Department of Breast Disease, Weifang People's Hospital, Weifang, No.151, Guangwen Street, Kuiwen District, Shandong, China.
Department of General Surgery, Gaomi People's Hospital, Weifang, Shandong, China.
Sci Rep. 2024 Mar 4;14(1):5339. doi: 10.1038/s41598-024-55513-8.
Tumor-associated neutrophils (TANs) can promote tumor progression. This study aimed to investigate the molecular signature that predict the prognosis and immune response of breast cancer (BRCA) based on TAN-related gene (TANRG) expression data. The RNA-seq data of BRCA were gathered from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) datasets. Univariate Cox regression analysis and the least absolute shrinkage and selection operator for selecting prognostic genes. A neo-TAN-related risk signature was constructed by multivariate Cox regression analysis. Time-dependent receiver operating characteristic (ROC) curve analyses and Kaplan-Meier analyses were performed to validate the signature in GEO cohorts and the triple-negative breast cancer (TNBC) subtype. We constructed an independent prognostic factor model with 11 TANRGs. The areas under the ROC curve (AUCs) of the TCGA training cohorts for 3-, 5-, and 7-year overall survival were 0.72, 0.73, and 0.73, respectively. The AUCs of the GEO test cohorts for 3-, 5-, and 7-year overall survival were 0.83, 0.89, and 0.94 (GSE25066) and 0.67, 0.69, and 0.73 (GSE58812), respectively. The proportion of immune subtypes differed among the different risk groups. The IC50 values differed significantly between risk groups and can be used as a guide for systemic therapy. The prognostic model developed by TANRGs has excellent predictive performance in BRCA patients. In addition, this feature is closely related to the prediction of survival, immune activity and treatment response in BRCA patients.
肿瘤相关中性粒细胞 (TANs) 可促进肿瘤进展。本研究旨在基于 TAN 相关基因 (TANRG) 表达数据,探讨预测乳腺癌 (BRCA) 预后和免疫反应的分子特征。BRCA 的 RNA-seq 数据来自癌症基因组图谱 (TCGA) 和基因表达综合 (GEO) 数据集。单变量 Cox 回归分析和最小绝对收缩和选择算子用于选择预后基因。通过多变量 Cox 回归分析构建了新的 TAN 相关风险特征。时间依赖性接受者操作特征 (ROC) 曲线分析和 Kaplan-Meier 分析用于在 GEO 队列和三阴性乳腺癌 (TNBC) 亚型中验证该特征。我们构建了一个包含 11 个 TANRGs 的独立预后因素模型。TCGA 训练队列的 3 年、5 年和 7 年总生存率的 ROC 曲线下面积 (AUC) 分别为 0.72、0.73 和 0.73。GEO 测试队列的 AUC 分别为 3 年、5 年和 7 年总生存率为 0.83、0.89 和 0.94(GSE25066)和 0.67、0.69 和 0.73(GSE58812)。不同风险组之间的免疫亚型比例不同。风险组之间的 IC50 值差异显著,可作为系统治疗的指导。TANRGs 开发的预后模型在 BRCA 患者中具有出色的预测性能。此外,该特征与 BRCA 患者的生存、免疫活性和治疗反应的预测密切相关。