Abstract 324: High throughput triculture: A breast cancer spheroid model for drug screening

Abstract

Abstract Many drugs that show promise in preclinical evaluation fail miserably during clinical trials, and the inability of current preclinical models to properly predict drug response may be attributed to oversimplified or non-existent tumor microenvironments. To provide a more physiologically predictive model for drug screening, we have developed an in vitro, 384 well, triculture system that presents key chemical (i.e. low pH, low glucose, low oxygen), extracellular matrix (ECM), and cellular (tumor cells, stromal cells and endothelial cells) attributes of tumor tissues. By using ECM proteins, we can promote the proper physiology for each of these cell types in triculture. To evaluate interactions between each cell type, they are fluorescently labeled with fluorophores with different excitation and emission spectra; MCF7 and MDA-MB-231 human breast cancer cell lines express a red fluorescence protein, while human umbilical vein endothelial cells (HUVECs) and human adipose-derived mesenchymal stem cells (hMSCs) are labeled with stable lipophilic membrane dyes. Breast tumor microtissues spontaneously assemble when breast cancer cells are co-cultured with hMSCs under low adhesion conditions. Once formed, these microtissues are deposited onto preformed tubule networks comprised of HUVECs and hMSCs and are embedded within a hydrogel composed of ECM proteins. Cellular interactions and dissemination are monitored via fluorescence microscopy, and cell proliferation of the breast cancer cells is quantified using a fluorescence plate reader. The breast cancer cells exhibit cell-cell interactions with endothelial tubules and stromal cells, forming microtissues. Furthermore, the response to anti-cancer drugs, paclitaxel and fluorouracil, in an in vitro triculture system is similar to the response for the same drugs in xenografts model, unlike 2D or 3D monoculture. This high throughput triculture cancer model will provide more insight into pathological mechanisms and can better predict response to anti-cancer drug treatment. Citation Format: Gabriel J. Benton, Gerald DeGray, Irina Arnaoutova, Hynda K. Kleinman, Jay George. High throughput triculture: A breast cancer spheroid model for drug screening. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 324. doi:10.1158/1538-7445.AM2015-324