Abstract
Although rejection or tolerance can occur in liver transplantation (LT) patients, there are no reliable non-invasive methods for predicting immune homeostasis. In this study, we developed a humanized mouse model to predict liver immune homeostasis in patients who underwent LT. The patient-derived avatar model was developed by injecting peripheral blood mononuclear cells from healthy controls (HCs) or LT patients with stable, rejection, or tolerance into NOD.Cg-PrkdcscidIL2rgtm1Wjl/SzJ (NSG) mice, followed by injection of human hepatic stellate cells and Carbone tetrachloride (CCl4). After 7 weeks, the patient’s T-cell engraftment and liver inflammation in the avatar model were evaluated and compared with the liver histology of LT patients. Changes in liver inflammation following treatment with tacrolimus and/or biguanide derivatives were also examined. The C-X-C Motif Chemokine Receptor 3 (CXCR3)-dependently engrafted patient T cells led to differences in liver inflammation in our model according to the status of LT patients. The livers of avatar models from rejection patients had severe inflammation with more T helper 17 cells and fewer regulatory T cells compared to those of models from tolerance and HCs showing only mild inflammation. Moreover, our model classified stable post-LT patients into severe and mild inflammation groups, which correlated well with liver immunity in these patients. Our models revealed alleviation of inflammation after combination treatment with tacrolimus and biguanide derivatives or monotherapy. Consequently, using our new patient-derived avatar model, we predicted liver immune homeostasis in patients with stable LT without biopsy. Moreover, our avatar model may be useful for preclinical analysis to evaluate treatment responses while reducing risks to patients.
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Lee, S. K., Park, M. J., Choi, J. W., Baek, J. A., Kim, S. Y., Choi, H. J., … Cho, M. L. (2022). Patient-Derived Avatar Mouse Model to Predict the Liver Immune Homeostasis of Long-Term Stable Liver Transplant Patients. Frontiers in Immunology, 13. https://doi.org/10.3389/fimmu.2022.817006
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