Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti–CTLA-4 therapy against melanoma
Bibliographic record
Abstract
Treatment with monoclonal antibody specific for cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), an inhibitory receptor expressed by T lymphocytes, has emerged as an effective therapy for the treatment of metastatic melanoma. Although subject to debate, current models favor a mechanism of activity involving blockade of the inhibitory activity of CTLA-4 on both effector (T eff) and regulatory (T reg) T cells, resulting in enhanced antitumor effector T cell activity capable of inducing tumor regression. We demonstrate, however, that the activity of anti-CTLA-4 antibody on the T reg cell compartment is mediated via selective depletion of T reg cells within tumor lesions. Importantly, T reg cell depletion is dependent on the presence of Fcγ receptor-expressing macrophages within the tumor microenvironment, indicating that T reg cells are depleted in trans in a context-dependent manner. Our results reveal further mechanistic insight into the activity of anti-CTLA-4-based cancer immunotherapy, and illustrate the importance of specific features of the local tumor environment on the final outcome of antibody-based immunomodulatory therapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".