A pyroptosis-associated gene risk model for predicting the prognosis of triple-negative breast cancer

Abstract

BackgroundPyroptosis 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) is still unclear. Therefore, we started to investigate the potential prognostic value of pyroptosis-associated genes in TNBC.MethodsThirty-three genes associated with pyroptosis were extracted from previous publications, 30 of which were identified in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. On the basis of the 30 pyroptosis-related genes, patients with TNBC were divided into three subtypes through unsupervised cluster analysis. The prognostic value of each pyroptosis-associated gene was assessed, and six genes were selected by univariate and LASSO Cox regression analysis to establish a multigene signature. According to the median value of risk score, patients with TNBC in the 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 using R clusterProfiler package. Moreover, the ESTIMATE score and immune cell infiltration were calculated by the 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.ResultsIn the training and validation cohorts, patients with TNBC 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 patients with TNBC. The enrichment analysis indicated that the DEGs between the two risk groups were mainly enriched by immune responses and activities. In addition, patients with TNBC in the low-risk set were found to have a higher value of ESTIMATE score and a higher rate of immune cell infiltration. Finally, the expression levels of five genes [programmed cell death protein 1 (PD-1); cytotoxic t-lymphocyte antigen-4 (CTLA4); lymphocyte activation gene 3 (LAG3); T cell immunoreceptor with Ig and ITIM domains (TIGIT)] associated with immune checkpoint inhibitors were identified to be higher in the low-risk sets. The sensitivities of some anti-cancer drugs commonly used in breast cancer were found closely related to the pyroptosis-associated risk model.ConclusionThe pyproptosis-associated risk model plays a vital role in the tumor immunity of TNBC and can be applied to be a prognostic predictor of patients with TNBC. Our discovery will provide novel insight for TNBC immunotherapies.

Characterization of immune checkpoints expression and lymphocyte densities of iranian breast cancer patients; the co-expression status and clinicopathological associates

“…In Stovgaard et al report, LAG-3 and IC PD-L1 expression had a significant impact on the improved overall survival relapse-free survival (limited to LAG-3) of TNBC [ 24 ]. This is also suggested for PD-1, PD-L1, LAG-3, and TILs in other series of TNBC cases [ 40 , 41 ]. In another study, higher LAG-3 mRNA expression was an independent predictor of metastasis-free survival in a multivariable Cox regression model [ 42 ].…”

Characterization of immune checkpoints expression and lymphocyte densities of Iranian breast cancer patients; the co-expression status and clinicopathological associates

“…In Stovgaard et al report, LAG-3 and IC PD-L1 expression had a signi cant impact on the improved overall survival relapse-free survival (limited to LAG-3) of TNBC (24). This is also suggested for PD-1, PD-L1, LAG-3, and TILs in other series of TNBC cases (40,41). In another study, higher LAG-3 mRNA expression was an independent predictor of metastasis-free survival in a multivariable Cox regression model (42).…”

Novel molecular insights into pyroptosis in triple‐negative breast cancer prognosis and immunotherapy

“…We also constructed a PPRS model. Although the pyroptosis‐associated gene risk model was developed based on 33 pyroptosis‐associated genes extracted from a previous publication, 39 the selection process in the present study was completely different from that previous study. The genes used to construct the PPRS model came from the most relevant turquoise modules of pyroptosis screened by WGCNA and were further subjected to LASSO analysis and Cox regression analysis.…”