Table 1_Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy.docx

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.

全面解析肿瘤异质性、肿瘤微环境与耐药机制，是推进乳腺癌研究的核心基础。尽管单细胞RNA测序（single-cell RNA sequencing）已在单细胞层面解析了基因的时间动态表达（temporal dynamic expression）问题，但空间信息的缺失仍阻碍了我们对乳腺癌的全面认知。空间转录组学（spatial transcriptomics）的引入与应用则攻克了这一局限。作为2020年度技术方法，空间转录组学可保留组织的空间位置信息，并对RNA测序数据进行解析，以实现特定组织区域内功能基因活性表达的定位与区分，从而支持对基因位置的空间属性以及细胞组织环境的研究。在乳腺癌研究场景中，空间转录组学可助力识别新型乳腺癌亚型，以及具备个体化精准治疗应用前景的空间判别特征。本文综述了空间转录组学的核心技术路径、最新研究进展及其在乳腺癌领域的应用，并探讨了当前空间转录组学方法的局限性与未来发展前景，以期推动该技术在临床实践中的应用。