School of Basic Medical Sciences, Jiangsu Vocational College of Medicine, 224005 Yancheng, Jiangsu, China.
Department of General Surgery, Research Unit of General Surgery, Beijing Yanging Hospital of Traditional Chinese Medicine, 102100 Beijing, China.
Front Biosci (Landmark Ed). 2024 Aug 19;29(8):290. doi: 10.31083/j.fbl2908290.
Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). TNBC has a poor prognosis due to high intratumoral heterogeneity and metastasis, pointing to the need to explore distinct molecular subtypes and gene regulatory networks.
The scRNA-seq data of five primary BC samples were downloaded from the Gene Expression Omnibus (GEO) database. Clustering was performed based on filtered and normalized data using the Seurat R package to identify marker genes, which were subsequently annotated to each subset using the CellMarker database. AUCell R package was applied to calculate the hallmark score for each epithelial cell. Marker genes of each subset were screened with FindAllMarkers and their biological functions were analyzed using the Database for Annotation Visualization and Integrated Discovery (DAVID) database. Next, cell-cell communication was performed with the CellChat R package. To identify the key regulatory genes, single-cell regulatory network inference and clustering (SCENIC) analysis was conducted. Finally, the expression and potential biological functions of the key regulatory factors were verified through cellular experiments.
A total of 29,101 cells were classified into nine cell subsets, namely, Fibroblasts, Fibroepithelial cells, Epithelial cells 1, Epithelial cells 2, Epithelial cells 3, Endothelial cells, T cells, Plasma B cells and Macrophages. Particularly, the epithelial cells had a higher proportion and higher transforming growth factor-β (TGF-β) activity in the TNBC pathotype as compared to the non-TNBC pathotype. Furthermore, four epithelial cell subsets (marked as Stearoyl-CoA Desaturase (), marker of proliferation Ki67 (), Annexin A3 () and aquaporin 5 ()) were identified as having the greatest impact on the TNBC pathotype. Cell-cell interaction analysis revealed that ANXA3-epithelial cell subset suppressed the T cell function through different mechanisms. C-fos gene () and X-box binding protein 1 () were considered critical regulons involved in TNBC progression. Notably, cellular experiments demonstrated that silencing XBP1 and overexpressing FOS inhibited cancer cell invasion.
The four epithelial cell subsets and two critical regulons identified based on the scRNA-seq data could help explore the underlying intratumoral heterogeneity molecular mechanism and develop effective therapies for TNBC.
三阴性乳腺癌（TNBC）是乳腺癌（BC）中最具侵袭性的亚型。由于肿瘤内异质性和转移较高，TNBC 的预后较差，这表明需要探索不同的分子亚型和基因调控网络。
从基因表达综合数据库（GEO）下载了五例原发性 BC 样本的 scRNA-seq 数据。使用 Seurat R 包对过滤和标准化数据进行聚类，以识别标记基因，随后使用 CellMarker 数据库将这些标记基因注释到每个亚群中。应用 AUCell R 包计算每个上皮细胞的特征基因评分。使用 FindAllMarkers 筛选每个亚群的标记基因，并使用数据库注释、可视化和综合发现（DAVID）数据库分析其生物学功能。接下来，使用 CellChat R 包进行细胞间通讯。使用单细胞调控网络推断和聚类（SCENIC）分析识别关键调控基因。最后，通过细胞实验验证关键调控因子的表达和潜在生物学功能。
共对 29,101 个细胞进行分类，分为 9 个细胞亚群，即成纤维细胞、成纤维上皮细胞、上皮细胞 1、上皮细胞 2、上皮细胞 3、内皮细胞、T 细胞、浆细胞 B 细胞和巨噬细胞。特别是在 TNBC 病理类型中，上皮细胞的比例更高，转化生长因子-β（TGF-β）活性更高。此外，在 TNBC 病理类型中，有四个上皮细胞亚群（标记为 Stearoyl-CoA 去饱和酶（）、增殖标记物 Ki67（）、膜联蛋白 A3（）和水通道蛋白 5（））被确定为对 TNBC 病理类型影响最大。细胞间相互作用分析表明，ANXA3-上皮细胞亚群通过不同机制抑制 T 细胞功能。C-fos 基因（）和 X 盒结合蛋白 1（）被认为是参与 TNBC 进展的关键调节因子。值得注意的是，细胞实验表明，沉默 XBP1 和过表达 FOS 可抑制癌细胞侵袭。
基于 scRNA-seq 数据鉴定的四个上皮细胞亚群和两个关键调控因子，有助于探索肿瘤内异质性的潜在分子机制，并为 TNBC 开发有效的治疗方法。
