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Digital twinning of Cellular Capsule Technology: Emerging outcomes from the perspective of porous media mechanics

Article dans une revue avec comité de lecture
Author
URCUN, Stéphane
1001017 Institut de Biomécanique Humaine Georges Charpak [IBHGC]
ROHAN, Pierre-Yves
1001017 Institut de Biomécanique Humaine Georges Charpak [IBHGC]
SKALLI, Wafa
1001017 Institut de Biomécanique Humaine Georges Charpak [IBHGC]
NASSOY, Pierre
300036 Institut d'Optique Graduate School [IOGS]
BORDAS, Stéphane P. A.
366875 University of Luxembourg [Luxembourg]
SCIUMÈ, Giuseppe
1002421 Institut de Mécanique et d'Ingénierie [I2M]

URI
http://hdl.handle.net/10985/21320
DOI
10.1371/journal.pone.0254512
Date
2021
Journal
PLOS ONE

Abstract

Spheroids encapsulated within alginate capsules are emerging as suitable in vitro tools to investigate the impact of mechanical forces on tumor growth since the internal tumor pressure can be retrieved from the deformation of the capsule. Here we focus on the particular case of Cellular Capsule Technology (CCT). We show in this contribution that a modeling approach accounting for the triphasic nature of the spheroid (extracellular matrix, tumor cells and interstitial fluid) offers a new perspective of analysis revealing that the pressure retrieved experimentally cannot be interpreted as a direct picture of the pressure sustained by the tumor cells and, as such, cannot therefore be used to quantify the critical pressure which induces stress-induced phenotype switch in tumor cells. The proposed multiphase reactive poro-mechanical model was cross-validated. Parameter sensitivity analyses on the digital twin revealed that the main parameters determining the encapsulated growth configuration are different from those driving growth in free condition, confirming that radically different phenomena are at play. Results reported in this contribution support the idea that multiphase reactive poro-mechanics is an exceptional theoretical framework to attain an in-depth understanding of CCT experiments, to confirm their hypotheses and to further improve their design.

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