Acquisition of suppressive function by conventional T cells limits antitumor immunity upon T <sub>reg</sub> depletion
Bibliographic record
Abstract
Regulatory T (T reg ) cells contribute to immune homeostasis but suppress immune responses to cancer. Strategies to disrupt T reg cell–mediated cancer immunosuppression have been met with limited clinical success, but the underlying mechanisms for treatment failure are poorly understood. By modeling T reg cell–targeted immunotherapy in mice, we find that CD4 + Foxp3 − conventional T (T conv ) cells acquire suppressive function upon depletion of Foxp3 + T reg cells, limiting therapeutic efficacy. Foxp3 − T conv cells within tumors adopt a T reg cell–like transcriptional profile upon ablation of T reg cells and acquire the ability to suppress T cell activation and proliferation ex vivo. Suppressive activity is enriched among CD4 + T conv cells marked by expression of C-C motif receptor 8 (CCR8), which are found in mouse and human tumors. Upon T reg cell depletion, CCR8 + T conv cells undergo systemic and intratumoral activation and expansion, and mediate IL-10–dependent suppression of antitumor immunity. Consequently, conditional deletion of Il10 within T cells augments antitumor immunity upon T reg cell depletion in mice, and antibody blockade of IL-10 signaling synergizes with T reg cell depletion to overcome treatment resistance. These findings reveal a secondary layer of immunosuppression by T conv cells released upon therapeutic T reg cell depletion and suggest that broader consideration of suppressive function within the T cell lineage is required for development of effective T reg cell–targeted therapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".