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Characterizing the molecular regulation of inhibitory immune checkpoints with multi-modal single-cell screens.

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153056
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The expression of inhibitory immune checkpoint molecules such as PD-L1 is frequently observed in human cancers and can lead to the suppression of T-cell mediated immune responses. Here we apply ECCITE-seq, a technology which combines pooled CRISPR screens with single-cell mRNA and surface protein measurements, to explore the molecular networks that regulate PD-L1 expression. We also develop a computational framework, mixscape, that substantially improves the signal-to-noise ratio in single-cell perturbation screens by identifying and removing confounding sources of variation. Applying these tools, we identify and validate regulators of PD-L1, and leverage our multi-modal data to identify both transcriptional and post-transcriptional modes of regulation. In particular, we discover that the kelch-like protein KEAP1 and the transcriptional activator NRF2, mediate levels of PD-L1 upregulation after IFNγ stimulation. Our results identify a novel mechanism for the regulation of immune checkpoints and present a powerful analytical framework for the analysis of multi-modal single-cell perturbation screens. Identification of novel immune checkpoint regulators using ECCITE-seq. Please note that the ECCITE_ADT_Barcodes.csv and ECCITE_Arrayed_ADT_Barcodes.csv files are identical. To avoid any confusion, duplicated files were generated to link to each experiment type for users who may try to analyze a specific experiment (ECCITE or ECCITE_Arrayed).

程序性死亡受体配体1(PD-L1)等抑制性免疫检查点分子在人类癌症中频繁表达,并可抑制T细胞介导的免疫应答。本研究采用整合了池化CRISPR筛选与单细胞mRNA、表面蛋白检测的技术ECCITE-seq,探究调控PD-L1表达的分子网络。同时,本研究开发了计算框架mixscape,通过识别并去除混杂变异来源,大幅提升单细胞扰动筛选中的信噪比。借助上述工具,本研究鉴定并验证了PD-L1的调控因子,并利用多模态数据揭示了转录水平与转录后水平的调控模式。具体而言,本研究发现类Kelch蛋白KEAP1与转录激活因子NRF2可介导干扰素γ(IFNγ)刺激后PD-L1的上调水平。本研究结果揭示了一条全新的免疫检查点调控机制,并为多模态单细胞扰动筛选分析提供了高效的分析框架。利用ECCITE-seq鉴定新型免疫检查点调控因子。请注意,ECCITE_ADT_Barcodes.csv与ECCITE_Arrayed_ADT_Barcodes.csv两份文件内容完全一致。为避免用户混淆,针对两类实验(ECCITE或ECCITE_Arrayed)分别生成了对应重复文件,以便需针对特定实验类型开展分析的用户使用。
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2024-01-06
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