Abstract

Invadopodia are dynamic actin-rich membrane protrusions that have been implicated in cancer cell invasion and metastasis. In addition, invasiveness of cancer cells is strongly correlated with invadopodia formation, which are observed during extravasation and colonization of metastatic cancer cells at secondary sites. However, quantitative understanding of the interaction of invadopodia with extracellular matrix (ECM) is lacking, and how invadopodia protrusion speed is associated with the frequency of protrusion-retraction cycles remains unknown. Here, we present a computational framework for the characterization of invadopodia protrusions which allows two way interactions between intracellular branched actin network and ECM fibers network. We have applied this approach to predicting the invasiveness of cancer cells by computationally knocking out actin-crosslinking molecules, such as α-actinin, filamin and fascin. The resulting simulations reveal distinct invadopodia dynamics with cycles of protrusion and retraction. Specifically, we found that (1) increasing accumulation of MT1-MMP at tips of invadopodia as the duration of protrusive phase is increased, and (2) the movement of nucleus toward the leading edge of the cell becomes unstable as duration of the retractile phase (or myosin turnover time) is longer than 1 min.

Details

Title
A computational modeling of invadopodia protrusion into an extracellular matrix fiber network
Author
Min-Cheol, Kim 1 ; Li, Ran 2 ; Abeyaratne Rohan 1 ; Kamm, Roger D 3 ; Harry, Asada H 1 

 Massachusetts Institute of Technology, Departments of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Massachusetts Institute of Technology, Biological Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts General Hospital Research Institute, Center for Systems Biology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924) 
 Massachusetts Institute of Technology, Departments of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, Biological Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2622384668
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.