A pyroptosis-associated gene risk model for predicting the prognosis of triple-negative breast cancer - Qiu, Pengjun; Guo, Qiaonan; Pan, Kelun; Chen, Jianpeng; Lin, Jianqing (Frontiers in Oncology, 2022)
Background: Pyroptosis is a novel identified form of inflammatory cell death that is important in the development and progression of various diseases, including malignancies. However, the relationship between pyroptosis and triple-negative breast cancer (TNBC) are still unclear. Methods: Thirty-three genes associated with pyroptosis were extracted from previous publications, 30 of which were identified in METABRIC cohort. Based on the 30 pyroptosis-related genes, TNBC patients were divided into 3 subtypes through unsupervised cluster analysis. The prognostic value of each pyroptosis-associated gene was assessed and 6 genes were selected by univariate and LASSO Cox regression analysis to establish a multigene signature. According to the median value of risk score, TNBC patients in training and validation cohorts were separated to high- and low- risk sets. The enrichment analysis was conducted on the differentially expressed genes (DEGs) of the two risk sets by use of R clusterProfiler package. Besides, the ESTIMATE Score and immune cell infiltration were calculated by ESTIMATE and CIBERSORT methods. After that, the correlation among pyroptosis-associated risk score and the expression of immune checkpoint-associated genes as well as anti-cancer drugs sensitivities were further analyzed. Results: In training and validation cohorts, TNBC patients in the high-risk set were found in a lower survival rate than those in the low-risk set. Combined with the clinical characteristics, the pyroptosis-related risk score was identified as an independent risk factor for the prognosis of TNBC patients. The enrichment analysis indicated that the DEGs between the two risk groups were mainly enriched by immune responses and activities. Additionally, TNBC patients in low-risk set were found to have higher value of ESTIMATE score and higher rate of immune cell infiltration. Finally, the expression levels of 5 genes associated with immune checkpoint inhibitors were identified higher in the low-risk sets. The sensitivities of some anti-cancer drugs commonly used in breast cancer (BC) were found closely related to the pyroptosis-associated risk model. Conclusion: The pyproptosis-associated risk model plays vital role in the tumor immunity of TNBC and can be applied to be a prognostic predictor of TNBC patients. Our discovery will provide novel insight for TNBC immunotherapies.