Identification of immune cell function in breast cancer by integrating multiple single-cell data - Zhang, Liyuan; Qin, Qiyuan; Xu, Chen; Zhang, Ningyi; Zhao, Tianyi (Frontiers in Immunology, 2022)
Breast cancer has now become the most commonly diagnosed cancer worldwide. It is a highly complex and heterogeneous disease that comprises distinct histological features and treatment response. With the development of molecular biology and immunology, immunotherapy has become a new field of breast cancer treatment. Identification of cell type-specific genes critical to the immune microenvironment of tumors can help treatment. Single-cell sequencing (scRNA-seq) technology could serve as a powerful tool to analyze cellular genetic information at single-cell resolution and to uncover the gene expression status of each cell, thus allowing comprehensive assessment of intercellular heterogeneity. Because of the influence of sample size and sequencing depth, the specificity of gene expression in different cell types cannot be fully revealed. Therefore, the present study used integrated analysis of two public scRNA-seq datasets to identify the differential expressed genes (DEG) of each cell type in tumor immune microenvironment. Furthermore, we performed functional enrichment analysis using the top 15 differentially expressed genes in each immune cell type to explore the functions and mechanisms of cell-specific genes. Finally, we identified total five differential expressed genes of B cells, T cells and macrophage and analyzed the function and the related pathways and GO terms.