Mapping Breast Cancer Microenvironment Through Single-Cell Omics.
Mapping Breast Cancer Microenvironment Through Single-Cell Omics.
复制标题
通过单细胞组学绘制乳腺癌微环境。
DOI：
10.3389/fimmu.2022.868813
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发表时间：
2022
影响因子：
7.3
通讯作者：
中科院分区：
文献类型：
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作者：
乳腺癌的发生和进展不仅依赖于肿瘤细胞的增殖，还依赖于周围肿瘤微环境的显着异质性。其独特的微环境，包括肿瘤浸润淋巴细胞、复杂骨髓细胞、脂质相关巨噬细胞、癌症相关成纤维细胞（CAF）以及其他促进肿瘤细胞生长和迁移的分子，已被证明在乳腺癌的发生、生长和转移中发挥着至关重要的作用。然而，对乳腺癌复杂微环境的详细了解仍然很大程度上未知。对乳腺癌微环境细胞的独特模式的研究很少，也没有评估这些细胞在发病机制中的支持作用。单细胞多组学生物技术，特别是单细胞RNA测序（scRNA-seq）以更高的分辨率揭示单细胞表达水平，精细剖析肿瘤微环境的分子特征。在此，我们回顾了有关乳腺癌微环境的最新文献，重点关注 scRNA-seq 研究并分析不同细胞（包括 T 细胞和 B 细胞、巨噬细胞/单核细胞、中性粒细胞和基质细胞）的异质性和空间位置。本综述旨在提供对乳腺癌微环境的更全面的认识，并为其临床分类、诊断和治疗提供注释。此外，我们还讨论了新颖的单细胞组学技术，如丰富的组学探索策略、多组学联合分析模式和深度学习网络架构对乳腺癌免疫微环境未来研究的影响。
Breast cancer development and progression rely not only on the proliferation of neoplastic cells but also on the significant heterogeneity in the surrounding tumor microenvironment. Its unique microenvironment, including tumor-infiltrating lymphocytes, complex myeloid cells, lipid-associated macrophages, cancer-associated fibroblasts (CAFs), and other molecules that promote the growth and migration of tumor cells, has been shown to play a crucial role in the occurrence, growth, and metastasis of breast cancer. However, a detailed understanding of the complex microenvironment in breast cancer remains largely unknown. The unique pattern of breast cancer microenvironment cells has been poorly studied, and neither has the supportive role of these cells in pathogenesis been assessed. Single-cell multiomics biotechnology, especially single-cell RNA sequencing (scRNA-seq) reveals single-cell expression levels at much higher resolution, finely dissecting the molecular characteristics of tumor microenvironment. Here, we review the recent literature on breast cancer microenvironment, focusing on scRNA-seq studies and analyzing heterogeneity and spatial location of different cells, including T and B cells, macrophages/monocytes, neutrophils, and stromal cells. This review aims to provide a more comprehensive perception of breast cancer microenvironment and annotation for their clinical classification, diagnosis, and treatment. Furthermore, we discuss the impact of novel single-cell omics technologies, such as abundant omics exploration strategies, multiomics conjoint analysis mode, and deep learning network architecture, on the future research of breast cancer immune microenvironment.