Dictionary of immune responses to cytokines at single-cell resolution.
Dictionary of immune responses to cytokines at single-cell resolution.
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单细胞分辨率下细胞因子免疫反应词典
DOI：
10.1038/s41586-023-06816-9
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发表时间：
2024-01
期刊：
影响因子：
64.8
通讯作者：
Hacohen, Nir
中科院分区：
文献类型：
--
作者：
Cui, Ang;Huang, Teddy;Li, Shuqiang;Ma, Aileen;Perez, Jorge L.;Sander, Chris;Keskin, Derin B.;Wu, Catherine J.;Fraenkel, Ernest;Hacohen, Nir
细胞因子在免疫系统中介导细胞间的通讯，是重要的治疗靶点。无数的研究都强调了它们在免疫功能中的核心作用，但我们缺乏每种免疫细胞类型对每种细胞因子的细胞反应的全球视角。为了解决这一差距，我们创建了免疫词典，这是一本包含超过17种免疫细胞类型的单细胞转录图谱的概要，对体内小鼠淋巴结中的86种细胞因子(1,400种细胞因子-细胞类型组合)做出反应。该词典以细胞因子为中心的观点显示，大多数细胞因子诱导高度细胞类型特异性反应。例如，炎性细胞因子白介素1β在几乎每种细胞类型中诱导不同的基因程序。该词典以细胞类型为中心的观点发现，免疫细胞类型中有66种以上由细胞因子驱动的细胞极化状态，包括之前未描述的状态，如白细胞介素18诱导的多功能自然杀伤细胞状态。基于这本词典，我们开发了配套软件免疫反应浓缩分析，用于从基因表达数据评估细胞因子活性和免疫细胞极化，并应用它来揭示免疫检查点阻断治疗后肿瘤中的细胞因子网络。我们的词典为细胞因子的功能产生了新的假说，阐明了细胞因子的多效性，扩展了我们对每种免疫细胞类型的激活状态的了解，并提供了一个框架来推断特定细胞因子和细胞-细胞通讯网络在任何免疫反应中的作用。对17种免疫细胞类型的86种细胞因子的体内反应进行了广泛的全球转录组学分析，揭示了细胞对细胞因子的反应的巨大复杂性，为免疫词典及其配套软件免疫反应浓缩分析提供了基础。
Cytokines mediate cell–cell communication in the immune system and represent important therapeutic targets. A myriad of studies have highlighted their central role in immune function, yet we lack a global view of the cellular responses of each immune cell type to each cytokine. To address this gap, we created the Immune Dictionary, a compendium of single-cell transcriptomic profiles of more than 17 immune cell types in response to each of 86 cytokines (>1,400 cytokine–cell type combinations) in mouse lymph nodes in vivo. A cytokine-centric view of the dictionary revealed that most cytokines induce highly cell-type-specific responses. For example, the inflammatory cytokine interleukin-1β induces distinct gene programmes in almost every cell type. A cell-type-centric view of the dictionary identified more than 66 cytokine-driven cellular polarization states across immune cell types, including previously uncharacterized states such as an interleukin-18-induced polyfunctional natural killer cell state. Based on this dictionary, we developed companion software, Immune Response Enrichment Analysis, for assessing cytokine activities and immune cell polarization from gene expression data, and applied it to reveal cytokine networks in tumours following immune checkpoint blockade therapy. Our dictionary generates new hypotheses for cytokine functions, illuminates pleiotropic effects of cytokines, expands our knowledge of activation states of each immune cell type, and provides a framework to deduce the roles of specific cytokines and cell–cell communication networks in any immune response. An extensive global transcriptomics analysis of in vivo responses to 86 cytokines across more than 17 immune cell types reveals enormous complexity of cellular responses to cytokines, providing the basis of the Immune Dictionary and its companion software Immune Response Enrichment Analysis.
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影响因子：
46.9
作者：
Becht, Etienne;McInnes, Leland;Newell, Evan W.
通讯作者：
Newell, Evan W.
DOI：
10.1126/science.1159407
发表时间：
2008-08-08
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Gardner JM;Devoss JJ;Friedman RS;Wong DJ;Tan YX;Zhou X;Johannes KP;Su MA;Chang HY;Krummel MF;Anderson MS
通讯作者：
Anderson MS
DOI：
10.1126/science.1179050
发表时间：
2009-10-09
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Amit I;Garber M;Chevrier N;Leite AP;Donner Y;Eisenhaure T;Guttman M;Grenier JK;Li W;Zuk O;Schubert LA;Birditt B;Shay T;Goren A;Zhang X;Smith Z;Deering R;McDonald RC;Cabili M;Bernstein BE;Rinn JL;Meissner A;Root DE;Hacohen N;Regev A
通讯作者：
Regev A
影响因子：
8.7
作者：
Dinarello CA
通讯作者：
Dinarello CA
影响因子：
48
作者：
Browaeys, Robin;Saelens, Wouter;Saeys, Yvan
通讯作者：
Saeys, Yvan