Tumor Spheroids Layered in an Imageable Cancer Environment (T-SLICE): a novel in vitro platform to study tumor biology
Cancer treatment is shifting towards precise medicine informed by tumor genetics and structural features. In recent years, it has become increasingly recognized that patient tumors--even those of the same tissue origin--can differ substantially between patients and respond differently to treatment. Given this, it is necessary to design therapies that target the heterogeneity of tumors. When investigating novel therapeutics in the laboratory, conventional cell culture models do not adequately recapitulate this heterogeneity and therefore may not accurately represent drug responses. Recent advances in miniaturized organ-on-a-chip models have been able to generate more complex microenvironments for in vitro studies. However, many of these models do not resemble the scale of clinically relevant tumors and pose a high barrier to use because they are technically complex. To facilitate mechanistic studies of the tumor microenvironment (TME), we designed T-SLICE, a chip made using commercially available elastomers and designed to fit in a standard 6-well plate. This simple 3-D tumor model incorporates microfluidic principles into a fully customizable TME, wherein cells drive the formation of biochemical gradients akin to those observed within a real tumor. In T-SLICE, spheroids are seeded atop a monolayer of fibroblasts situated between two closely spaced coverslips (300-700 {micro}m). The restrictive gap height limits the permeation of oxygen (O2) and hinders the removal of carbon dioxide (CO2) and metabolic waste, which leads to the generation of tumor-like hypoxic gradients. We demonstrate that T-SLICE establishes cell-driven oxygen gradients leading to the formation of a hypoxic core, with further impacts on cellular viability, mitochondrial membrane potential (MMP), and proliferation. T-SLICE cultures can be imaged live or fixed and stained for immunohistochemistry (IHC). These features of T-SLICE make it an accessible and faithful model of a tumors heterogeneity and open the possibility for more faithful testing of novel therapeutics in the context of a realistic TME.