Screening of key genes related to angiogenesis in rosacea based on bioinformatics analysis

‍Objective‍ ‍To investigate the differential expression genes (DEGs) related to angiogenesis in rosacea (RA) by utilizing bioinformatics analysis in order to screen the key genes and verify their mRNA expression levels. Methods‍ ‍The gene microarray dataset GSE65914 was retrieved from the Gene Expression Omnibus (GEO) repository. Analyzed by R programming, the dataset was refined to identify DEGs related to RA, and then cross-referenced with angiogenesis-related genes from the GeneCards database to get a subset specific to RA angiogenesis. The process of identifying key genes was augmented by employing protein-protein interaction (PPI) network analysis and Cytoscape-based computational algorithms. The mRNA expression levels of the aforementioned pivotal genes were detected by real-time fluorescent quantitative reverse transcription PCR (RT-qPCR). Results‍ ‍A total of 947 RA-associated DEGs were identified from GEO dataset, and then 202 genes related to RA angiogenesis were further delineated. PPI network analysis and Cytoscape algorithm finally identified 3 key genes, that is, CXCL8, IL-1B, and STAT1. The results of RT-qPCR showed that the mRNA expression levels of MIP-2, GCP-2, IL-1B and STAT1 in RA lesions were significantly higher than those in normal controls (P<0.05). Conclusion‍ ‍With aid of bioinformatics analysis, our study has screened and validated key genes associated with angiogenesis in RA, namely CXCL8, IL-1B, and STAT1, which providing a theoretical basis for elucidating the potential mechanisms underlying RA-induced angiogenesis and developing targeted therapeutic strategies.