多组学图谱辅助发现转录因子,实现特定细胞状态编程。

H Kay Chung, Cong Liu, Alexander N Jambor, Brian P Riesenberg, Ming Sun, Eduardo Casillas, Brent Chick, Audrey Wang, Jun Wang, Shixin Ma, Bryan Mcdonald, Peixiang He, Qiyuan Yang, Timothy Chen, Siva Karthik Varanasi, Michael LaPorte, Thomas H Mann, Dan Chen, Filipe Hoffmann, Victoria Tripple, Josephine Ho, Jennifer Modliszewski, April Williams, Ukrae H Cho, Longwei Liu, Yingxiao Wang, Diana C Hargreaves, Jessica E Thaxton, Susan M Kaech, Wei Wang
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引用次数: 0

摘要

同一类型的细胞可以呈现出不同的状态,具有不同的功能。有效的细胞疗法可以通过特异性驱动理想的细胞状态来实现,这需要阐明关键转录因子(TFs)。在这里,我们在系统水平上整合了表观基因组和转录组数据,以无偏见的方式确定了定义不同 CD8 + T 细胞状态的 TF。这些TF图谱可用于细胞状态编程,以最大限度地发挥T细胞的治疗潜力。例如,可以对 T 细胞进行编程,以避免终末衰竭状态(Tex Term),这是一种功能失调的 T 细胞状态,通常出现在肿瘤或慢性感染中。然而,Tex Term 与有益的组织驻留记忆 T 状态(T RM)在位置和转录特征方面表现出高度的相似性。我们的生物信息学分析预测,新型 TF Zscan20 在 Tex Term 中具有独特的活性。同样,敲除 Zscan20 会阻碍 Tex Term 在体内的分化,但不会影响 T RM 的分化。此外,扰乱 Zscan20 会使 T 细胞进入一种类似效应器的状态,这种状态会带来卓越的肿瘤和病毒控制能力,并与免疫检查点疗法产生协同作用。我们还发现 Jdp2 和 Nfil3 是强大的 Tex Term 驱动因子。一句话总结:多组学图谱能够系统鉴定细胞状态转录因子,用于治疗性细胞状态编程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Omics Atlas-Assisted Discovery of Transcription Factors for Selective T Cell State Programming.

Transcription factors (TFs) regulate the differentiation of T cells into diverse states with distinct functionalities. To precisely program desired T cell states in viral infections and cancers, we generated a comprehensive transcriptional and epigenetic atlas of nine CD8 + T cell differentiation states for TF activity prediction. Our analysis catalogued TF activity fingerprints of each state, uncovering new regulatory mechanisms that govern selective cell state differentiation. Leveraging this platform, we focused on two critical T cell states in tumor and virus control: terminally exhausted T cells (TEX term ), which are dysfunctional, and tissue-resident memory T cells (T RM ), which are protective. Despite their functional differences, these states share significant transcriptional and anatomical similarities, making it both challenging and essential to engineer T cells that avoid TEX term differentiation while preserving beneficial T RM characteristics. Through in vivo CRISPR screening combined with single-cell RNA sequencing (Perturb-seq), we validated the specific TFs driving the TEX term state and confirmed the accuracy of TF specificity predictions. Importantly, we discovered novel TEX term -specific TFs such as ZSCAN20, JDP2, and ZFP324. The deletion of these TEX term -specific TFs in T cells enhanced tumor control and synergized with immune checkpoint blockade. Additionally, this study identified multi-state TFs like HIC1 and GFI1, which are vital for both TEX term and T RM states. Furthermore, our global TF community analysis and Perturb-seq experiments revealed how TFs differentially regulate key processes in T RM and TEX term cells, uncovering new biological pathways like protein catabolism that are specifically linked to TEX term differentiation. In summary, our platform systematically identifies TF programs across diverse T cell states, facilitating the engineering of specific T cell states to improve tumor control and providing insights into the cellular mechanisms underlying their functional disparities.

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