STING agonists drive recruitment and intrinsic type I interferon responses in monocytic lineage cells for optimal anti-tumor immunity
Bibliographic record
Abstract
The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway, a sensor of cytosolic DNA, orchestrates the production of proinflammatory cytokines, chemokines, and type I interferons (IFN-Is), thereby contributing to spontaneous tumor surveillance. Intratumoral delivery of synthetic STING agonists induces IFN-I-dependent tumor regression in preclinical cancer models and is being tested clinically. In this study, we investigate the role of monocytic lineage cells (MCs) in response to STING agonist induced IFN-I signaling. We show that CCR2-deficient mice, lacking inflammatory MCs in the periphery, or Lyz2-Cre-IFNAR1fl/fl mice in which IFN-I signaling in monocytes is reduced, exhibit impaired responses to STING agonist therapy of MC38 and/or B16F10 tumors. STING agonist treatment induced CCR5-dependent migration of MCs carrying tumor antigen from the tumor to the lymph nodes. Single-cell RNA sequencing of CD45+ cells from lymph nodes and tumors of mice in which half the hematopoietic cells lack the IFNAR1 (interferon alpha/beta receptor 1) revealed that STING agonist therapy induces intrinsic IFNAR1-dependent acquisition of an inflammatory monocytic cell phenotype distinct from inflammatory classical dendritic cells (cDC) and a reduction in macrophages with a protumor TGFβ/angiogenesis transcriptome. Interleukin (IL)-18-IL-18R1 interaction was the top predicted interaction between monocytic lineage cells and CD8+ T cells or natural killer cells. Blocking IL-18 reduced IFN-γ production by CD8 T cells in lymph nodes and decreased the therapeutic efficacy of STING agonist treatment in Ccr2+/+ but not in Ccr2-/- mice. These findings support a pivotal role for IL-18 producing inflammatory monocytic lineage cells in CD8+ T cell control of melanoma following STING agonist treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".