(357d) Effects of Intratumoral Heterogeneity on Metastasis of Triple-Negative Breast Cancer Cells

Metastasis is responsible for most cancer-related deaths and evaluating the risk of metastasis is essential for predicting a patient’s prognosis. Predicting the course of a patient’s disease is challenging in the context of triple negative breast cancer (TNBC), a highly heterogeneous disease in which individual cells can undergo modifications at the genomic, epigenomic, transcriptomic, and/or proteomic levels. These modifications can give rise to distinct clonal subpopulations within a tumor, yielding intratumoral heterogeneity. For example, one subpopulation may appear more likely to invade into the surrounding tissue while another subpopulation may appear more noninvasive. Our lab has derived both noninvasive, epithelial-like and invasive, mesenchymal-like clonal subpopulations from a mouse TNBC cell line. We have been investigating the ability of TNBC cells within epithelial-like, mesenchymal-like, and heterogeneous tumors to invade into the surrounding matrix and escape into a nearby cavity within an engineered tumor model. Our data show that epithelial-like tumors invade and escape more slowly than mesenchymal-like or heterogeneous tumors do. Additionally, the presence of as few as one mesenchymal-like cell for every nine epithelial-like cells is sufficient to alter tumor morphology and increase the rate of invasion and escape. Interestingly, the effects of mesenchymal-like cells are not due to paracrine signaling and adding conditioned medium from mesenchymal-like tumors to epithelial-like tumors does not change the rate of invasion or escape. We are using this engineered tumor model to test whether specifically reducing the number of mesenchymal-like cells via a pharmacological treatment affects the rate of invasion and escape of a heterogeneous tumor. To investigate the metastatic capacity of the clonal populations in vivo, we xenografted tumor cells onto the chick chorioallantoic membrane and used a novel quantitative reverse transcription polymerase chain reaction-based method to detect murine cancer cells in the chick embryonic tissues. Using this engineered tumor model and an in ovo model to examine the behaviors of homogeneous and heterogeneous cell populations has enhanced our understanding of the effects of intratumoral heterogeneity on metastatic potential. This understanding is necessary as physicians move towards more accurately predicting a patient’s prognosis and developing personalized treatment plans.

Research Interests

I am passionate about improving our understanding of cancer, specifically of the factors that contribute to the risk of metastasis in patients. I am interested in using in vitro and in vivo models to study how the composition of tumors and the tumor microenvironment affect tumor progression, metastatic potential, and chemosensitivity. I am also interested in the effects of metabolism and diet on primary tumors and the risk of metastasis.