Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer

Author:

Zhao Shen,Chen De-PinORCID,Fu Tong,Yang Jing-Cheng,Ma DingORCID,Zhu Xiu-Zhi,Wang Xiang-Xue,Jiao Yi-Ping,Jin Xi,Xiao Yi,Xiao Wen-Xuan,Zhang Hu-Yunlong,Lv Hong,Madabhushi AnantORCID,Yang Wen-TaoORCID,Jiang Yi-Zhou,Xu JunORCID,Shao Zhi-MingORCID

Abstract

AbstractDigital 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.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry,Multidisciplinary

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Onco-Breastomics: An Eco-Evo-Devo Holistic Approach;International Journal of Molecular Sciences;2024-01-28

2. OII-DS: A benchmark Oral Implant Image Dataset for object detection and image classification evaluation;Computers in Biology and Medicine;2023-12

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