Autophagy-related gene-based prognostic model for breast cancer.

[PURPOSE] Breast cancer (BRCA), a major global health issue, has recently become the first major cancer, surpassing lung cancer, and the primary contributor to female cancer deaths. Neoadjuvant chemotherapy (NAC) serves as the standard treatment for BRCA and is associated with favorable disease-free survival (DFS) and overall survival (OS). Autophagy-related genes (ARGs) not only facilitate tumor initiation and progression but also exhibit a close correlation with chemoresistance. This study intends to explore the molecular signature for predicting the BRCA immune response and prognosis based on ARGs.

[METHODS] We collected RNA sequencing data of BRCA from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and screened prognostic genes by WCGNA, univariate Cox analysis, and LASSO regression. Then, based on 11 chemotherapy-sensitive ARGs (C-ARGs), a prognostic model was established using a multivariate Cox analysis. Subsequently, to assess the model’s performance (TCGA), we plotted receiver operating characteristic (ROC) curves and conducted external validation (GEO).

[RESULTS] We found that for 1-/3-/5-year overall survival, the areas under the ROC curve (AUCs) were 0.654, 0.673, and 0.698 in the TCGA training cohort, and 0.641, 0.719, and 0.749 (GSE42568) and 0.635, 0.742, and 0.702 (GSE20685) in the GEO validation cohort. The results demonstrated the satisfactory performance of the C-ARG-based model in predicting the efficacy and BRCA prognosis. In addition, in the low-/high-risk groups, the proportion of immune subtypes and the IC50 value significantly differed, which can guide the systemic therapy.

[CONCLUSION] The C-ARG-based prognostic model exhibits excellent performance in predicting the BRCA prognosis, which lays a solid foundation for the development of clinical treatment protocols for BRCA.

[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s12672-026-04771-1.