Breast cancer is becoming a tumor with the highest morbidity rate, and inflammation-induced cell death namely pyroptosis reportedly plays dual roles in cancers. However, the specific mechanism between pyroptosis and the clinical prognosis of breast cancer patients is indistinct. Hence, novel pyroptosis-related biomarkers and their contributing factors deserve further exploration to predict the prognosis in breast cancer.
Pearson’s correlation analysis, and univariate and multivariate Cox regression analysis were utilized to obtain six optimal pyroptosis-related gene prognostic signatures (Pyro-GPS). The risk score of each breast cancer patient was calculated. Next, a Pyro-GPS risk model was constructed and verified in TCGA cohort (n=1,089) and GSE20711 cohort (n=88). Then analyses of immune microenvironment, genomic variation, functional enrichment, drug response and clinicopathologic feature stratification associated with the risk score of Pyro-GPS were performed. Subsequently, a nomogram based on the risk score and several significant clinicopathologic features was established. Ultimately, we further investigated the role of
The low-risk breast cancer patients have better survival outcomes than the high-risk patients. The low-risk patients also show higher immune cell infiltration levels and immune-oncology target expression levels. There is no significant difference in genetic variation between the two risk groups, but the frequency of gene mutations varies. Functional enrichment analysis shows that the low-risk patients are prominently correlated with immune-related pathways, whereas the high-risk patients are enriched in cell cycle, ubiquitination, mismatch repair, homologous recombination and biosynthesis-related pathways. Pyro-GPS is positively correlated with the IC50 of anti-tumor drugs. Furthermore, comprehensive analyses based on risk score and clinicopathological features were performed to predict the prognosis of breast cancer patients. Additionally,
The risk score of Pyro-GPS can serve as a promising hallmark to predict the prognosis of BRCA patients. Risk score evaluation may assist to acquire relevant information of tumor immune microenvironment, genomic mutation status, functional pathways and drug sensitivity, and thus provide more effective personalized strategies.