Biologically-relevant 3D Tumor Arrays: Treatment Response and the Importance of Stromal Partners

The development and translational potential of therapeutic strategies for cancer is limited, in part, by a lack of biological models that capture important aspects of tumor growth and treatment response. It is also becoming increasingly evident that no single treatment will be curative for this complex disease. Rationally-designed combination regimens that impact multiple targets provide the best hope of significantly improving clinical outcomes for cancer patients. Rapidly identifying treatments that cooperatively enhance treatment efficacy from the vast library of candidate interventions is not feasible, however, with current systems. There is a vital, unmet need to create cell-based research platforms that more accurately mimic the complex biology of human tumors than monolayer cultures, while providing the ability to screen therapeutic combinations more rapidly than animal models. We have developed a highly reproducible in vitro three-dimensional (3D) tumor model for micrometastatic ovarian cancer (OvCa), which in conjunction with quantitative image analysis routines to batch-process large datasets, serves as a high throughput reporter to screen rationally-designed combination regimens. We use this system to assess mechanism-based combination regimens with photodynamic therapy (PDT), which sensitizes OvCa to chemo and biologic agents, and has shown promise in clinic trials. We show that PDT synergistically enhances carboplatin efficacy in a sequence dependent manner. In printed heterocellular cultures we demonstrate that proximity of fibroblasts enhances 3D tumor growth and investigate co-cultures with endothelial cells. The principles described here could inform the design and evaluation of mechanism-based therapeutic options for a broad spectrum of metastatic solid tumors.