Kidney transplantation is the optimal treatment method for chronic kidney disease. Although the short-term and long-term survival rates of transplanted kidneys have been significantly improved with the development of immunosuppressive agents, acute rejection remains the main risk factor threatening the survival of the allografts and patient. We utilized bioinformatics analysis to identify the predictive and therapeutic target of acute rejection after kidney transplantation. In the results, cytokines were considered as critical role in allografts acute rejection, and most cytokines were increased in the process of AR. According to the machine learning algorithm analysis and receiver operating characteristic curve results, CXCL11 was identified as the most valued cytokine in prediction of AR. Single-gene GSEA results showed CXCL11 was strongly associated with AR-related biological behavior. Subsequent analysis results showed the gene RELA regulate the expression of CXCL11 and mainly distribute in renal tubular epithelial cells. In cell experiments, LPS as the activator of NF-κB signaling pathway induced the expression of CXCL11. In animal experiments, compared to syn group, severe acute rejection occurs in allo group, and companied with severe inflammatory reaction and the expression of CXCL11, as the activation of NF-κB signaling pathway. CXCR3 specifically recognizes CXCL11 as one of its ligands, single cell analysis demonstrated CXCR3 and CD8 were co-expression on the T cells in the microenvironment of allografts. Finally, we demonstrated in allo group of rat kidney transplantation, there were a large number of CXCR3 + CD8+ T cells infiltrated the allografts. Conclusion, we utilized bioinformatics analysis tools, finally identified CXCL11 as the potential target for prediction and treatment in acute rejection after kidney transplantation.
扫码关注我们
求助内容:
应助结果提醒方式:
