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单细胞分析揭示的异质性肿瘤微环境泛癌蓝图。

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling.

机构信息

VIB Center for Cancer Biology, Leuven, Belgium.

Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium.

出版信息

Cell Res. 2020 Sep;30(9):745-762. doi: 10.1038/s41422-020-0355-0. Epub 2020 Jun 19.

Abstract

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4 T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

摘要

肿瘤微环境的基质部分由一组异质的组织驻留细胞和肿瘤浸润细胞组成,这些细胞受到癌细胞的深刻影响。一个悬而未决的问题是,不同器官的癌症之间这种异质性在多大程度上相似。在这里,我们对来自肺癌、结直肠癌、卵巢癌和乳腺癌患者的 233591 个单细胞(n=36)进行了分析,并使用不同的单细胞 RNA 和基于蛋白质的技术构建了基质细胞异质性的泛癌症蓝图。我们确定了 68 个基质细胞群体,其中 46 个在癌症类型之间共享,22 个是独特的。我们还通过突出其标记基因、转录因子、代谢活性和组织特异性表达差异来对每个群体进行表型特征描述。驻留细胞类型具有显著的组织特异性,而肿瘤浸润细胞类型在很大程度上在癌症类型之间共享。最后,通过将蓝图应用于接受检查点免疫治疗的黑色素瘤肿瘤,并鉴定出一种预测对检查点免疫治疗反应的幼稚 CD4 T 细胞表型,我们说明了它如何作为解释 scRNA-seq 数据的指南。总之,通过提供一个交互式网络服务器,我们生成了不同癌症中基质细胞共享复杂性的第一个全景图。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a46/7641203/c3ffa3cf15cb/41422_2020_355_Fig1_HTML.jpg

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