乳腺癌（BRCA）是女性中发病率和死亡率很高的最常见恶性肿瘤，转录因子（TF）与BRCA的发生和发展密切相关。本研究旨在基于TF家族确定一个预后基因签名，揭示BRCA的免疫特征和预后生存情况。在本研究中，从癌症基因组图谱（TCGA）和GSE42568获取了RNA测序和相应的临床数据。筛选出预后差异表达的TF家族基因（TFDEGs）以构建一个风险评分模型，然后根据对应的风险评分将BRCA患者分为低风险组和高风险组。应用Kaplan-Meier（KM）分析评估风险评分模型的预后意义，并开发了一个刻度线模型并在TCGA和GSE20685中进行验证。此外，GSEA揭示了在低风险组和高风险组中富集的病理过程和信号通路。最后，完成了关于免疫渗透、免疫检查点和趋化因子水平的分析，以研究风险评分和肿瘤免疫微环境（TIME）之间的相关性。选择基于TFDEGs的预后9基因签名构建风险评分模型。根据KM分析，TCGA-BRCA和GSE20685中高风险组的总体生存率（OS）显著较低风险组差。此外，刻度线模型表明在预测BRCA患者的OS方面具有很大的可能性。如在GSEA分析中所示，肿瘤相关的病理过程和通路在高风险组中相对富集，风险评分与ESTIMATE评分、CD4+和CD8+ T细胞浸润水平以及免疫检查点和趋化因子的表达水平呈负相关。基于TFDEGs的预后模型可作为预测BRCA患者预后的新生物标志物，并可用于在不同的TIME中鉴定潜在的免疫治疗受益人口，并预测潜在的药物靶点。©2023.作者。

Breast cancer (BRCA) is the most common malignancy with high morbidity and mortality in women, and transcription factor (TF) is closely related to the occurrence and development of BRCA. This study was designed to identify a prognostic gene signature based on TF family to reveal immune characteristics and prognostic survival of BRCA.In this study, RNA-sequence with corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and GSE42568. Prognostic differentially expressed transcription factor family genes (TFDEGs) were screened to construct a risk score model, after which BRCA patients were stratified into low-risk and high-risk groups based on their corresponding risk scores. Kaplan-Meier (KM) analysis was applied to evaluate the prognostic implication of risk score model, and a nomogram model was developed and validated with the TCGA and GSE20685. Furthermore, the GSEA revealed pathological processes and signaling pathways enriched in the low-risk and high-risk groups. Finally, analyses regarding levels of immune infiltration, immune checkpoints and chemotactic factors were all completed to investigate the correlation between the risk score and tumor immune microenvironment (TIME).A prognostic 9-gene signature based on TFDEGs was selected to establish a risk score model. According to KM analyses, high-risk group witnessed a significantly worse overall survival (OS) than low-risk group in both TCGA-BRCA and GSE20685. Furthermore, the nomogram model proved great possibility in predicting the OS of BRCA patients. As indicted in GSEA analysis, tumor-associated pathological processes and pathways were relatively enriched in high-risk group, and the risk score was negatively correlated with ESTIMATE score, infiltration levels of CD4+ and CD8+T cells, as well as expression levels of immune checkpoints and chemotactic factors.The prognostic model based on TFDEGs could distinguish as a novel biomarker for predicting prognosis of BRCA patients; in addition, it may also be utilized to identify potential benefit population from immunotherapy in different TIME and predict potential drug targets.© 2023. The Author(s).