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Recent Progress and Applications of Single-cell Sequencing Technology in Breast Cancer

Overview
Journal Front Genet
Date 2024 Oct 3
PMID 39359479
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Abstract

Single-cell RNA sequencing (scRNA-seq) technology enables the precise analysis of individual cell transcripts with high sensitivity and throughput. When integrated with multiomics technologies, scRNA-seq significantly enhances the understanding of cellular diversity, particularly within the tumor microenvironment. Similarly, single-cell DNA sequencing has emerged as a powerful tool in cancer research, offering unparalleled insights into the genetic heterogeneity and evolution of tumors. In the context of breast cancer, this technology holds substantial promise for decoding the intricate genomic landscape that drives disease progression, treatment resistance, and metastasis. By unraveling the complexities of tumor biology at a granular level, single-cell DNA sequencing provides a pathway to advancing our comprehension of breast cancer and improving patient outcomes through personalized therapeutic interventions. As single-cell sequencing technology continues to evolve and integrate into clinical practice, its application is poised to revolutionize the diagnosis, prognosis, and treatment strategies for breast cancer. This review explores the potential of single-cell sequencing technology to deepen our understanding of breast cancer, highlighting key approaches, recent advancements, and the role of the tumor microenvironment in disease plasticity. Additionally, the review discusses the impact of single-cell sequencing in paving the way for the development of personalized therapies.

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References
1.
Ding S, Chen X, Shen K . Single-cell RNA sequencing in breast cancer: Understanding tumor heterogeneity and paving roads to individualized therapy. Cancer Commun (Lond). 2020; 40(8):329-344. PMC: 7427308. DOI: 10.1002/cac2.12078. View

2.
Hollern D, Xu N, Thennavan A, Glodowski C, Garcia-Recio S, Mott K . B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer. Cell. 2019; 179(5):1191-1206.e21. PMC: 6911685. DOI: 10.1016/j.cell.2019.10.028. View

3.
Kashima Y, Sakamoto Y, Kaneko K, Seki M, Suzuki Y, Suzuki A . Single-cell sequencing techniques from individual to multiomics analyses. Exp Mol Med. 2020; 52(9):1419-1427. PMC: 8080663. DOI: 10.1038/s12276-020-00499-2. View

4.
Lee J, Hyeon D, Hwang D . Single-cell multiomics: technologies and data analysis methods. Exp Mol Med. 2020; 52(9):1428-1442. PMC: 8080692. DOI: 10.1038/s12276-020-0420-2. View

5.
Biancolella M, Testa B, Baghernajad Salehi L, DApice M, Novelli G . Genetics and Genomics of Breast Cancer: update and translational perspectives. Semin Cancer Biol. 2020; 72:27-35. DOI: 10.1016/j.semcancer.2020.03.013. View