Background: Increasing evidence shows that the cancer microenvironment affects both tumorigenesis and the response of cancer to drug treatment. Therefore in vitro models that selectively reflect characteristics of the in vivo environment are greatly needed. Current methods allow us to screen the effect of extrinsic parameters such as matrix composition and to model the complex and three-dimensional (3D) cancer environment. However, 3D models that reflect characteristics of the in vivo environment are typically too complex and do not allow the separation of discrete extrinsic parameters.