【文献分享】A single-cell and spatially resolved atlas of human breast cancers提供数据和代码

介绍

乳腺癌是一种复杂的细胞生态系统，在其疾病发展和对治疗的反应过程中，异型相互作用起着核心作用。然而，我们对这些癌细胞的细胞组成和组织结构的了解还很有限。在此，我们对人类乳腺癌进行了单细胞和空间分辨率的转录组学分析。我们开发了一种单细胞内在亚型分类方法（SCSubtype），以揭示复发性肿瘤细胞的异质性。通过使用转录组细胞索引和表位测序（CITE-seq）进行免疫表型分析，我们获得了高分辨率的免疫特征，包括与临床结果相关的新的 PD-L1/PD-L2+巨噬细胞群体。间充质细胞通过在三个主要谱系中的分化表现出不同的功能和细胞表面蛋白表达。肿瘤中的基质免疫微环境在空间上是有序排列的，为我们提供了关于抗肿瘤免疫调节的见解。利用单细胞特征，我们对大规模乳腺癌队列进行了去混叠分析，将其分为九个簇，称为“生态型”，每个生态型具有独特的细胞组成和临床结果。这项研究为乳腺癌的细胞结构提供了全面的转录组图谱。

Breast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of their cellular composition and organization is limited. Here we present a single-cell and spatially resolved transcriptomics analysis of human breast cancers. We developed a single-cell method of intrinsic subtype classification (SCSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) provides high-resolution immune profiles, including new PD-L1/PD-L2+ macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell-surface protein expression through differentiation within three major lineages. Stromal-immune niches were spatially organized in tumors, offering insights into antitumor immune regulation. Using single-cell signatures, we deconvoluted large breast cancer cohorts to stratify them into nine clusters, termed ‘ecotypes’, with unique cellular compositions and clinical outcomes. This study provides a comprehensive transcriptional atlas of the cellular architecture of breast cancer.

代码

https://github.com/Swarbricklab-code/BrCa_cell_atlas

参考

• A single-cell and spatially resolved atlas of human breast cancers
• https://github.com/Swarbricklab-code/BrCa_cell_atlas