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Cancer cell sedimentation in 3D cultures reveals active migration regulated by self-generated gradients and adhesion sites.

Authors :
Dimitriou NM
Flores-Torres S
Kyriakidou M
Kinsella JM
Mitsis GD
Source :
PLoS computational biology [PLoS Comput Biol] 2024 Jun 11; Vol. 20 (6), pp. e1012112. Date of Electronic Publication: 2024 Jun 11 (Print Publication: 2024).
Publication Year :
2024

Abstract

Cell sedimentation in 3D hydrogel cultures refers to the vertical migration of cells towards the bottom of the space. Understanding this poorly examined phenomenon may allow us to design better protocols to prevent it, as well as provide insights into the mechanobiology of cancer development. We conducted a multiscale experimental and mathematical examination of 3D cancer growth in triple negative breast cancer cells. Migration was examined in the presence and absence of Paclitaxel, in high and low adhesion environments and in the presence of fibroblasts. The observed behaviour was modeled by hypothesizing active migration due to self-generated chemotactic gradients. Our results did not reject this hypothesis, whereby migration was likely to be regulated by the MAPK and TGF-β pathways. The mathematical model enabled us to describe the experimental data in absence (normalized error<40%) and presence of Paclitaxel (normalized error<10%), suggesting inhibition of random motion and advection in the latter case. Inhibition of sedimentation in low adhesion and co-culture experiments further supported the conclusion that cells actively migrated downwards due to the presence of signals produced by cells already attached to the adhesive glass surface.<br />Competing Interests: The authors have declared that no competing interests exist.<br /> (Copyright: © 2024 Dimitriou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Details

Language :
English
ISSN :
1553-7358
Volume :
20
Issue :
6
Database :
MEDLINE
Journal :
PLoS computational biology
Publication Type :
Academic Journal
Accession number :
38861575
Full Text :
https://doi.org/10.1371/journal.pcbi.1012112