Zhao Hongmeng, Zhou Xuejie, Wang Guixin, Yu Yue, Li Yingxi, Chen Zhaohui, Song Wenbin, Zhao Liwei, Wang Li, Wang Xin, Cao Xuchen, Tian Yao
The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China.
Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
J Cancer. 2024 Sep 23;15(18):6002-6015. doi: 10.7150/jca.101042. eCollection 2024.
Triple-negative breast cancer (TNBC) is a poor prognostic subtype of breast cancer due to limited treatment. Macrophage plays a critical role in tumor growth and survival. Our study intends to explore the heterogeneity of macrophage in TNBC and establish a macrophage-related prognostic model for TNBC prognostic stratification. Seurat package was conducted to analyze the single-cell RNA expression profilers. The cell types were identified by the markers derived from public research and online database. The cell-cell interactions were calculated by the CellChat package. Monocle package was used to visualize the cell trajectory of macrophages. The prognostic model was constructed by six macrophage-related genes after a series of selections. The expression of six genes were validated in normal and TNBC tissues. And several potential agents for high-risk TNBC patients were analyzed by Connectivity Map analysis. Nine cell types were identified, and the macrophages were highly enriched in TNBC samples. five distinct subgroups of macrophage were identified. Notably, SPP1+ tumor-associated macrophages exhibited a poor prognosis. The prognostic model was constructed by , , , , , and with good predictive accuracy at 3-, 5- years overall survival for TNBC patients in both training and external test cohorts. Finally, several drugs were identified for the high-risk TNBC patients decided by model. Our study provides a valuable source for clarifying macrophage heterogeneity in TNBC, and a promising tool for prognostic risk stratification of TNBC.
三阴性乳腺癌（TNBC）是一种预后较差的乳腺癌亚型，因为其治疗手段有限。巨噬细胞在肿瘤生长和存活中起着关键作用。我们的研究旨在探索TNBC中巨噬细胞的异质性，并建立一个与巨噬细胞相关的预后模型，用于TNBC的预后分层。使用Seurat软件包分析单细胞RNA表达谱。通过来自公共研究和在线数据库的标志物鉴定细胞类型。使用CellChat软件包计算细胞间相互作用。使用Monocle软件包可视化巨噬细胞的细胞轨迹。经过一系列筛选后，由六个与巨噬细胞相关的基因构建预后模型。在正常组织和TNBC组织中验证了这六个基因的表达。并通过连通图分析为高危TNBC患者分析了几种潜在药物。鉴定出九种细胞类型，并且巨噬细胞在TNBC样本中高度富集。鉴定出巨噬细胞的五个不同亚组。值得注意的是，SPP1 +肿瘤相关巨噬细胞预后较差。由 、 、 、 、 和 构建的预后模型在训练队列和外部测试队列中对TNBC患者3年、5年总生存率具有良好的预测准确性。最后，为模型判定的高危TNBC患者鉴定出几种药物。我们的研究为阐明TNBC中巨噬细胞的异质性提供了有价值的资源，并为TNBC的预后风险分层提供了一个有前景的工具。
