Unmet Need: Metastasis is by far the main cause of cancer lethality; the majority of cancer death from solid tumors are due to metastatic cancer spread from the tumor to other sites in the body. Key features of metastatic cascade are invasion, migration, and epithelial-mesenchymal transition (EMT). There are models of cancer cell metastasis but they omit such initial steps of metastatic cascade so potential molecular targets may also be missed. Lack of an in vitro model of metastasis is a major impediment in understanding its biology and identification of potential therapeutic targets.
Technology Overview: JHU inventors have created an in vitro model which displays the signatures of metastatic phenotype such as migration, invasiveness, chemoresistance and expression of cancer stem-cell markers. This technique includes development of anchorage-independent multicellular spheroids and their spontaneous reversal into monolayer. The most striking feature of the current reversed-spheroid monolayer model is the ability to retain EMT markers during reversal process, and the demonstration of metastatic phenotype for migration/invasion. Furthermore, the increased expression of CSC markers in the reversed-spheroid monolayer underscores both the tumorigenic potential as well as chemoresistance.
This model could improve the screening efficiency of anti-metastatic agents. This invention could be developed to an assay/kit for screening cancer agents against metastatic cancer,
This novel approach for modeling metastasis is a relatively easy procedure. There is a fast growing market for 3D cell culture products, and likely good market acceptance because spheroids model are one of the most promising 3D culture platforms.
Stage of development: The inventive method includes the culturing conditions and techniques for producing the reversed-spheroid monolayer. JHU is seeking a partner to complete validation studies and any customization to a commercial kit useful for an anti-cancer drug screen.
Publications: Sci Rep. 2014 Oct 29;4:6816
