Atlas-guided discovery of transcription factors for T cell programming

利用图谱引导发现T细胞编程的转录因子

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Abstract

CD8(+) T cells differentiate into diverse states that shape immune outcomes in cancer and chronic infection(1-4). To define systematically the transcription factors (TFs) driving these states, we built a comprehensive atlas integrating transcriptional and epigenetic data across nine CD8(+) T cell states and inferred TF activity profiles. Our analysis catalogued TF activity fingerprints, uncovering regulatory mechanisms governing selective cell state differentiation. Leveraging this platform, we focused on two transcriptionally similar but functionally opposing states that are critical in tumour and viral contexts: terminally exhausted T (TEX(term)) cells, which are dysfunctional(5-8), and tissue-resident memory T (T(RM)) cells, which are protective(9-13). Global TF community analysis revealed distinct biological pathways and TF-driven networks underlying protective versus dysfunctional states. Through in vivo CRISPR screening integrated with single-cell RNA sequencing (in vivo Perturb-seq) we delineated several TFs that selectively govern TEX(term) cell differentiation. We also identified HIC1 and GFI1 as shared regulators of TEX(term) and T(RM) cell differentiation and KLF6 as a unique regulator of T(RM) cells. We discovered new TEX(term)-selective TFs, including ZSCAN20 and JDP2, with no previous known function in T cells. Targeted deletion of these TFs enhanced tumour control and synergized with immune checkpoint blockade but did not interfere with T(RM) cell formation. Consistently, their depletion in human T cells reduces the expression of inhibitory receptors and improves effector function. By decoupling exhaustion T(EX)-selective from protective T(RM) cell programmes, our platform enables more precise engineering of T cell states, accelerating the rational design of more effective cellular immunotherapies.

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