目的:本研究旨在利用单细胞转录组测序(scRNA-seq)分析HER2+乳腺癌(PT组)与正常乳腺组织(NM组)之间的细胞组成及细胞通讯差异,以探讨乳腺癌微环境的变化及其潜在的分子机制。方法:数据来源于Gene Expression Omnibus (GEO)数据库的GSE16...
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目的:本研究旨在利用单细胞转录组测序(scRNA-seq)分析HER2+乳腺癌(PT组)与正常乳腺组织(NM组)之间的细胞组成及细胞通讯差异,以探讨乳腺癌微环境的变化及其潜在的分子机制。方法:数据来源于Gene Expression Omnibus (GEO)数据库的GSE161529数据集,共包含3例HER2+乳腺癌患者(PT组)和3例健康乳腺组织样本(NM组)。本研究利用Seurat进行单细胞数据分析,基于差异表达基因(DEGs)进行Gene Ontology (GO)功能富集分析,并采用CellChat解析细胞–细胞相互作用网络,以识别HER2+乳腺癌微环境中的关键信号通路。结果:通过UMAP聚类分析,共鉴定出8种主要细胞类型。与NM组相比,PT组中B细胞、T/NK细胞、上皮细胞和髓系细胞的比例显著升高,而内皮细胞、成纤维细胞和嗜碱性粒细胞比例下降,肥大细胞无显著变化。差异基因分析显示,PT组显著上调的基因富集于免疫应答、细胞增殖及代谢重编程相关通路,而下调基因主要涉及核糖体生物合成、RNA代谢及蛋白翻译等过程。此外,CellChat分析揭示,PT组的细胞通讯显著增强,特别是FN1、MIF和APP信号通路的活跃,涉及细胞外基质重塑、炎症调控及免疫逃逸。结论:HER2+乳腺癌组织的细胞通讯模式发生了显著变化,肿瘤微环境的重塑可能通过增强特定信号通路促进癌症进展。Objective: This study aims to analyze the differences in cellular composition and cell-cell communication between HER2+ breast cancer (PT group) and normal breast tissue (NM group) using single-cell RNA sequencing (scRNA-seq), to explore microenvironmental alterations and their potential molecular mechanisms. Methods: The dataset GSE161529 was obtained from the Gene Expression Omnibus (GEO) database, including three HER2+ breast cancer samples (PT group) and three healthy breast tissue samples (NM group). Single-cell data analysis was performed using the Seurat package, differentially expressed genes (DEGs) were subjected to Gene Ontology (GO) functional enrichment analysis, and CellChat was used to construct the cell-cell interaction network to identify key signaling pathways in the HER2+ breast cancer microenvironment. Results: UMAP clustering analysis identified eight major cell types. Compared to the NM group, the PT group exhibited a significant increase in B cells, T/NK cells, epithelial cells, and myeloid cells, while endothelial cells, fibroblasts, and basophils were decreased, with mast cells showing no significant changes. Differential gene expression analysis revealed that upregulated genes in the PT group were enriched in immune response, cell proliferation, and metabolic reprogramming pathways, whereas downregulated genes were primarily associated with ribosome biogenesis,
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