Characterizing the Macrophage Response to Immunomodulatory Biomaterials Through Gene Set Analyses

Impact statement Immunomodulatory biomaterials that target macrophage phenotype are a promising approach for promoting tissue repair. However, due to the complexity of macrophage behavior as they interact with biomaterials, there is a need for improved methods for their characterization. We demonstrate the utility of gene set analyses to characterize the macrophage response to biomaterials using the classic M1 and M2a phenotypes as a reference, and suggest that this method may be adopted as a useful method for characterizing macrophage phenotype in a way that is practical, thorough, objective, and tailorable to particular phenotypes of interest. This methodology allows for identification of hybrid phenotypes and incorporation of additional phenotypes as their set of markers is established. Due to the variety of applications, this methodology is likely to be useful for engineers, scientists, and clinicians. The primary regulators of the innate immune response to implanted biomaterials are macrophages, which change phenotype over time to regulate multiple phases of the tissue repair process. Immunomodulatory biomaterials that target macrophage phenotype are a promising approach for promoting tissue repair. Although expression of multiple markers has been widely used to characterize macrophage phenotype, the complexity of the macrophage response to biomaterials makes interpretation difficult. The aim of this study was to put forth an objective method to characterize macrophage phenotype with respect to specific biological processes or standard phenotypes of interest. We investigated the utility of gene set analyses to analyze macrophages as they respond to model biomaterials in comparison to reference M1 and M2a macrophage phenotypes. Primary human macrophages were seeded onto crosslinked collagen scaffolds with or without adsorption of the proinflammatory cytokine interferon-gamma (IFNg). Gene expression of a custom-curated panel of 48 genes, representing the M1 and M2a gene signatures as well as other genes important for angiogenesis and tissue repair, was quantified using NanoString on days 3, 5, and 8 of culture. A dataset of phenotype controls, consisting of M0, M1, and M2a macrophages, was used as a source of comparison and to validate the methods of characterization. Gene expression of M1 and M2a markers showed mixed upregulation and downregulation by macrophages seeded on collagen and IFNg-adsorbed collagen scaffolds, highlighting the need for more holistic analyses. Euclidean distance measurements to the reference phenotypes were unable to resolve differences between groups. In contrast, rotation gene set testing with and without gene weighting based on the genes' ability to differentiate between M1, M2a, and M0 controls, followed by gene set variation analysis, showed that collagen scaffolds inhibited the classic M1 phenotype without promoting a classic M2a phenotype, and that IFNg-adsorbed collagen scaffolds promoted the M1 phenotype and inhibited the M2a phenotype. In summary, this work demonstrates a powerful, objective methodology for characterizing the macrophage response to biomaterials in comparison to reference macrophage phenotypes. With the addition of more macrophage phenotypes with defined gene expression signatures, this method could prove beneficial for characterizing complex hybrid phenotypes.