Atlas-guided
Chung HK, Liu C, Battu A, Jambor AN, Pratt BM, Xie F, Riesenberg BP, Casillas E, Sun M, Landoni E, Li Y, Ye Q, Joo D, Green J, Syed Z, Brown NJ, Smith M, Ma S, Tan S, Chick B, Tripple V, Wang ZA, Wang J, Mcdonald B, He P, Yang Q, Chen T, Varanasi SK, LaPorta MA, Mann TH, Chen D, Hoffmann F, Ho J, Modliszewski J, Williams A, Liu Y, Wang Z, Liu J, Gao Y, Hu Z, Cho UH, Liu L, Wang Y, Hargreaves DC, Dotti G, Savoldo B, Thaxton JE, Milner JJ, Kaech SM, Wang W
2026 · Nature
CD8+ T cells differentiate into diverse states that shape immune outcomes in cancer and chronic infection1-4.
Abstract
From the original paper, Nature · PubMed
CD8+ T cells differentiate into diverse states that shape immune outcomes in cancer and chronic infection1-4. 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 (TEXterm) cells, which are dysfunctional5-8, and tissue-resident memory T (TRM) cells, which are protective9-13. 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 TEXterm cell differentiation. We also identified HIC1 and GFI1 as shared regulators of TEXterm and TRM cell differentiation and KLF6 as a unique regulator of TRM cells. We discovered new TEXterm-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 TRM cell formation. Consistently, their depletion in human T cells reduces the expression of inhibitory receptors and improves effector function. By decoupling exhaustion TEX-selective from protective TRM cell programmes, our platform enables more precise engineering of T cell states, accelerating the rational design of more effective cellular immunotherapies.
Summary
Level-1 CD8 TF-state prioritization via Taiji v2.0 on 121 sorted ATAC/RNA experiments (nine states): weighted GRNs, PageRank activity, state-selective TF calling, TF waves, and Leiden TF communities decouple TEXterm from TRM programs. Experimentally validated by in vivo Perturb-seq, KO/OE screens, B16-GP33 ACT, anti-PD1 synergy, and human CD8 perturbations (ZSCAN20, JDP2); distinct from Taiji-reprogram cocktail ranking.
Why this class
Level 1 because the method scores candidate interventions through static regulatory-network influence relative to a target GRN, without computing the post-intervention state . Representation family is regulatory-network influence. Cited in §3.2 of the review. Editorial rationale pending review by the maintainer.