Background: Triple-negative breast cancer (TNBC) is the most invasive and metastatic subtype of breast cancer. SUMO1-activating enzyme subunit 1 (SAE1), an E1-activating enzyme, is indispensable for protein SUMOylation. SAE1 has been found to be a relevant biomarker for progression and prognosis in several tumor types. However, the role of SAE1 in TNBC remains to be elucidated. Methods: In the research, the mRNA expression of SAE1 was analyzed via the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database. Cistrome DB Toolkit was used to predict which transcription factors (TFs) are most likely to increase SAE1 expression in TNBC. The correlation between the expression of SAE1 and the methylation of SAE1 or quantity of tumor-infiltrating immune cells was further invested. Single-cell analysis, using CancerSEA, was performed to query which functional states are associated with SAE1 in different cancers in breast cancer at the single-cell level. Next, weighted gene coexpression network (WGCNA) was applied to reveal the highly correlated genes and coexpression networks of SAE1 in TNBC patients, and a prognostic model containing SAE1 and correlated genes was constructed. Finally, we also examined SAE1 protein expression of 207 TNBC tissues using immunohistochemical (IHC) staining. Results: The mRNA and protein expression of SAE1 were increased in TNBC tissues compared with adjacent normal tissues, and the protein expression of SAE1 was significantly associated with overall survival (OS) and disease-free survival (DFS). Correlation analyses revealed that SAE1 expression was positively correlated with forkhead box M1 (FOXM1) TFs and negatively correlated with SAE1 methylation site (cg14042711) level. WGCNA indicated that the genes coexpressed with SAE1 belonged to the green module containing 1,176 genes. Through pathway enrichment analysis of the module, 1,176 genes were found enriched in cell cycle and DNA repair. Single-cell analysis indicated that SAE1 and its coexpression genes were associated with cell cycle, DNA damage, DNA repair, and cell proliferation. Using the LASSO COX regression, a prognostic model including SAE1 and polo-like kinase 1 (PLK1) was built to accurately predict the likelihood of DFS in TNBC patients. Conclusion: In conclusion, we comprehensively analyzed the mRNA and protein expression, prognosis, and interaction genes of SAE1 in TNBC and constructed a prognostic model including SAE1 and PLK1. These results might be important for better understanding of the role of SAE1 in TNBC. In addition, DNA methyltransferase and TFs inhibitor treatments targeting SAE1 might improve the survival of TNBC patients.

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