Dr. Griffith began by noting that cell-based devices have been used for more than 40 years to support organ/tissue replacement and to engineer cell biology. Although a great deal of effort has been made to improve devices such as membranes and nutrient gradients, many problems remain in the clinical application of these tools (e.g., immune reactions, challenges in getting high molecular-weight nutrients across membranes). As such, numerous approaches have yielded few commercial successes. For example, dialysis devices for the treatment of liver failure have generated ambiguous results for costly procedures. Given the challenges of using cell-based devices in the clinic, Dr. Griffith asked whether the engineering of the immune system would succeed first. From an engineering perspective, this strategy involves prevention (e.g., through a vaccine) rather than the construction of a cumbersome device.
Blueprints for engineering cell behavior can be constructed based on predictive frameworks. As an example, she discussed the engineering of cell migration, which is modulated by factors in the microenvironment. The speed of cellular migration can be predicted by the ratio of cell-substratum adhesivity to contractile force extension. Adhesion strength governs migration speed in a biphasic manner, and ingrowth into arginine/glycine/aspartate-modified scaffolds depends on the ligand density in a biphasic manner. As stem cells differentiate, however, possible differences in matrix stiffness in vivo or slow interstitial flow rates may affect the cells’ behavior. However, the behavior of dividing cells can be influenced by engineering approaches. For example, morphogen and inhibitor gradients can control branching morphogenesis (Nelson CM, et.al. Science 2006;314:298-300), which occurs where the concentration of inhibitor is lowest. Similar types of autocrine gradients govern differentiation and proliferation of stem cells in colony assays and in embryoid bodies. Also, long-term cellular growth is a function of the delivery of growth factors.
Dr. Griffith also noted that the engineering of cell behavior involves computational challenges. Numerous factors regulate differentiation and the ways that cells choose between potential fates. Because the combination of cytokine and matrix cues can predict an outcome, mathematical modeling is a useful predictive tool. However, it must be noted that modeling the complexity of organs in three dimensions incorporates additional challenges, as numerous phenomena influence the engineering considerations.
One attendee asked about the factors that must be considered when engineering cells to maintain liver function. Dr. Griffith noted that the liver performs many complex tasks, and a cell model must account for flow- and matrix-related mechanical stresses. Moreover, many diseases reflect an orchestration between non-parenchymal and parenchymal cells and matrix factors.