Targeting Potential of Innate Lymphoid Cells in Melanoma and Other Cancers
Bibliographic record
Abstract
Reinvigorating the killing function of tumor-infiltrating immune cells through the targeting of regulatory molecules expressed on lymphocytes has markedly improved the prognosis of cancer patients, particularly in melanoma. While initially thought to solely strengthen adaptive T lymphocyte anti-tumor activity, recent investigations suggest that other immune cell subsets, particularly tissue-resident innate lymphoid cells (ILCs), may benefit from immunotherapy treatment. Here, we describe the recent findings showing immune checkpoint expression on tissue-resident and tumor-infiltrating ILCs and how their effector function is modulated by checkpoint blockade-based therapies in cancer. We discuss the therapeutic potential of ILCs beyond the classical PD-1 and CTLA-4 regulatory molecules, exploring other possibilities to manipulate ILC effector function to further impede tumor growth and quench disease progression.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".