Collagen-based three-dimensional culture microenvironment promotes epithelial to mesenchymal transition and drug resistance of human ovarian cancer in vitro.
RSC Adv
; 8(16): 8910-8919, 2018 Feb 23.
Article
em En
| MEDLINE
| ID: mdl-35539845
ABSTRACT
Ovarian cancer (OvCa) is a leading cause of mortality from gynecologic malignancy due to its disseminated peritoneal metastasis. The tumor microenvironment dominates epithelial-mesenchymal transition (EMT) development and impacts cancer metastasis as well as mediates drug resistance. Tumour cell interaction with the collagen I matrix is critical in OvCa development. To better understand the role of the collagen matrix and the underlying mechanisms in the early stage of OvCa invasion, we developed a three-dimensional (3D) culture model in vitro by embedding OvCa cells within collagen I to recreate the architecture of a solid tumour. Our results showed that tumour spheroids formed in the 3D collagen model displayed good viability and decreased growth rates, which partly recapitulated the growth behavior of in vivo tumour cells. Collagen I enhanced the OvCa cell motility/invasion capability by up-regulating the expression of MMPs and α5ß1 integrin. Moreover, highly invasive OvCa cells in collagen showed the overexpression of mesenchymal markers (N-cadherin, vimentin and fibronectin) and transcriptional factors (Snail and Slug). EMT-associated TGF-ß1/Smad4 and Wnt5b/ß-catenin signaling pathways were significantly up-regulated accordingly. Additionally, a remarkably enhanced drug resistance to chemotherapeutics was also detected in the 3D cultures. Collectively, the bioengineered 3D collagen models could recapitulate the in vivo tumour-like microenvironment and reflect some biological characteristics of human OvCa more accurately. The collagen I matrix promoted local invasion via EMT and enhanced the multidrug resistance in OvCa. This system might serve as a comprehensive in vitro model to better understand the manifold mechanisms of OvCa metastasis and also provide a robust tool for screening new anti-ovarian cancer therapeutics.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article