间质细胞
多细胞生物
乳腺癌
肿瘤异质性
表型
背景(考古学)
遗传异质性
细胞
单细胞分析
基质
癌症
医学
病理
癌细胞
电池类型
生物
免疫组织化学
遗传学
基因
古生物学
作者
Hartland W. Jackson,Jana Fischer,Vito Riccardo Tomaso Zanotelli,H. Raza Ali,Robert Mechera,Savas D. Soysal,Holger Moch,Simone Muenst,Zsuzsanna Varga,William P. Weber,Bernd Bodenmiller
出处
期刊:Nature
[Springer Nature]
日期:2020-01-20
卷期号:578 (7796): 615-620
被引量:677
标识
DOI:10.1038/s41586-019-1876-x
摘要
Single-cell analyses have revealed extensive heterogeneity between and within human tumours1–4, 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 cytometry5 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. A single-cell, spatially resolved analysis of breast cancer demonstrates the heterogeneity of tumour and stroma tissue and provides a more-detailed method of patient classification than the current histology-based system.
科研通智能强力驱动
Strongly Powered by AbleSci AI