The B7 family-related protein, V-set and Ig domain (VSIG4) / Z39Ig / complement receptor immunoglobulin (CRIg), is a new player in the regulation of immunity to infection and inflammation. The unique features of this receptor as compared with classical complement receptors, CR3 and CR4, have heralded the emergence of new concepts in the regulation of innate and adaptive immunity. Its selective expression in tissue macrophages and dendritic cells has been considered of importance in host defence and in maintaining tolerance against self-antigens. Although a major receptor for phagocytosis of complement opsonised bacteria, its array of emerging functions which incorporates the immune suppressive and anti-inflammatory action of the receptor have now been realised. Accumulating evidence from mouse experimental models indicates a potential role for CRIg in protection against bacterial infection and inflammatory diseases, such as rheumatoid arthritis, type 1 diabetes and systemic lupus erythematosus, and also in promotion of tumour growth. CRIg expression can be considered as a control point in these diseases, through which inflammatory mediators, including cytokines, act. The ability of CRIg to suppress cytotoxic T cell proliferation and function may underlie its promotion of cancer growth. Thus, the unique properties of this receptor open up new avenues for understanding of the pathways that regulate inflammation during infection, autoimmunity and cancer with the potential for new drug targets to be identified. While some complement receptors may be differently expressed in mice and humans, as well as displaying different properties, mouse CRIg has a structure and function similar to the human receptor, suggesting that extrapolation to human diseases is appropriate. Furthermore, there is emerging evidence in human conditions that CRIg may be a valuable biomarker in infection and immunity, inflammatory conditions and cancer prognosis.
Bibliographical note1872-4973/ © 2017 The Authors. Published by Elsevier Ireland Ltd. This is an open access article under the CC BY-NC-ND license
- Evidence evaluation
- Bayesian networks
- Likelihood ration
- Activity level propositions