Discovery of Metastatic Regulators using a Rapid and Quantitative Intravital Chick Chorioallantoic Membrane Model

Abstract

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be involved in differentially regulating cancer metastatic cascade genes and gene products dependent on the cancer type, tissue, and individual patient characteristics. These represent potentially important targets for genetic therapeutics and personalized medicine approaches. The development of rapid screening platforms is essential for the identification of these genetic targets. The chick chorioallantoic membrane (CAM) is a highly vascularized, collagen rich membrane located under the eggshell that allows for gas exchange in the developing embryo. Due to the location and vascularization of the CAM, we developed it as an intravital human cancer metastasis model that allows for robust human cancer cell xenografting and real-time imaging of cancer cell interactions with the collagen rich matrix and vasculature. Using this model, a quantitative screening platform was designed for the identification of novel drivers or suppressors of cancer metastasis. We transduced a pool of head and neck HEp3 cancer cells with a complete human genome shRNA gene library, then injected the cells, at low density, into the CAM vasculature. The cells proliferated and formed single-tumor cell colonies. Individual colonies that were unable to invade into the CAM tissue were visible as a compact colony phenotype and excised for identification of the transduced shRNA present in the cells. Images of individual colonies were evaluated for their invasiveness. Multiple rounds of selections were performed to decreases the rate of false positives. Individual, isolated cancer cell clones or newly engineered clones that express genes of interest were subjected to primary tumor formation assay or cancer cell vasculature co-option analysis. In summary we present a rapid screening platform that allows for anti-metastatic target identification and intravital analysis of a dynamic and complex cascade of events.