Background Aortic dissection (AD) is an acute critical disease of the cardiovascular system characterized by high mortality and morbidity. According to reports, immune cell infiltration is associated to AD. However, the intrinsic molecular mechanisms underlying the pathogenesis of AD still need to be clarified. Methods Four datasets (GSE52093, GSE98770, GSE153434 and GSE190635) were download through the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) of each dataset were screened by robust rank aggregation (RRA) algorithms. Gene ontology (GO) functional enrichment analysis and Kyto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to DEGs. Using the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database, a protein–protein interaction (PPI) network was constructed, and the hub genes were identified by Cytoscape. And, after correcting for nonbiological effects between four datasets by Rank-In algorithm, we obtained a merged matrix. Furthermore, we adopted this merged matrix to evaluate immune infiltration by using CIBERSORT and single sample gene set enrichment analysis (ssGSEA). Finally, we calculated the correlation between hub genes and immune cells. Results Sixty-two integrated DEGs were identified. These DEGs were mainly enriched in 69 biological process (BP) terms and the ATP-binding cassette (ABC) transporters pathways. By applying 12 methods from Cytoscape plugin CytoHubba respectively, we selected final hub genes. The final hub genes consist of angiotensin Ⅰ converting enzyme (ACE), angiotensin converting enzyme 2 (ACE2), calsequestrin 2 (CASQ2) and TIMP metallopeptidase inhibitor 1 (TIMP1). CIBERSORT showed that monocytes ( P < 0.001) and activated mast cells ( P < 0.05) were higher fraction in AD group. ssGSEA showed that regulatory T cell ( P < 0.05), CD56 bright natural killer (NK) cell ( P < 0.01), central memory CD4 T cell ( P < 0.01), T follicular helper cell ( P < 0.01), activated dendritic cell ( P < 0.001), myeloid derived suppressor cells (MDSC) ( P < 0.001), monocytes ( P < 0.001), NK T cell ( P < 0.001), type 1 T helper cell (Th1) ( P < 0.001) and Th17 cell ( P < 0.001) were higher fraction in AD group. Conclusion ACE, ACE2, CASQ2 and TIMP1 are engaged in the process of AD, which can be used as molecular biomarkers for the screening and diagnosis of AD. Immune cell infiltration plays a major role in the development of AD.