A Novel Prognostic Prediction Model Based on Pyroptosis-related Signature for Breast Cancer

Abstract Background: Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that pyroptosis, a newly discovered form of programmed cell death accompanied by inflammation and immune response, is inextricably involved in the development of cancer, and may activate tumor-specific immunity and/or enhance the effectiveness of existing therapies.Methods: We constructed a novel pyroptosis-related model, based on RNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA). Data from a total of 1025 patients were included in this study, and the relationships among their clinicopathological features, survival, immune cell infiltration and RNA-seq expression levels were analyzed.Results: Two pyroptosis clusters were determined according to 38 pyroptosis-related genes. The proportions of tumor-infiltrating immune cells differed significantly in the two pyroptosis clusters. The GO and KEGG enrichment analysis of the differential gene expressions (DGEs) implicated that the immune-related pathways were activated. Then, a 56 pyroptosis-related genes signature, constructed by using univariate and multivariate Cox regression, was significantly associated with progression free interval (PFI), disease specific survival (DSS), and overall survival (OS) of patients with BC. Kaplan-Meier (KM) and receiver operating characteristic (ROC) analyses were conducted to confirm the clinical significance of the signature. Finally, a nomogram was constructed based on the signature to evaluate its clinical value. Cox analysis revealed that the signature was significantly associated with PFI and DSS of patients with BC. KM analysis demonstrated that the signature could efficiently distinguish high and low risk patients. Moreover, ROC analysis showed that the signature exhibited high sensitivity and specificity in predicting the prognosis of patients with BC. Patients in both gene and clinical low risk subgroup (G-C-) who received adjuvant chemotherapy had a significantly lower incidence of the clinical event than those who did not. A nomogram constructed based on the signature was effective in predicting 5- and 10-year PFI and DSS. Conclusion: This study presents a novel 56 pyroptosis-related genes signature prognostic signature significantly associated with PFI, DSS, and OS in patients with BC, and combining with TNM stage might be a potential therapeutic strategy for individualized clinical decision-making.