BACKGROUND: Recently, interleukin 17 (IL-17) has been found to play a critical role in the development of breast cancer. However, its prognostic significance in invasive breast cancer (IBC) remains unclear. This study aims to determine the role of IL-17-related signatures in IBC to identify novel therapeutic options. METHODS: IBC data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used to identify IL-17-related prognostic genes. A predictive model was developed using TCGA data and validated using METABRIC data. The relationship between IL-17 scores and immune landscape, chemotherapy drug sensitivity [half maximal inhibitory concentration (IC50)], and immune checkpoint gene expression was analyzed. The quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate key gene expression in breast tumor and normal tissue samples. RESULTS: The predictive model identified core IL-17-related prognostic genes and successfully estimated the prognosis of IBC patients. The model's validity was confirmed using METABRIC data. Patients with high IL-17 scores had worse overall survival (OS) compared to those with low IL-17 scores. Low IL-17 scores were associated with higher immune checkpoint gene expression and predicted enhanced responses to cytotoxic T-lymphocyte-associated protein 4 (CTLA4) and programmed cell death protein 1 (PD-1) therapies. Patients with low IL-17 scores exhibited a higher abundance of immune microenvironment components. Furthermore, qRT-PCR confirmed the lower expression of OR51E1, NDRG2, RGS2, and TSPAN7 in breast tumors compared to normal tissue. CONCLUSIONS: IL-17-related signatures are promising biomarkers for predicting the prognosis of IBC patients. These findings suggest that IL-17-related markers could be used to guide individualized therapeutic strategies, potentially improving outcomes for IBC patients.