ArticleTissue engineering. Part C, Methods2020
Characterizing the Macrophage Response to Immunomodulatory Biomaterials Through Gene Set Analyses.
Article in Tissue engineering. Part C, Methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
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- The BCL-2 inhibitor APG-2575 resets tumor-associated macrophages toward the M1 phenotype, promoting a favorable response to anti-PD-1 therapy via NLRP3 activation.Cellular & molecular immunology · 2024Article
- Identification and Validation of Epithelial Cell Centre Regulatory Transcription Factors in the Gastric Cancer Microenvironment.International journal of general medicine · 2024Article
- Injectable Antioxidant and Oxygen-Releasing Lignin Composites to Promote Wound Healing.ACS applied materials & interfaces · 2023Article
- Assessing the response of human primary macrophages to defined fibrous architectures fabricated by melt electrowriting.Bioactive materials · 2023Article
- Bone response in vivo of Ti-45Zr alloy as dental implant material.Journal of materials science. Materials in medicine · 2022Article
- The extended effect of adsorbed damage-associated molecular patterns and Toll-like receptor 2 signaling on macrophage-material interactions.Frontiers in bioengineering and biotechnology · 2022Article
- Rational Design of Immunomodulatory Hydrogels for Chronic Wound Healing.Advanced materials (Deerfield Beach, Fla.) · 2021Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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