction to the Development of Microfluidic Devices, Microfluidics and Biosensors in Cancer Research. Advances in Experimental Medicine and Biology, Vol. 1379, pp. 115–138, doi:10.1007/978-3-031-04039-9_5, 2022 |
Abstract(s): | The tumor microenvironment (TME) is like the Referee of a soccer match who has constant eyes on the activity of all players, such as cells, acellular stroma components, and signaling molecules for the successful completion of the game, that is, tumorigenesis. The cooperation among all the "team members" determines the characteristics of tumor, such as the hypoxic and acidic niche, stiffer mechanical properties, or dilated vasculature. Like in soccer, each TME is different. This heterogeneity makes it challenging to fully understand the intratumor dynamics, particularly among different tumor subpopulations and their role in therapeutic response or resistance. Further, during metastasis, tumor cells can disseminate to a secondary organ, a critical event responsible for approximately 90% of the deaths in cancer patients. The recapitulation of the rapidly changing TME in the laboratory is crucial to improve patients' prognosis for unraveling key mechanisms of tumorigenesis and developing better drugs. Hence, in this chapter, we provide an overview of the characteristic features of the TME and how to model them, followed by a brief description of the limitations of existing in vitro platforms. Finally, various attempts at simulating the TME using microfluidic platforms are highlighted. The chapter ends with the concerns that need to be addressed for designing more realistic and predictive tumor-on-a-chip platforms. |
Type: | Book part |
URI: | https://hdl.handle.net/1822/78568 |
ISBN: | 978-3-031-04038-2 |
e-ISBN: | 978-3-031-04039-9 |
DOI: | 10.1007/978-3-031-04039-9_5 |
ISSN: | 0065-2598 |
Publisher version: | https://link.springer.com/chapter/10.1007/978-3-031-04039-9_5#chapter-info |
Peer-Reviewed: | yes |
Access: | Restricted access (UMinho) |
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File | Description | Size | Format | |
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20806-ch5-banani-kundu.pdf Restricted access | 860,05 kB | Adobe PDF | View/Open |