鉴定乳腺癌中与细胞焦亡相关的预后特征。

BACKGROUND: The relationship between pyroptosis and cancer is complex. It is controversial that whether pyroptosis represses or promotes tumor development. This study aimed to explore prognostic molecular characteristics to predict the prognosis of breast cancer (BRCA) based on a comprehensive analysis of pyroptosis-related gene expression data. METHODS: RNA-sequcing data of BRCA were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) datasets. First, pyroptosis-related differentially expressed genes (DEGs) between normal and tumor tissues were identified from the TCGA database. Based on the DEGs, 1053 BRCA patients were divided into two clusters. Second, DEGs between the two clusters were used to construct a signature by a least absolute shrinkage and selection operator (LASSO) Cox regression model, and the GEO cohort was used to validate the signature. Various statistical methods were applied to assess this gene signature. Finally, Single-sample gene set enrichment analysis (ssGSEA) was employed to compare the enrichment scores of 16 types of immune cells and 13 immune-related pathways between the low- and high-risk groups. We calculated the tumor mutational burden (TMB) of TCGA cohort and evaluated the correlations between the TMB and riskscores of the TCGA cohort. We also compared the TMB between the low- and high-risk groups. RESULTS: A total of 39 pyroptosis-related DEGs were identified from the TCGA-breast cancer dataset. A prognostic signature comprising 16 genes in the two clusters of DEGs was developed to divide patients into high-risk and low-risk groups, and its prognostic performance was excellent in two independent patient cohorts. The high-risk group generally had lower levels of immune cell infiltration and lower activity of immune pathway activity than did the low-risk group, and different risk groups revealed different proportions of immune subtypes. The TMB is higher in high-risk group compared with low-risk group. OS of low-TMB group is better than that of high-TMB group. CONCLUSION: A 16-gene signature comprising pyroptosis-related genes was constructed to assess the prognosis of breast cancer patients and its prognostic performance was excellent in two independent patient cohorts. The signature was found closely associated with the tumor immune microenvironment and the potential correlation could provide some clues for further studies. The signature was also correlated with TMB and the mechanisms are still warranted.

背景：细胞焦亡与癌症的关系复杂，细胞焦亡抑制还是促进肿瘤发展存在争议。本研究旨在通过综合分析细胞焦亡相关基因表达数据，探索预测乳腺癌（BRCA）预后的分子特征。

方法：从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）中收集 BRCA 的 RNA-seq 数据。首先，从 TCGA 数据库中鉴定出正常组织和肿瘤组织之间的细胞焦亡相关差异表达基因（DEGs）。基于这些 DEGs，将 1053 名 BRCA 患者分为两个聚类。其次，使用最小绝对收缩和选择算子（LASSO）Cox 回归模型，对两个聚类之间的 DEGs 进行分析，构建签名，并使用 GEO 队列进行验证。应用各种统计方法评估该基因签名。最后，采用单样本基因集富集分析（ssGSEA）比较低风险和高风险组之间 16 种免疫细胞和 13 种免疫相关途径的富集评分。计算 TCGA 队列的肿瘤突变负荷（TMB），评估 TCGA 队列中 TMB 与风险评分的相关性。比较低风险组和高风险组之间的 TMB。

结果：从 TCGA-BRCA 数据集鉴定出 39 个与细胞焦亡相关的 DEGs。基于两个 DEGs 聚类中的 16 个基因，开发了一个预后签名，将患者分为高风险和低风险组，在两个独立的患者队列中具有良好的预后预测性能。高风险组的免疫细胞浸润水平普遍较低，免疫途径活性也较低，而低风险组则相反。不同风险组显示出不同比例的免疫亚型。高风险组的 TMB 高于低风险组。低 TMB 组的 OS 优于高 TMB 组。

结论：构建了一个包含细胞焦亡相关基因的 16 基因签名，用于评估乳腺癌患者的预后，在两个独立的患者队列中具有良好的预后预测性能。该签名与肿瘤免疫微环境密切相关，其潜在相关性可为进一步研究提供一些线索。该签名还与 TMB 相关，其机制仍有待进一步研究。