Background: Although we have a good understanding of the diagnosis and treatment of pheochromocytoma and paraganglioma (PPGL), the underlying pathogenesis and molecular pathways of PPGL need to be further studied. This study aimed to use bioinformatics to analyze the role of immunerelated genes (IRGs) in the pathogenesis of PPGL.Methods: GSE19422 and GSE60459 microarray data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the "limma" package in R, and genes overlapping with IRGs were screened using the "VennDiagram" package. A protein-protein interaction (PPI) network was constructed in the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and the core genes were identified by Cytoscape, followed by enrichment analysis and receiver operating characteristic (ROC) curve analysis to evaluate the diagnostic efficacy of the core genes. In addition, the level of immune cell infiltration of PPGL was analyzed and the target drug of the core gene was predicted.Results: A total of 1,105 DEGs were identified from the 2 datasets, of which 94 were IRGs, suggesting that the occurrence of PPGL involved immune-related pathways. Through PPI and Cytoscape, a total of 2 core genes: fibroblast growth factor 2 (FGF2), FYN proto-oncogene (FYN), and vascular cell adhesion molecule 1 (VCAM1) were identified, and the ROC curve showed that these 3 core genes had good efficacy in the diagnosis of PPGL, and more than 50 potential therapeutic drugs could be predicted based on these 3 core genes. Subsequent immunoinfiltration analysis showed that mast cells activated were significantly elevated in patients with PPGL, negatively correlated with macrophages M2, and positively correlated with the level of dendritic cells activated.Conclusions: This study found that immunity is closely related to the occurrence of PPGL, and that FGF2, FYN, and VCAM1 may be potential biomarkers and therapeutic targets of PPGL.