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Review
. 2024 Dec 22;25(24):13706.
doi: 10.3390/ijms252413706.

Advancements in the Application of scRNA-Seq in Breast Research: A Review

Affiliations
Review

Advancements in the Application of scRNA-Seq in Breast Research: A Review

Zhenyu Zhang et al. Int J Mol Sci. .

Abstract

Single-cell sequencing technology provides apparent advantages in cell population heterogeneity, allowing individuals to better comprehend tissues and organs. Sequencing technology is currently moving beyond the standard transcriptome to the single-cell level, which is likely to bring new insights into the function of breast cells. In this study, we examine the primary cell types involved in breast development, as well as achievements in the study of scRNA-seq in the microenvironment, stressing the finding of novel cell subsets using single-cell approaches and analyzing the problems and solutions to scRNA-seq. Furthermore, we are excited about the field's promising future.

Keywords: advancements; breast; scRNA-seq; single cell.

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Conflict of interest statement

The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The main cell type of the adult breast. Note: Nature (2023). A spatially resolved single-cell genomic atlas of the adult human breast [89]. Retrieved from: https://www.nature.com/articles/s41586-023-06252-9. (accessed on 8 October 2024). (a) Anatomy of the adult human breast and a pathological hematoxylin and eosin (H&E) section, with illustrations of the major breast cell types. Scale bars, 100 μm. (b) The workflow of the HBCA project. (c) Uniform manifold approximation and projection (UMAP) of scRNA-seq data from 714,331 cells integrated across 167 tissues from 126 women, showing 10 clusters that correspond to the major cell types. (d) Consensus heat map of the top seven genes expressed in each cell type cluster from averaged scRNA-seq data. (e) UMAP representation of snRNA-seq data from 117,346 nuclei integrated across 24 tissues from 20 women, showing 11 cell type clusters. (f) Consensus heat map of the top seven genes expressed in each cell cluster from averaged snRNA-seq data. Adipo., adipocytes; perivasc., perivascular cells.

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