Stress-dependent growth in breast cancer arises from a mechano-osmotic coupling and cell-sizing checkpoint

I Irish Senthilkumar (Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway) J Jef Vangheel (Mechatronics, Biostatistics, and Sensors (MeBIOS) division, Department of Biosystems, KU Leuven) V Vatsal Kumar (Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway) L Laoise McNamara (Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway) B Bart Smeets (Mechatronics, Biostatistics, and Sensors (MeBIOS) division, Department of Biosystems, KU Leuven) E Enda Howley (School of Computer Science and Data Science Institute, University of Galway) E Eoin McEvoy (Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway)

Abstract

Mechanoresponsive cell proliferation is a feature of growing tumors, despite the suppression of many other regulatory checkpoints in cancer, but the underlying cell-scale mechanisms driving this behavior have not yet been established. In this study, we propose a biophysical model for cell growth as governed by actively controlled osmolarity, which we integrate with a discrete particle framework to simulate growth and remodeling of breast cancer spheroids. Confinement and biomechanical feedback from the extracellular environment are analyzed through a neural-network-accelerated finite element solver. Combining the framework with experiments, our model reveals that stress-dependent spheroid growth can arise from a sizing checkpoint for mitosis. Under sufficient extracellular loading, cell growth is restricted by high hydrostatic forces in competition with osmotic pressure from biomolecule synthesis, which prevents cells from surpassing a critical volume. Our model provides insight into mechanosensitive growth arrest in breast cancer, potentially serving as a computational tool for analyzing growth in a wider range of normal and malignant biological tissues.

Article Details

Volume / Issue Vol. 123, Issue 10
Published March 10, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (7)

I

Irish Senthilkumar

Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway

J

Jef Vangheel

Mechatronics, Biostatistics, and Sensors (MeBIOS) division, Department of Biosystems, KU Leuven

V

Vatsal Kumar

Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway

L

Laoise McNamara

Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway

B

Bart Smeets

Mechatronics, Biostatistics, and Sensors (MeBIOS) division, Department of Biosystems, KU Leuven

E

Enda Howley

School of Computer Science and Data Science Institute, University of Galway

E

Eoin McEvoy

Biomedical Engineering and Institute for Health Discovery and Innovation, College of Science and Engineering, University of Galway