A High-Throughput Breast Tumor Model for Drug Testing

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with the highest likelihood of metastasis. TNBC is very difficult to treat with targeted therapies due to the lack of estrogen and progesterone receptors and non-amplified human epidermal growth factor.  Thus, chemotherapy has remained the standard of care. Considering the importance of cell invasion in metastasis and the prevalence of metastatic disease in TNBC, we asked to what extent chemotherapy drugs prevent invasion of TNBC cells into the surrounding matrix. To achieve this goal, we have developed a 3D tumor model that includes a tumor spheroid embedded in a defined extracellular matrix of human collagen. Using a robotic liquid handler, we automated the process to allow for high throughput testing of the efficacy of chemotherapeutic treatments. We used this model to test inhibitory effects of seven drugs, 5-FU, carboplatin, dactolisib, doxorubicin, gemcitabine, paclitaxel, and trametinib dose-dependently on collagen invasion of MDA-MB-231 and SUM159 TNBC cells. We quantified the invasiveness of cells from each spheroid from collapsed z-stack confocal microscope images by calculating the invading area of cells into the matrix and found an IC50 concentration for each drug used against each cell line.  We found that doxorubicin, paclitaxel, and trametinib were the most effective drugs and showed a maximum inhimbition of invasion of MDA-MB-231 by 94%, 96%, and 96%, and of SUM159 cells by 98%, 98%, and 90%, respectively. In future, we will leverage the modularity of this tumor model and investigate effects of other extracellular matrix components such as fibronectin and hyaluronic acid, and stromal cells such as cancer associated fibroblasts on invasiveness of TNBC cells and whether these drug compounds will be effective against TNBC invasion. These improvements combined with the use of patient derived cancer cells will help tailor the testing of various chemotherapeutics toward individual patients.