A Retrospective View of the Triple-Negative Breast Cancer Microenvironment: Novel Markers, Interactions, and Mechanisms of Tumor-Associated Components Using Public Single-Cell RNA-Seq Datasets

三阴性乳腺癌 肿瘤微环境 CDKN2A 电池类型 生物 癌症研究 计算生物学 单细胞分析 细胞 乳腺癌 癌症 遗传学
作者
Minsoo Kim,Wonhee Yang,Dawon Hong,Hye Sung Won,Seokhyun Yoon
出处
期刊:Cancers [MDPI AG]
卷期号:16 (6): 1173-1173 被引量:3
标识
DOI:10.3390/cancers16061173
摘要

Triple-negative breast cancer (TNBC) is a significant clinical challenge due to its aggressive nature and limited treatment options. In search of new treatment targets, not only single genes but also gene pairs involved in protein interactions, we explored the tumor microenvironment (TME) of TNBC from a retrospective point of view, using public single-cell RNA sequencing datasets. A High-resolution Cell type Annotation Tool, HiCAT, was used first to identify the cell type in 3-level taxonomies. Tumor cells were then identified based on the estimates of copy number variation. With the annotation results, differentially expressed genes were analyzed to find subtype-specific markers for each cell type, including tumor cells, fibroblast, and macrophage. Cell–cell interactions were also inferred for each cell type pair. Through integrative analysis, we could find unique TNBC markers not only for tumor cells but also for various TME components, including fibroblasts and macrophages. Specifically, twelve marker genes, including DSC2 and CDKN2A, were identified for TNBC tumor cells. Another key finding of our study was the interaction between the DSC2 and DSG2 genes among TNBC tumor cells, suggesting that they are more tightly aggregated with each other than those of other subtypes, including normal epithelial cells. The overexpression of DSC2 in TNBC and its prognostic power were verified by using METABRIC, a large bulk RNA-seq dataset with clinical information. These findings not only corroborate previous hypotheses but also lay the foundation for a new structural understanding of TNBC, as revealed through our single-cell analysis workflow.

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