Three-dimensional prostate tumor model based on a hyaluronic acid-alginate hydrogel for evaluation of anti-cancer drug efficacy
In vitro cell-based assays are widely applied to evaluate anti-cancer drug efficacy. However, the conventional approaches are mostly based on two-dimensional (2D) culture systems, making it difficult to recapitulate the in vivo tumor scenario because of spatial limitations. Here, we develop an in vi...
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Published in | Journal of biomaterials science. Polymer ed. Vol. 28; no. 14; pp. 1603 - 1616 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Taylor & Francis
01.10.2017
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | In vitro cell-based assays are widely applied to evaluate anti-cancer drug efficacy. However, the conventional approaches are mostly based on two-dimensional (2D) culture systems, making it difficult to recapitulate the in vivo tumor scenario because of spatial limitations. Here, we develop an in vitro three-dimensional (3D) prostate tumor model based on a hyaluronic acid (HA)-alginate hybrid hydrogel to bridge the gap between in vitro and in vivo anticancer drug evaluations. In situ encapsulation of PCa cells was achieved by mixing HA and alginate aqueous solutions in the presence of cells and then crosslinking with calcium ions. Unlike in 2D culture, cells were found to aggregate into spheroids in a 3D matrix. The expression of epithelial to mesenchyme transition (EMT) biomarkers was found to be largely enhanced, indicating an increased invasion and metastasis potential in the hydrogel matrix. A significant up-regulation of proangiogenic growth factors (IL-8, VEGF) and matrix metalloproteinases (MMPs) was observed in 3D-cultured PCa cells. The results of anti-cancer drug evaluation suggested a higher drug tolerance within the 3D tumor model compared to conventional 2D-cultured cells. Finally, we found that the drug effect within the in vitro 3D cancer model based on HA-alginate matrix exhibited better predictability for in vivo drug efficacy. |
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ISSN: | 0920-5063 1568-5624 |
DOI: | 10.1080/09205063.2017.1338502 |