Local delivery of low-dose anti–CTLA-4 to the melanoma lymphatic basin leads to systemic T <sub>reg</sub> reduction and effector T cell activation
Bibliographic record
Abstract
Preclinical studies show that locoregional CTLA-4 blockade is equally effective in inducing tumor eradication as systemic delivery, without the added risk of immune-related side effects. This efficacy is related to access of the CTLA-4 blocking antibodies to tumor-draining lymph nodes (TDLNs). Local delivery of anti–CTLA-4 after surgical removal of primary melanoma, before sentinel lymph node biopsy (SLNB), provides a unique setting to clinically assess the role of TDLN in the biological efficacy of locoregional CTLA-4 blockade. Here, we have evaluated the safety, tolerability, and immunomodulatory effects in the SLN and peripheral blood of a single dose of tremelimumab [a fully human immunoglobulin gamma-2 (IgG2) mAb directed against CTLA-4] in a dose range of 2 to 20 mg, injected intradermally at the tumor excision site 1 week before SLNB in 13 patients with early-stage melanoma (phase 1 trial; NCT04274816). Intradermal delivery was safe and well tolerated and induced activation of migratory dendritic cell (DC) subsets in the SLN. It also induced profound and durable decreases in regulatory T cell (T reg ) frequencies and activation of effector T cells in both SLN and peripheral blood. Moreover, systemic T cell responses against NY-ESO-1 or MART-1 were primed or boosted ( N = 7), in association with T cell activation and central memory T cell differentiation. These findings indicate that local administration of anti–CTLA-4 may offer a safe and promising adjuvant treatment strategy for patients with early-stage melanoma. Moreover, our data demonstrate a central role for TDLN in the biological efficacy of CTLA-4 blockade and support TDLN-targeted delivery methods.
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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".