Abstract

The bone and bone marrow are highly vascularized and structurally complex organs, and are sites for cancer and metastasis formation. In vitro models recapitulating bone- and bone marrow-specific functions, including vascularization, that are compatible with drug screening are highly desirable. Such models can bridge the gap between simplistic, structurally irrelevant two-dimensional (2D) in vitro models and the more expensive, ethically challenging in vivo models. This article describes a controllable three-dimensional (3D) co-culture assay based on engineered poly(ethylene glycol) (PEG) matrices for the generation of vascularized, osteogenic bone-marrow niches. The PEG matrix design allows the development of 3D cell cultures through a simple cell seeding step requiring no encapsulation, thus enabling the development of complex co-culture systems. Furthermore, the matrices are transparent and pre-cast onto glass-bottom 96-well imaging plates, rendering the system suitable for microscopy. For the assay described here, human bone marrow-derived mesenchymal stromal cells (hBM-MSCs) are cultured first until a sufficiently developed 3D cell network is formed. Subsequently, GFP-expressing human umbilical vein endothelial cells (HUVECs) are added. The culture development is followed by bright-field and fluorescence microscopy. The presence of the hBM-MSC network supports the formation of vascular-like structures that otherwise would not form and that remain stable for at least 7 days. The extent of vascular-like network formation can easily be quantified. This model can be tuned toward an osteogenic bone-marrow niche by supplementing the culture medium with bone morphogenetic protein 2 (BMP-2), which promotes the osteogenic differentiation of the hBM-MSCs, as assessed by increased alkaline phosphatase (ALP) activity at day 4 and day 7 of co-culture. This cellular model can be used as a platform for culturing various cancer cells and studying how they interact with bone- and bone marrow-specific vascular niches. Moreover, it is suitable for automation and high-content analyses, meaning it would enable cancer drug screening under highly reproducible culture conditions.

Full Text
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