Abstract

Traction force microscopy (TFM) is an important family of techniques used to measure and study the role of cellular traction forces (CTFs) associated with many biological processes. However, current standard TFM methods rely on imaging techniques that do not provide the experimental capabilities necessary to study CTFs within 3D collective and dynamic systems embedded within optically scattering media. Traction force optical coherence microscopy (TF-OCM) was developed to address these needs, but has only been demonstrated for the study of isolated cells embedded within optically clear media. Here, we present computational 4D-OCM methods that enable the study of dynamic invasion behavior of large tumor spheroids embedded in collagen. Our multi-day, time-lapse imaging data provided detailed visualizations of evolving spheroid morphology, collagen degradation, and collagen deformation, all using label-free scattering contrast. These capabilities, which provided insights into how stromal cells affect cancer progression, significantly expand access to critical data about biophysical interactions of cells with their environment, and lay the foundation for future efforts toward volumetric, time-lapse reconstructions of collective CTFs with TF-OCM.

Details

Title
Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen
Author
Mulligan, Jeffrey A 1 ; Lu, Ling 2 ; Nichaluk, Leartprapun 2 ; Fischbach, Claudia 3 ; Adie, Steven G 2 

 Cornell University, School of Electrical and Computer Engineering, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X); Cornell University, Nancy E. and Peter C. Meinig School of Biomedical Engineering, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X) 
 Cornell University, Nancy E. and Peter C. Meinig School of Biomedical Engineering, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X) 
 Cornell University, Nancy E. and Peter C. Meinig School of Biomedical Engineering, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X); Cornell University, Kavli Institute at Cornell for Nanoscale Science, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2485324722
Copyright
© The Author(s) 2021. 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.