本研究旨在开发一个基于超增强子相关基因（SERGs）的稳健预后签名，以揭示乳腺癌的生存预后和免疫微环境。乳腺癌的RNA测序数据来自癌症基因组图谱（TCGA），其中的1069名患者以1：1的比例随机分配到训练集和测试集中。SERGs从超增强子数据库（SEdb）下载得到。之后，在训练集中建立了一个SERGs签名，并在测试集中进一步验证其预后价值。随后，我们确定了该模型的潜在功能富集和肿瘤免疫浸润。此外，我们完成了体外实验，进一步探索ZIC2基因（预后模型中的一个风险基因）在乳腺癌中的生物学功能。 通过使用6个SERGs（ZIC2、NFE2、FOXJ1、KLF15、POU3F2和SPIB）构建了一个预后价值的风险评分系统，发现在训练集和测试集中具有显著更差预后的高风险组患者。此外，通过将这6个基因与年龄和N分期结合，建立了一个多变量回归模型，通过校准、时间依赖性接收器操作特征曲线（ROC）分析和决策曲线分析（DCA）表现良好。进一步分析表明，高风险组中与肿瘤相关的病理过程和通路明显富集。总的来说，这个新的SERGs签名可以应用于筛选具有免疫抑制微环境的乳腺癌，因为风险评分与ESTIMATE评分、肿瘤浸润淋巴细胞（如CD4+和CD8+T细胞）、免疫检查点和趋化因子呈负相关。此外，ZIC2基因表达的下调抑制了乳腺癌细胞的细胞活力、细胞迁移和细胞周期。这个新的SERGs签名可以预测乳腺癌的预后，并且SERGs可能成为乳腺癌的潜在治疗靶点。© 2023. BioMed Central Ltd., part of Springer Nature.

This study targeted at developing a robust, prognostic signature based on super-enhancer-related genes (SERGs) to reveal survival prognosis and immune microenvironment of breast cancer.RNA-sequencing data of breast cancer were retrieved from The Cancer Genome Atlas (TCGA), 1069 patients of which were randomly assigned into training or testing set in 1:1 ratio. SERGs were downloaded from Super-Enhancer Database (SEdb). After which, a SERGs signature was established based on the training set, with its prognostic value further validated in the testing set. Subsequently, we identified the potential function enrichment and tumor immune infiltration of the model. Moreover, in vitro experiments were completed to further explore the biological functions of ZIC2 gene (one of the risk genes in the prognostic model) in breast cancer.A risk score system of prognostic value was constructed with 6 SERGs (ZIC2, NFE2, FOXJ1, KLF15, POU3F2 and SPIB) to find patients in high-risk group with significantly worse prognosis in both training and testing sets. In addition, a multivariate regression was established via integrating the 6 genes with age and N stage, indicating well performance by calibration, time-dependent receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Further analysis demonstrated that tumor-associated pathological processes and pathways were significantly enriched in the high-risk group. In general, the novel SERGs signature could be applied to screen breast cancer with immunosuppressive microenvironment for the risk score was negatively correlated with ESTIMATE score, tumor-infiltration lymphocytes (such as CD4 + and CD8 + T cell), immune checkpoints and chemotactic factors. Furthermore, down-regulation of ZIC2 gene expression inhibited the cell viability, cellular migration and cell cycle of breast cancer cells.The novel SERGs signature could predict the prognosis of breast cancer; and SERGs might serve as potential therapeutic targets for breast cancer.© 2023. BioMed Central Ltd., part of Springer Nature.