Objective To screen the differentially expressed immune-related genes （DEIRGs） in in-stent restenosis （ISR）， and to analyze the immune cell infiltration in ISR， and to clarify the mechanism of occurrence and development of ISR. Methods The mRNA gene expression data of GSE46560 dataset samples were downloaded from the Gene Expression Omnibus （GEO），and divided into ISR group and non-ISR group. The “Limma” package in R software was used to identify the differentially expressed genes （DEGs） which were then intersected with immune-related genes （IRGs） to identify the DEIRGs in ISR； R software was used for Gene Ontology （GO） functional enrichment andalysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） signaling pathway enrichment analysis on DEIRGs；the STRING database was used to construct the protein-protein interaction （PPI） network， which was visualized and analyzed for Hub genes by Cytoscape software； the receiver operating characteristic （ROC） curve of the Hub genes were plotted， and the area under the curve （AUC） was calculated and the diagnostic value was evaluated； CIBERSORT software was used to analyze the immune cell infiltration in ISR； Pearson correlation analysis was used to analyze the relationships between the immune cells and the relationships between the immune cells and key genes. Results A total of 331 DEGs were identified （P<0.05， | log₂FC| >1）， including 176 upregulated genes and 155 downregulated genes， and 38 DEIRGs were obstained. The GO functional enrichment analysis results showed that the DEIRGs were mainly enriched in biological processes （BP） such as defense response， immune response， and immune system； in cellular components （CC），the DEIRGs were located primarily in the extracellular region and cytoplasmic membrane； and in molecular functions （MF）， the DEIRGs were mainly involved in regulating signaling receptor binding and cytokine receptor activity.The KEGG signaling pathway enrichment analysis results indicated that the DEIRGs in ISR were primarily enriched in the phosphatidylinositol 3-kinase/protein kinase B （PI3K-AKT） and transforming growth factor-β （TGF-β） signaling pathways. In the PPI network， CD19 had the highest node among the top 10 Hub genes. Compared with non-ISR group， the expression level of the CD19 gene in the samples in ISR group was increased （P<0.05）. The AUC value in the ROC curve of CD19 gene expression was 0.92 （P<0.05）. The immune cell infiltration analysis results showed that compared with non-ISR group， the infiltration level of T lymphocyte follicular helper （Tfh） cells in the patients in ISR group were increased （P<0.05）， the infiltration levels of immature B lymphocytes， CD8+T lymphocytes， naive CD4+T lymphocytes， and M0 macrophages were increased， but the differences were not statistically significant （P>0.05）， while the infiltration levels of memory B lymphocytes， activated memory CD4+ T lymphocytes， regulatory T cells， resting natural killer （NK） cells， activated NK cells， monocytes， resting mast cells， and neutrophils were decreased， but the differences were not statistically significant （P>0.05）. There were positive correlations between Tfh cells and M0 macrophages and resting mast cells （r=0.88，P<0.05；r=0.68，P<0.05）， and there were negative correlations between Tfh cells and monocytes and neutrophils（r=-0.49，P<0.05；r=-0.42，P<0.05）. Conclusion CD19 may influence the occurrence and development of ISR by regulating the activation of the PI3K-AKT signaling pathway to affect the Tfh and B lymphocytes. CD19 can serve as a biomarker for the diagnosis of ISR.