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多组学图谱辅助发现用于选择性T细胞状态编程的转录因子

Multi-Omics Atlas-Assisted Discovery of Transcription Factors for Selective T Cell State Programming.

作者信息

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

出版信息

bioRxiv. 2025 Jan 4:2023.01.03.522354. doi: 10.1101/2023.01.03.522354.

Abstract

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 ), which are dysfunctional, and tissue-resident memory T cells (T ), 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 differentiation while preserving beneficial T characteristics. Through CRISPR screening combined with single-cell RNA sequencing (Perturb-seq), we validated the specific TFs driving the TEX state and confirmed the accuracy of TF specificity predictions. Importantly, we discovered novel TEX -specific TFs such as ZSCAN20, JDP2, and ZFP324. The deletion of these TEX -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 and T states. Furthermore, our global TF community analysis and Perturb-seq experiments revealed how TFs differentially regulate key processes in T and TEX cells, uncovering new biological pathways like protein catabolism that are specifically linked to TEX 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.

摘要

转录因子(TFs)调控T细胞分化为具有不同功能的多种状态。为了在病毒感染和癌症中精确编程所需的T细胞状态,我们生成了一个涵盖九种CD8⁺ T细胞分化状态的全面转录和表观遗传图谱,用于预测TF活性。我们的分析编目了每种状态的TF活性指纹,揭示了控制选择性细胞状态分化的新调控机制。利用这个平台,我们聚焦于肿瘤和病毒控制中的两种关键T细胞状态:功能失调的终末耗竭T细胞(TEX)和具有保护作用的组织驻留记忆T细胞(TRM)。尽管它们功能不同,但这些状态在转录和解剖学上有显著相似性,这使得设计既能避免TEX分化又能保留有益TRM特征的T细胞既具有挑战性又至关重要。通过将CRISPR筛选与单细胞RNA测序(Perturb-seq)相结合,我们验证了驱动TEX状态的特定TFs,并证实了TF特异性预测的准确性。重要的是,我们发现了新的TEX特异性TFs,如ZSCAN20、JDP2和ZFP324。在T细胞中删除这些TEX特异性TFs可增强肿瘤控制,并与免疫检查点阻断协同作用。此外,本研究还鉴定了对TEX和TRM状态都至关重要的多状态TFs,如HIC1和GFI1。此外,我们的全局TF群落分析和Perturb-seq实验揭示了TFs如何差异调节TRM和TEX细胞中的关键过程,揭示了如蛋白质分解代谢等与TEX分化特异性相关的新生物学途径。总之,我们的平台系统地识别了不同T细胞状态下的TF程序,促进了特定T细胞状态的工程设计以改善肿瘤控制,并深入了解了其功能差异背后的细胞机制。

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