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.

乳腺癌是复杂的细胞生态系统，其中异型相互作用在疾病进展和对治疗的反应中起着核心作用。然而，我们对其细胞组成和组织的了解是有限的。在这里，我们提出了人类乳腺癌的单细胞和空间分辨转录组学分析。我们开发了一种内在亚型分类 (SCSubtype) 的单细胞方法来揭示复发性肿瘤细胞异质性。通过测序 (CITE-seq) 使用转录组和表位的细胞索引进行免疫表型分析，可提供高分辨率的免疫概况，包括新的 PD-L1/PD-L2 ⁺与临床结果相关的巨噬细胞群。间充质细胞通过三个主要谱系内的分化显示出不同的功能和细胞表面蛋白表达。基质免疫生态位在肿瘤中按空间组织，提供了抗肿瘤免疫调节的见解。使用单细胞特征，我们对大型乳腺癌队列进行了去卷积，将它们分为九个集群，称为“生态型”，具有独特的细胞组成和临床结果。本研究提供了乳腺癌细胞结构的综合转录图谱。