An Junsha, Lu Yajie, Chen Yuxi, Chen Yuling, Zhou Zhaokai, Chen Jianping, Peng Cheng, Huang Ruizhen, Peng Fu
West China School of Pharmacy, Sichuan University, Chengdu, China.
State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Front Immunol. 2024 Dec 19;15:1499301. doi: 10.3389/fimmu.2024.1499301. eCollection 2024.
A comprehensive understanding of tumor heterogeneity, tumor microenvironment and the mechanisms of drug resistance is fundamental to advancing breast cancer research. While single-cell RNA sequencing has resolved the issue of "temporal dynamic expression" of genes at the single-cell level, the lack of spatial information still prevents us from gaining a comprehensive understanding of breast cancer. The introduction and application of spatial transcriptomics addresses this limitation. As the annual technical method of 2020, spatial transcriptomics preserves the spatial location of tissues and resolves RNA-seq data to help localize and differentiate the active expression of functional genes within a specific tissue region, enabling the study of spatial location attributes of gene locations and cellular tissue environments. In the context of breast cancer, spatial transcriptomics can assist in the identification of novel breast cancer subtypes and spatially discriminative features that show promise for individualized precise treatment. This article summarized the key technical approaches, recent advances in spatial transcriptomics and its applications in breast cancer, and discusses the limitations of current spatial transcriptomics methods and the prospects for future development, with a view to advancing the application of this technology in clinical practice.
全面了解肿瘤异质性、肿瘤微环境和耐药机制是推动乳腺癌研究的基础。虽然单细胞RNA测序在单细胞水平上解决了基因“时间动态表达”的问题,但缺乏空间信息仍然阻碍我们全面了解乳腺癌。空间转录组学的引入和应用解决了这一局限性。作为2020年的年度技术方法,空间转录组学保留了组织的空间位置并解析RNA测序数据,以帮助定位和区分特定组织区域内功能基因的活性表达,从而能够研究基因位置的空间定位属性和细胞组织环境。在乳腺癌的背景下,空间转录组学可以协助识别新的乳腺癌亚型和具有个性化精准治疗潜力的空间判别特征。本文总结了空间转录组学的关键技术方法、最新进展及其在乳腺癌中的应用,并讨论了当前空间转录组学方法的局限性和未来发展前景,以期推动该技术在临床实践中的应用。