On-chip human microvasculature assay for visualization and quantification of tumor cell extravasation dynamics - Chen, Michelle B.; Fröse, Julia (Nature protocols, 2017)
Distant metastasis, which results in >90% of cancer-related deaths, is enabled by hematogenous dissemination of tumor cells via the circulation. This requires the completion of a sequence of complex steps including transit, initial arrest, extravasation, survival and proliferation. Increased understanding of the cellular and molecular players enabling each of these steps is key to uncovering new opportunities for therapeutic intervention during early metastatic dissemination. As a protocol extension, this article describes an adaptation to our existing protocol describing a microfluidic platform that offers additional applications. This protocol describes an in vitro model of the human microcirculation with the potential to recapitulate discrete steps of early metastatic seeding, including arrest, transendothelial migration and early micrometastases formation. The microdevice features self-organized human microvascular networks formed over 4-5 d, after which the tumor can be perfused and extravasation events are easily tracked over 72 h via standard confocal microscopy. Contrary to most in vivo and in vitro extravasation assays, robust and rapid scoring of extravascular cells, combined with high-resolution imaging, can be easily achieved because of the confinement of the vascular network to one plane close to the surface of the device. This renders extravascular cells clearly distinct and allows tumor cells of interest to be identified quickly as compared with those in thick tissues. The ability to generate large numbers of devices (∼36) per experiment further allows for highly parametric studies, which are required when testing multiple genetic or pharmacological perturbations. This is coupled with the capability for live tracking of single-cell extravasation events, allowing both tumor and endothelial morphological dynamics to be observed in high detail with a moderate number of data points.