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A Biomimetic High Throughput Model of Cancer Cell Spheroid Dissemination onto Aligned Fibrillar Collagen.

Authors :
Ibrahim H
Thorpe SD
Paukshto M
Zaitseva TS
Moritz W
Rodriguez BJ
Source :
SLAS technology [SLAS Technol] 2022 Aug; Vol. 27 (4), pp. 267-275. Date of Electronic Publication: 2022 May 16.
Publication Year :
2022

Abstract

Cell dissemination during tumor development is a characteristic of cancer metastasis. Dissemination from three-dimensional spheroid models on extracellular matrices designed to mimic tissue-specific physiological microenvironments may allow us to better elucidate the mechanism behind cancer metastasis and the response to therapeutic agents. The orientation of fibrillar collagen plays a key role in cellular processes and mediates metastasis through contact-guidance. Understanding how cells migrate on aligned collagen fibrils requires in vitro assays with reproducible and standardized orientation of collagen fibrils on the macro-to-nanoscale. Herein, we implement a spheroid-based migration assay, integrated with a fibrillar type I collagen matrix, in a manner compatible with high throughput image acquisition and quantitative analysis. The migration of highly proliferating U2OS osteosarcoma cell spheroids onto an aligned fibrillar type I collagen matrix was quantified. Cell dissemination from the spheroid was polarized with increased invasion in the direction of fibril alignment. The resulting area of cell dissemination had an aspect ratio of 1.2 ± 0.1 and an angle of maximum invasion distance of 5° ± 44° relative to the direction of collagen fibril alignment. The assay described here can be applied to a fully automated imaging and analysis pipeline for the assessment of tumor cell migration with high throughput screening.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2022. Published by Elsevier Inc.)

Details

Language :
English
ISSN :
2472-6311
Volume :
27
Issue :
4
Database :
MEDLINE
Journal :
SLAS technology
Publication Type :
Academic Journal
Accession number :
35584761
Full Text :
https://doi.org/10.1016/j.slast.2022.05.001