BackgroundThe clinical outcome of triple-negative breast cancer (TNBC) is poor. Finding more targets for the treatment of TNBC is an urgent need. SENPs are SUMO-specific proteins that play an important role in SUMO modification. Among several tumor types, SENPs have been identified as relevant biomarkers for progression and prognosis. The role of SENPs in TNBC is not yet clear.MethodsThe expression and prognosis of SENPs in TNBC were analyzed by TCGA and GEO data. SENP3 coexpression regulatory networks were determined by weighted gene coexpression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and Cox univariate analyses were used to develop a risk signature based on genes associated with SENP3. A time-dependent receiver operating characteristic (ROC) analysis was employed to evaluate a risk signature’s predictive accuracy and sensitivity. Moreover, a nomogram was constructed to facilitate clinical application.ResultsThe prognostic and expression effects of SENP family genes were validated using the TCGA and GEO databases. SENP3 was found to be the only gene in the SENP family that was highly expressed and associated with an unfavorable prognosis in TNBC patients. Cell functional experiments showed that knockdown of SENP3 leads to growth, invasion, and migration inhibition of TNBC cells in vitro. By using WGCNA, 273 SENP3-related genes were identified. Finally, 11 SENP3-related genes were obtained from Cox univariate analysis and LASSO regression. Based on this, a prognostic risk prediction model was established. The risk signature of SENP3-related genes was verified as an independent prognostic marker for TNBC patients.ConclusionAmong SENP family genes, we found that SENP3 was overexpressed in TNBC and associated with a worse prognosis. SENP3 knockdown can inhibit tumor proliferation, invasion, and migration. In TNBC patients, a risk signature based on the expression of 11 SENP3-related genes may improve prognosis prediction. The established risk markers may be promising prognostic biomarkers that can guide the individualized treatment of TNBC patients.