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Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines.

Authors :
Paul Van Liedekerke
Johannes Neitsch
Tim Johann
Kevin Alessandri
Pierre Nassoy
Dirk Drasdo
Source :
PLoS Computational Biology, Vol 15, Iss 3, p e1006273 (2019)
Publication Year :
2019
Publisher :
Public Library of Science (PLoS), 2019.

Abstract

Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite experimental response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized by measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with different growth kinetics from the growth kinetics in absence of external stress. Our model simulation results suggest a generic, even quantitatively same, growth response of cell populations upon externally applied mechanical stress, as it can be quantitatively predicted using the same growth progression function.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
1553734X and 15537358
Volume :
15
Issue :
3
Database :
Directory of Open Access Journals
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.fbcedb38305340d3bc0c27c900410be1
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pcbi.1006273