Development of a stacked, porous silk scaffold neuroblastoma model for investigating spatial differences in cell and...

Development of in vitro, preclinical cancer models that contain cell-driven microenvironments remains a challenge. Engineering of millimeter-scale, in vitro tumor models with spatially distinct regions that can be independently assessed to study tumor microenvironments has been limited. Here, we report the use of porous silk scaffolds to generate a high cell density neuroblastoma (NB) model that can spatially recapitulate changes resulting from cell and diffusion driven changes. Using COMSOL modeling, a scaffold holder design that facilitates stacking of thin, 200 μm silk scaffolds into a thick, bulk millimeter-scale tumor model (2, 4, 6, and 8 stacked scaffolds) and supports cell-driven oxygen gradients was developed. Cell-driven oxygen gradients were confirmed through pimonidazole staining. Post-culture, the stacked scaffolds were separated for analysis on a layer-by-layer basis. The analysis of each scaffold layer demonstrated decreasing DNA and increasing expression of hypoxia related genes (VEGF, CAIX, and GLUT1) from the exterior scaffolds to the interior scaffolds. Furthermore, the expression of hypoxia related genes at the interior of the stacks was comparable to that of a single scaffold cultured under 1% O₂ and at the exterior of the stacks was comparable to that of a single scaffold cultured under 21% O₂. The four-stack scaffold model underwent further evaluation to determine if a hypoxia activated drug, tirapazamine, induced reduced cell viability within the internal stacks (region of reduced oxygen) as compared with the external stacks. Decreased DNA content was observed in the internal stacks as compared to the external stacks when treated with tirapazamine, which suggests the internal scaffold stacks had higher levels of hypoxia than the external scaffolds. This stacked silk scaffold system presents a method for creating a single culture model capable of generating controllable cell-driven microenvironments through different stacks that can be individually assessed and used for drug screening.