Issue 29, 2016

Bioengineering three-dimensional culture model of human lung cancer cells: an improved tool for screening EGFR targeted inhibitors

Abstract

Cell models have been widely accepted to explore the mechanisms of tumorigenesis and predict drug response. Unfortunately, there is still a lack of accurate models that can highly recapitulate the important molecular events occurring in the human non-small-cell lung cancer patient's body. We hypothesize that the 3D microenvironment provided by collagen hydrogel would not only promote generation of tumor cultures that more closely resemble the in vivo tumor morphology, but also contribute to bioengineering a well-defined non-small-cell lung cancer culture model that potentially enhances the molecularly targeted drug evaluation. Here, we developed a more pathologically relevant, three-dimensional culture model of human lung cancer cells through embedding A549 cells within a collagen hydrogel. Our results showed that the collagen-embedded A549 cells formed numbers of cell aggregates that displayed good viability and more tissue-like morphology. A significantly increased expression level of EGF/EGFR was also observed in the 3D cultures. More importantly, the 3D culture had the ability to respond to treatment by the targeted inhibitor, as evidenced by its enhanced drug resistance and inhibited growth. Thus, this in vitro culture system effectively represents an improved culture model of human lung cancer and would potentially provide a robust tool for mechanism-based anti-lung cancer drug discovery and development.

Graphical abstract: Bioengineering three-dimensional culture model of human lung cancer cells: an improved tool for screening EGFR targeted inhibitors

Article information

Article type
Paper
Submitted
05 Jan 2016
Accepted
26 Feb 2016
First published
26 Feb 2016

RSC Adv., 2016,6, 24083-24090

Bioengineering three-dimensional culture model of human lung cancer cells: an improved tool for screening EGFR targeted inhibitors

D. Wang, W. Liu, J. Chang, X. Cheng, X. Zhang, H. Xu, D. Feng, L. Yu and X. Wang, RSC Adv., 2016, 6, 24083 DOI: 10.1039/C6RA00229C

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