Objective：Bioinformatics analysis was applied to explore the differentially expressed genes（DEG）in normal women with high breast density and low breast density and analyze their enrichment pathways，so as to provide theoretical basis for early diagnosis，targeted therapy and prognosis assessment of breast cancer patients with dense breast. Methods：GSE38506 data set was obtained from the GEO database and DEGs were screened using GEO2R. Enrichment analysis of GO and KEGG was performed using DAVID database. CytoHubba plug-in of STRING and Cytoscape software was used for protein interaction network analysis and Hub gene screening. Finally，the online tool bcGenExMiner was used to analyze the prognosis of these 5 Hub genes. Results：A total of 830 significantly DEGs were screened from GSE38506 gene chip，among which 442 genes were up-regulated and 388 genes were down-regulated. Enrichment analysis showed that DEGs were mainly involved in signal transduction，positive regulation of GTPase activity，innate immune response，cell adhesion，cytoplasmic membrane，cell surface，cell connection，ATP binding，actin binding，transcription factor binding，and so on. A total of 2 core modules and 5 Hub genes were screened，including EGFR，JUN proto-Oncogene，CDC42，SRC proto-oncogene，RAC1，and they were all associated with breast cancer prognosis. Conclusion：In this study，5 Hub genes related to mammographic density in healthy women were screened through bioinformatics，which may have certain influence on the occurrence，development and prognosis of breast cancer，and are potential molecular markers and new targeted therapy sites for breast cancer patients with dense breast.