PO.BCS01.15 · 生物信息与计算
整合大体与单细胞RNA测序分析揭示乳腺癌中肥大细胞的基因特征和浸润模式
Gene signatures and infiltration patterns of mast cells in breast cancer revealed by integrated bulk and single-cell RNA sequencing Analyses
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：乳腺癌是女性主要癌症之一，由乳腺组织中细胞的不受控生长引起。肥大细胞是一类通常负责炎症和过敏反应的免疫细胞，已成为肿瘤微环境中的关键免疫参与者。然而，这些细胞在乳腺癌中的功能仍未被完全理解，有时甚至存在争议。本研究通过整合大体和单细胞RNA-seq分析，考察了三种乳腺癌亚型中肥大细胞的浸润和基因表达谱。
方法：从NCBI下载公开可用的转录组数据集GSE45419、GSE254991，并使用标准流程重新分析。以|logFC| > 0.2和FDR < 0.05鉴定差异表达基因（DEGs）。生成UMAP图和热图以可视化数据。随后进行基因本体（GO）富集分析，以识别显著富集的生物学通路。
结果：GSE45419的大体RNA-seq数据分析显示，与良性乳腺病变相比，肥大细胞标志基因（KIT、FCER1A、MS4A2、CPA3、HDC和TPSAB1）在ER+、HER2+、TN+（三阴性）乳腺癌中显著上调（图1）。这些基因的表达在ER+中最高，HER2+中居中，TN+中较低，而在良性乳腺病变中最低。对单细胞RNA-seq数据集GSE254991的重新分析在癌组织和邻近组织中均识别出13个细胞簇，包括一个表达经典标志物（KIT、FCER1A、MS4A2、CPA3、HDC和TPSAB1）的独特肥大细胞簇。来自同一患者的肿瘤组织中肥大细胞比例（4.59%）高于配对正常乳腺组织（2.89%）。对癌区与邻近区之间肥大细胞基因表达谱的交叉比较，识别出与乳腺癌相关的、富集于肥大细胞的核心DEGs。GO分析显示乳腺癌中显著上调的通路包括肽抗原的抗原加工与提呈、抗原结合、MHC I类和II类蛋白复合物组装、白细胞介导的免疫和细胞间黏附、对II型干扰素的反应。
结论：整合大体和单细胞转录组数据分析揭示了三种乳腺癌亚型中肥大细胞浸润增加和独特的转录重编程。这些发现为肥大细胞在肿瘤进展中潜在的免疫调节作用提供了新见解，并可能为开发靶向肥大细胞对抗乳腺癌的新型疗法提供依据。
查看英文原文 English abstract
Background: Breast cancer is one of the leading cancers in women, caused by uncontrolledcell growth in breast tissue. Mast cells, a type of immune cell generally responsible forinflammation and allergic reactions, have emerged as key immune players within the tumormicroenvironment. However, the functions of these cells in breast cancer remain incompletelyunderstood and sometimes controversial. This study investigated mast cell infiltration and geneexpression profiles across three breast cancer subtypes by using integrated bulk and single-cellRNA-seq analyses.
Methods: Publicly available transcriptomic datasets GSE45419, GSE254991 were downloadedfrom NCBI and reanalyzed with standard pipelines. Differentially expressed genes (DEGs) wereidentified with |logFC| > 0.2 and FDR < 0.05. UMAPs and Heatmaps were generated tovisualize the data. Gene Ontology (GO) enrichment analysis was subsequently performed toidentify significantly enriched biological pathways.
Results: Bulk RNA-seq data analysis of GSE45419 revealed significant upregulations of mastcell marker genes (KIT, FCER1A, MS4A2, CPA3, HDC and TPSAB1) in ER+, HER2+, TN+(triple negative) breast cancers compared with benign breast lesions (Figure 1). Expressions ofthese genes were the highest in ER+, intermediate in HER2+, lower in TN+, and minimal inbenign breast lesions. Reanalysis of single-cell RNA-seq dataset GSE254991 identified 13clusters of cells in both cancer and adjacent tissues, including a distinct mast cell clusterexpressing canonical markers (KIT, FCER1A, MS4A2, CPA3, HDC and TPSAB1). Theproportion of mast cells is higher in tumor tissue (4.59%) than in paired normal breast tissue(2.89%) from the same patient. Cross-comparison of mast cell gene expression profilesbetween cancerous and adjacent regions identified the core DEGs enriched in mast cellsassociated with breast cancer. GO analysis indicated the significantly up-regulated pathways inbreast cancer including antigen processing and presentation of peptide antigen, antigen binding,MHC Class I and II protein complex assembly, leukocyte mediated immunity and cell-celladhesion, response to type II interferon.
Conclusion: Integrated bulk and single-cell transcriptomic data analysis revealed increasedmast cell infiltration and distinct transcriptional reprogramming in three subtypes of breastcancer. These findings provide new insights into potential immunoregulatory roles of mast cellsin tumor progression and may inform the development of novel therapies targeting mast cells tofight for breast cancer.
利益披露 Disclosure
E. Liu, None..
B. Jin, None..
C. Hu, None..
Q. Wang, None.