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  • A method to investigate the anti-metabolic activity of anti-cancer agents on ovarian cancer cells cultured in a 96-well high throughput format.

A method to investigate the anti-metabolic activity of anti-cancer agents on ovarian cancer cells cultured in a 96-well high throughput format.

Journal of ovarian research (2015-07-05)
Simon J Hogg, John J Evans, Peter H Sykes, Kenny Chitcholtan
ABSTRACT

An early step of advanced ovarian cancer begins when floating cancerous cells as single cells or small clusters grow on the peritoneal surface. This surface is rich in extracellular matrix (ECM) proteins, which have profound effects on cellular behaviour and can facilitate cancer progression. Subsequently, this ECM may alter cellular metabolism making cancer cells susceptible to chemotherapeutic agents differently. Therefore, generating a cell culture tool in vitro that includes the interaction between ECM and cancer cells will facilitate our understanding of how cancer cells behave during cancer treatment. There is some evidence to suggest that in an in vitro model that includes ECM components such as collagens will provide a better predictive tool for drug evaluation than a traditional cell monolayer (2D) culture model. As a proof -of- concept, we made a collagen gel in a 96-well plate format and utilised this to evaluate the efficacy of clinical cytotoxic drugs, a targeted drug, and food compounds in single and combination treatments. The primary endpoints were to measure the reduction of cellular metabolism and secretion of vascular endothelial growth factor (VEGF). The invasive capacity of cancer cells was observed in collagen gels and it was cell line-dependent. The responses to drugs were prominently observed in collagen gels, but they had little effect on 2D cell monolayers. These responses were cell line- and type of drug-dependent. The collagen gel in a 96 well plate format was easy to set up and could have potential to identify drug sensitivity in the clinical management of women with platinum resistant ovarian cancer.

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