Suppression of Metastases Using a New Lymphocyte Checkpoint Target for Cancer Immunotherapy
Bibliographic record
Abstract
UNLABELLED: CD96 has recently been shown as a negative regulator of mouse natural killer (NK)-cell activity, with Cd96(-/-)mice displaying hyperresponsive NK cells upon immune challenge. In this study, we have demonstrated that blocking CD96 with a monoclonal antibody inhibited experimental metastases in three different tumor models. The antimetastatic activity of anti-CD96 was dependent on NK cells, CD226 (DNAM-1), and IFNγ, but independent of activating Fc receptors. Anti-CD96 was more effective in combination with anti-CTLA-4, anti-PD-1, or doxorubicin chemotherapy. Blocking CD96 in Tigit(-/-)mice significantly reduced experimental and spontaneous metastases compared with its activity in wild-type mice. Co-blockade of CD96 and PD-1 potently inhibited lung metastases, with the combination increasing local NK-cell IFNγ production and infiltration. Overall, these data demonstrate that blocking CD96 is a new and complementary immunotherapeutic strategy to reduce tumor metastases. SIGNIFICANCE: This article illustrates the antimetastatic activity and mechanism of action of an anti-CD96 antibody that inhibits the CD96-CD155 interaction and stimulates NK-cell function. Targeting host CD96 is shown to complement surgery and conventional immune checkpoint blockade.
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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) | 0.002 | 0.001 |
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".