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Location, location, location
When buying a house, we research neighborhoods and carefully choose an environment that fits our personality. So why does a “one-material-fits-all” mentality dominate when choosing a biomaterial for various clinical scenarios? Now, Oliva et al. attempt to shift that mindset by defining the molecular properties of diseased-tissue microenvironments and then tuning a dendrimer/dextran–based material to thrive differentially under selected clinical conditions. By measuring tissue modifications and material performance—in two gut diseases and under varying degrees of severity—the authors unveiled contextual effects on the compatibility between a biomaterial and its neighborhood. These findings drove development of a predictive paradigm that matches a material with its model home—a practice that may one day translate to improved clinical outcomes.
Abstract
A “one material fits all” mindset ignores profound differences in target tissues that affect their responses and reactivity. Yet little attention has been paid to the role of diseased tissue on material performance, biocompatibility, and healing capacity. We assessed material-tissue interactions with a prototypical adhesive material based on dendrimer/dextran and colon as a model tissue platform. Adhesive materials have high sensitivity to changes in their environment and can be exploited to probe and quantify the influence of even subtle modifications in tissue architecture and biology. We studied inflammatory colitis and colon cancer and found not only a difference in adhesion related to surface chemical interactions but also the existence of a complex interplay that determined the overall dendrimer/dextran biomaterial compatibility. Compatibility was contextual, not simply a constitutive property of the material, and was related to the extent and nature of immune cells in the diseased environment present before material implantation. We then showed how to use information about local alterations of the tissue microenvironment to assess disease severity. This in turn guided us to an optimal dendrimer/dextran formulation choice using a predictive model based on clinically relevant conditions.
- Copyright © 2015, American Association for the Advancement of Science
