Immune responses to azacytidine in animal models of inflammatory disorders: a systematic review
SourceJournal of Translational Medicine, 19, 1, (2021), article 11
Article / Letter to editor
Display more detailsDisplay less details
Journal of Translational Medicine
SubjectRadboudumc 10: Reconstructive and regenerative medicine RIHS: Radboud Institute for Health Sciences; Radboudumc 5: Inflammatory diseases RIMLS: Radboud Institute for Molecular Life Sciences
Inflammatory disorders like diabetes, systemic lupus erythematodes, inflammatory lung diseases, rheumatoid arthritis and multiple sclerosis, but also rejection of transplanted organs and GvHD, form a major burden of disease. Current classes of immune suppressive drugs to treat these disorders are never curative and side effects are common. Therefore there is a need for new drugs with improved and more targeted modes of action. Potential candidates are the DNA methyl transferase inhibitor 5-azacytidine (Aza) and its derivative 5-aza 2'deoxycitidine (DAC). Aza and DAC have been tested in several pre-clinical in vivo studies. In order to obtain an overview of disorders for which Aza and/or DAC can be a potential treatment, and to find out where information is lacking, we systematically reviewed pre-clinical animal studies assessing Aza or DAC as a potential therapy for distinct inflammatory disorders. Also, study quality and risk of bias was systematically assessed. In the 35 identified studies, we show that both Aza and DAC do not only seem to be able to alleviate a number of inflammatory disorders, but also prevent solid organ rejection and GvHD in in vivo pre-clinical animal models. Aza/DAC are known to upregulate FOXP3, a master transcription factor for Treg, in vitro. Seventeen studies described the effect on Treg, of which 16 studies showed an increase in Treg. Increasing Treg therefore seems to be a common mechanism in preventing inflammatory disorders by Aza/DAC. We also found, however, that many essential methodological details were poorly reported leading to an unclear risk of bias. Therefore, reported effects might be an overestimation of the true effect.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.