Development of an ubiquitin-proteasome system signature for predicting prognosis and providing therapeutic guidance for patients with triple-negative breast cancer.

Abstract

Triple-negative breast cancer (TNBC) is a pathological subtype with a high mortality, and the development of inhibitors in the ubiquitin-proteasome system (UPS) component could be a novel therapeutic tool. Triple-negative breast cancer data were obtained from The Cancer Genome Atlas (TCGA), and subtype analysis was performed by consistent clustering analysis to identify molecular subtypes of TNBC according to UPS characteristics. Differential analysis, COX and least absolute shrinkage and selection operator (LASSO) COX regression analyses were performed to select genes associated with overall survival in TNBC. The final prognostic model (UPS score) was determined using the LASSO COX model. The model performance was assessed using receiver operating characteristic (ROC) curves and survival curves. In addition, the results of the UPS score on analyzing the abundance of immune cell infiltration and immunotherapy were explored. Finally, we developed a nomogram for TNBC survival prediction. Two UPS subtypes (UPSMS1 and UPSMS2) showing significant survival differences were classified. COX regression analysis on differentially expressed genes in UPSMS1 and UPSMS2 filtered five genes that affected overall survival. Based on the regression coefficients and expression data of the five genes, we built a prognostic assessment system (UPS score). The UPS score showed consistent prognostic and therapeutic guidance values. Finally, the ROC curve of the nomogram and UPS score showed the highest predictive efficacy compared with traditional clinical prognostic indicators. The UPS score represented a promising prognostic tool to predict overall survival and immune status and guide personalized treatment selection in TNBC patients, and this study may provide a more practical alternative for clinical monitoring and management of TNBC.