Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition

T cells exhibit heterogeneous functional states, which correlate with responsiveness to immune checkpoint blockade and prognosis of tumor patients. However, the molecular regulatory mechanisms underlying the dynamic process of T cell state transition remain largely unknown. Based on single-cell tran...

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Autores principales:	Min Yan, Jing Hu, Huating Yuan, Liwen Xu, Gaoming Liao, Zedong Jiang, Jiali Zhu, Bo Pang, Yanyan Ping, Yunpeng Zhang, Yun Xiao, Xia Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	T cell dysfunction state transition trajectory dynamic regulatory network pseudo-times critical regulators Therapeutics. Pharmacology RM1-950
Acceso en línea:	https://doaj.org/article/c501c08eaa224fe2b9e632b3e2cc91f3
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spelling	oai:doaj.org-article:c501c08eaa224fe2b9e632b3e2cc91f32021-11-06T04:26:07ZDynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition2162-253110.1016/j.omtn.2021.10.011https://doaj.org/article/c501c08eaa224fe2b9e632b3e2cc91f32021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2162253121002547https://doaj.org/toc/2162-2531T cells exhibit heterogeneous functional states, which correlate with responsiveness to immune checkpoint blockade and prognosis of tumor patients. However, the molecular regulatory mechanisms underlying the dynamic process of T cell state transition remain largely unknown. Based on single-cell transcriptome data of T cells in non-small cell lung cancer, we combined cell states and pseudo-times to propose a pipeline to construct dynamic regulatory networks for dissecting the process of T cell dysfunction. Candidate regulators at different stages were revealed in the process of tumor-infiltrating T cell dysfunction. Through comparing dynamic networks across the T cell state transition, we revealed frequent regulatory interaction rewiring and further refined critical regulators mediating each state transition. Several known regulators were identified, including TCF7, EOMES, ID2, and TOX. Notably, one of the critical regulators, TSC22D3, was frequently identified in the state transitions from the intermediate state to the pre-dysfunction and dysfunction state, exerting diverse roles in each state transition by regulatory interaction rewiring. Moreover, higher expression of TSC22D3 was associated with the clinical outcome of tumor patients. Our study embedded transcription factors (TFs) within the temporal dynamic networks, providing a comprehensive view of dynamic regulatory mechanisms controlling the process of T cell state transition.Min YanJing HuHuating YuanLiwen XuGaoming LiaoZedong JiangJiali ZhuBo PangYanyan PingYunpeng ZhangYun XiaoXia LiElsevierarticleT cell dysfunctionstate transition trajectorydynamic regulatory networkpseudo-timescritical regulatorsTherapeutics. PharmacologyRM1-950ENMolecular Therapy: Nucleic Acids, Vol 26, Iss , Pp 1115-1129 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	T cell dysfunction state transition trajectory dynamic regulatory network pseudo-times critical regulators Therapeutics. Pharmacology RM1-950
spellingShingle	T cell dysfunction state transition trajectory dynamic regulatory network pseudo-times critical regulators Therapeutics. Pharmacology RM1-950 Min Yan Jing Hu Huating Yuan Liwen Xu Gaoming Liao Zedong Jiang Jiali Zhu Bo Pang Yanyan Ping Yunpeng Zhang Yun Xiao Xia Li Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition
description	T cells exhibit heterogeneous functional states, which correlate with responsiveness to immune checkpoint blockade and prognosis of tumor patients. However, the molecular regulatory mechanisms underlying the dynamic process of T cell state transition remain largely unknown. Based on single-cell transcriptome data of T cells in non-small cell lung cancer, we combined cell states and pseudo-times to propose a pipeline to construct dynamic regulatory networks for dissecting the process of T cell dysfunction. Candidate regulators at different stages were revealed in the process of tumor-infiltrating T cell dysfunction. Through comparing dynamic networks across the T cell state transition, we revealed frequent regulatory interaction rewiring and further refined critical regulators mediating each state transition. Several known regulators were identified, including TCF7, EOMES, ID2, and TOX. Notably, one of the critical regulators, TSC22D3, was frequently identified in the state transitions from the intermediate state to the pre-dysfunction and dysfunction state, exerting diverse roles in each state transition by regulatory interaction rewiring. Moreover, higher expression of TSC22D3 was associated with the clinical outcome of tumor patients. Our study embedded transcription factors (TFs) within the temporal dynamic networks, providing a comprehensive view of dynamic regulatory mechanisms controlling the process of T cell state transition.
format	article
author	Min Yan Jing Hu Huating Yuan Liwen Xu Gaoming Liao Zedong Jiang Jiali Zhu Bo Pang Yanyan Ping Yunpeng Zhang Yun Xiao Xia Li
author_facet	Min Yan Jing Hu Huating Yuan Liwen Xu Gaoming Liao Zedong Jiang Jiali Zhu Bo Pang Yanyan Ping Yunpeng Zhang Yun Xiao Xia Li
author_sort	Min Yan
title	Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition
title_short	Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition
title_full	Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition
title_fullStr	Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition
title_full_unstemmed	Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition
title_sort	dynamic regulatory networks of t cell trajectory dissect transcriptional control of t cell state transition
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/c501c08eaa224fe2b9e632b3e2cc91f3
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_version_	1718443942973800448

Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition

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