3D and 4D Tumorigenesis Model for the Quantitative Analysis of Cancer Cell Behavior and Screening for Anticancer Drugs

Abstract

Cancer cells from cell lines and tumor biopsy tissue undergo aggregation and aggregate coalescence when dispersed in a 3D Matrigel™ matrix. Coalescence is a dynamic process mediated by a subset of cells within the population of cancer cells. In contrast, non-tumorigenic cells from normal cell lines and normal tissues do not aggregate or coalesce, nor do they possess the motile cell types that orchestrate coalescence of cancer cells. Therefore, coalescence is a cancer cell-specific phenotype that may drive tumor growth in vivo, especially in cases of field cancerization. Here, we describe a simple 3D tumorigenesis model that takes advantage of the coalescence capabilities of cancer cells and uses this feature as the basis for a screen for treatments that inhibit tumorigenesis. The screen is especially useful in testing monoclonal antibodies that target cell-cell interactions, cell-matrix interactions, cell adhesion molecules, cell surface receptors, and general cell surface markers. The model can also be used for 2D imaging in a 96-well plate for rapid screening and is adaptable for 3D high-resolution assessment. In the latter case, we show how the 3D model can be optically sectioned with differential interference contrast (DIC) optics, then reconstructed in 4D and quantitatively analyzed by computer-assisted methods, or, alternatively, imaged with confocal microscopy for 4D quantitative analysis of cancer cell interactions with normal cells within the tumor microenvironment. We demonstrate reconstructions and quantitative analyses using the advanced image analysis software J3D-DIAS 4.2, in order to illustrate the types of detailed phenotypic characterizations that have proven useful. Other software packages may be able to perform similar types of analyses.