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人类乳腺癌的单细胞和空间分辨图谱。

A single-cell and spatially resolved atlas of human breast cancers.

机构信息

The Kinghorn Cancer Centre and Cancer Research Theme, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.

St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.

出版信息

Nat Genet. 2021 Sep;53(9):1334-1347. doi: 10.1038/s41588-021-00911-1. Epub 2021 Sep 6.


DOI:10.1038/s41588-021-00911-1
PMID:34493872
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9044823/
Abstract

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.

摘要

乳腺癌是一个复杂的细胞生态系统,其中异质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结构的了解有限。在这里,我们对人类乳腺癌进行了单细胞和空间分辨转录组学分析。我们开发了一种用于内在亚型分类的单细胞方法 (SCSubtype),以揭示复发性肿瘤细胞异质性。使用细胞转录组和表位测序的免疫表型分析 (CITE-seq) 提供了高分辨率的免疫谱,包括与临床结果相关的新的 PD-L1/PD-L2 巨噬细胞群。间充质细胞通过三个主要谱系内的分化表现出不同的功能和细胞表面蛋白表达。肿瘤中的基质-免疫生态位是空间组织的,为抗肿瘤免疫调节提供了深入了解。使用单细胞特征,我们对大型乳腺癌队列进行去卷积,将它们分为九个称为“生态型”的簇,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全面转录图谱。

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[2]
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[4]
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[5]
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[6]
Spatial Transcriptomics Decodes Breast Cancer Microenvironment Heterogeneity: From Multidimensional Dynamic Profiling to Precision Therapy Blueprint Construction.

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[7]
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[8]
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[9]
Single-cell RNA sequencing reveals different cellular states in malignant cells and the tumor microenvironment in primary and metastatic ER-positive breast cancer.

NPJ Breast Cancer. 2025-8-26

[10]
Integrating multi-modal transcriptomics identifies cellular subtypes with distinct roles in PDAC progression.

Cell Oncol (Dordr). 2025-8-25

本文引用的文献

[1]
Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer.

Nat Cancer. 2020-2

[2]
Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis.

Genome Med. 2021-5-10

[3]
Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography.

Commun Biol. 2020-10-9

[4]
TREM2 marks tumor-associated macrophages.

Signal Transduct Target Ther. 2020-10-9

[5]
Stromal cell diversity associated with immune evasion in human triple-negative breast cancer.

EMBO J. 2020-10-1

[6]
TREM2 Modulation Remodels the Tumor Myeloid Landscape Enhancing Anti-PD-1 Immunotherapy.

Cell. 2020-8-20

[7]
Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer.

Cell. 2020-8-20

[8]
A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors.

Nat Med. 2020-5-11

[9]
CellPhoneDB: inferring cell-cell communication from combined expression of multi-subunit ligand-receptor complexes.

Nat Protoc. 2020-2-26

[10]
A framework for advancing our understanding of cancer-associated fibroblasts.

Nat Rev Cancer. 2020-1-24

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