生物
乳腺癌
肿瘤微环境
癌症研究
转录组
细胞
癌症
计算生物学
基因表达
肿瘤细胞
遗传学
基因
作者
Shen Zhao,Dian-Jun Chen,Tong-Ming Fu,Jingcheng Yang,Ding Ma,Zhonghua Wang,Xiang-Xue Wang,Yiwen Jiao,Xi Jin,Yi Xiao,Wen-Xuan Xiao,Hu-Yun-Long Zhang,Hong Lv,Anant Madabhushi,Wentao Yang,Yi‐Zhou Jiang,Jun Xu,Zhi‐Ming Shao
标识
DOI:10.1038/s41467-023-42504-y
摘要
Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.
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