Abstract
Invasion of the extracellular matrix is a critical step in the colonization of metastatic tumors. The invasion process is thought to be driven by both chemokine signaling and interactions between invading cancer cells and physical components of the metastatic niche, including endothelial cells that line capillary walls and serve as a barrier to both diffusion and invasion of the underlying tissue. Transwell chambers, a tool for generating artificial chemokine gradients to induce cell migration, have facilitated recent work to investigate the chemokine contributions to matrix invasion. These chambers, however, are poorly designed for imaging, which limits their use in investigating the physical cell-cell and cell-matrix interactions driving matrix invasion. Microfluidic devices offer a promising model in which the invasion process can be imaged. Many current designs, however, have limited surface areas and possess intricate geometries that preclude the use of standard staining protocols to visualize cells and matrix proteins. In this work, we present a novel microfluidic platform for imaging cell-cell and cell-matrix interactions driving metastatic cancer cell matrix invasion. Our model is applied to investigate how endothelial cell-secreted matrix proteins and the physical endothelial monolayer itself interact with invading metastatic breast cancer cells to facilitate invasion of an underlying type I collagen gel. The results show that matrix invasion of metastatic breast cancer cells is significantly enhanced in the presence of live endothelial cells. Probing this interaction further, our platform revealed that, while the fibronectin-rich matrix deposited by endothelial cells was not sufficient to drive invasion alone, metastatic breast cancer cells were able to exploit components of energetically inactivated endothelial cells to gain entry into the underlying matrix. These findings reveal novel cell-cell interactions driving a key step in the colonization of metastatic tumors and have important implications for designing drugs targeted at preventing cancer metastasis.