3D collagen alignment limits protrusions to enhance breast cancer cell persistence.

Riching KM, Cox BL, Salick MR, Pehlke C, Riching AS, Ponik SM, Bass BR, Crone WC, Jiang Y, Weaver AM, Eliceiri KW, Keely PJ
Biophys J. 2014 107 (11): 2546-58

PMID: 25468334 · PMCID: PMC4255204 · DOI:10.1016/j.bpj.2014.10.035

Patients with mammographically dense breast tissue have a greatly increased risk of developing breast cancer. Dense breast tissue contains more stromal collagen, which contributes to increased matrix stiffness and alters normal cellular responses. Stromal collagen within and surrounding mammary tumors is frequently aligned and reoriented perpendicular to the tumor boundary. We have shown that aligned collagen predicts poor outcome in breast cancer patients, and postulate this is because it facilitates invasion by providing tracks on which cells migrate out of the tumor. However, the mechanisms by which alignment may promote migration are not understood. Here, we investigated the contribution of matrix stiffness and alignment to cell migration speed and persistence. Mechanical measurements of the stiffness of collagen matrices with varying density and alignment were compared with the results of a 3D microchannel alignment assay to quantify cell migration. We further interpreted the experimental results using a computational model of cell migration. We find that collagen alignment confers an increase in stiffness, but does not increase the speed of migrating cells. Instead, alignment enhances the efficiency of migration by increasing directional persistence and restricting protrusions along aligned fibers, resulting in a greater distance traveled. These results suggest that matrix topography, rather than stiffness, is the dominant feature by which an aligned matrix can enhance invasion through 3D collagen matrices.

Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

MeSH Terms (9)

Breast Neoplasms Cell Line, Tumor Cell Movement Collagen Extracellular Matrix Female Gels Humans Models, Biological

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