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Quantitative Measurement of Invadopodia-mediated Extracellular Matrix Proteolysis in Single and Multicellular Contexts
Published on: August 27, 2012
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Quantitative evaluation of single cell spread on collagen matrices.
E De Vlieghere1, G Wagemans1, S De Backer2
1Laboratory of Experimental Cancer Research, Ghent University, Belgium; Cancer Research Institute Ghent (CRIG), Ghent University, Belgium.
Experimental Cell Research
|October 25, 2016
Summary
A new software, Morphology Analysis Software (MAS), objectively quantifies cell spreading on collagen, overcoming manual scoring limitations. This tool aids in cancer research and drug screening by analyzing cell morphology changes and migration potential.
Area of Science:
- Cell biology
- Biophysics
- Cancer research
Background:
- Cell morphology changes in response to environmental cues.
- Quantitative evaluation of single cell spread on extracellular matrices is crucial in cancer research.
- Manual scoring of cellular spread suffers from inter- and intra-observer variation.
Purpose of the Study:
- To develop and validate the Morphology Analysis Software (MAS) for objective and standardized scoring of cell morphology.
- To assess the utility of MAS in a functional screening assay for identifying modulators of cell spreading.
- To correlate cell spreading with migration potential and investigate the role of EGFR signaling.
Main Methods:
- MAS analyzes phase-contrast images of cells on type I collagen gels.
- The software uses four parameters: cellular extension, cell area, eccentricity, and circularity.
- Functional screening involved six cytokines, xCELLigence migration assays, and EGFR signaling pathway inhibitors.
Main Results:
- MAS provides scores equivalent to expert observers but is faster, more objective, and standardized.
- Transforming growth factor-alpha (TGFα) was identified as a stimulator of HCT8/E11 and SK-BR-3 cell spreading.
- TGFα-induced cell spreading correlated with increased migration potential and was inhibited by EGFR pathway inhibitors.
Conclusions:
- Morphology classification of unlabeled cells is a valuable readout for cancer cell properties.
- MAS software offers a robust, objective, and efficient tool for cell morphology analysis.
- MAS has significant potential for application in drug screening strategies for cancer therapies.
