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乳腺癌的单细胞病理学图谱。

The single-cell pathology landscape of breast cancer.

机构信息

Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.

Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.

出版信息

Nature. 2020 Feb;578(7796):615-620. doi: 10.1038/s41586-019-1876-x. Epub 2020 Jan 20.

Abstract

Single-cell analyses have revealed extensive heterogeneity between and within human tumours, but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data available for 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis.

摘要

单细胞分析揭示了人类肿瘤之间和内部的广泛异质性,但复杂的单细胞表型及其空间背景目前尚未反映在许多临床决策基础的组织学分层中。在这里,我们使用成像质谱细胞术同时定量分析 35 种生物标志物,对 352 名乳腺癌患者的肿瘤组织进行了 720 次高维病理学成像,其中 281 名患者有长期生存数据。通过空间分辨的单细胞分析,鉴定了肿瘤和基质单细胞的表型、它们的组织和异质性,并能够基于细胞组成和组织组织来描述乳腺癌组织的细胞结构。我们的分析揭示了肿瘤微环境的多细胞特征和与不同临床结果相关的新型乳腺癌亚群。因此,空间分辨的单细胞分析可以以与疾病相关的方式描述肿瘤内表型异质性,并有可能为患者的具体诊断提供信息。

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