Bioinformatics Analysis Reveals CCR7 As A Potential Biomarker for Predicting CKD Progression

Background Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur in time. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict the progression of CKD early is required. Methods We used the online Gene Expression Omnibus (GEO) microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein-protein interaction (PPI) network analysis on DEGs and identified key genes. Finally, the expression patterns of the key genes were verified using the GSE60860 data set, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by RT-PCR and western blot analysis. Results Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that the upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas the downregulated DEGs were mainly related to angiogenesis and the extracellular environment. PPI network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21, have also been identified as DEGs. The ROC curve analysis of CCR7, CCL19 and CCL21 found that CCR7 and CCL19 present good disease prediction ability. Conclusion CCR7 may be a stable biomarker for predicting the progression of CKD, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD.