Targeted ADAM17 blocker directed to CD16 (TAB16) augments NK cell proliferation and cytotoxicity 3752
Bibliographic record
Abstract
Abstract Description NK cells are cytotoxic innate lymphocytes that mediate tumor cell killing and are an attractive cell therapy for cancer. The Fc receptor CD16 on human NK cells is cleaved from the cell surface by the membrane protease ADAM17 upon their activation. We have reported that Medi-1, a fully human IgG1 mAb that blocks ADAM17 function is engaged by CD16 and blocks its cleavage, inducing and prolonging CD16 signaling, which synergizes with IL-15 stimulation to enhance NK cell proliferation. Because ADAM17 is broadly expressed and has numerous substrates, on-target off-NK cell effects by Medi-1 are a concern. To address this, we developed TAB16, a novel dual-targeting antibody that links Medi-1 scFv with an anti-CD16 camelid VHH. Our data shows that TAB16 prevents the cleavage of ADAM17 substrates selectively on NK cells. Moreover, IL-15 in combination with TAB16 results in enhanced NK cell proliferation. Real-time cytotoxicity assays show TAB16 augments NK cell-mediated killing of tumor cells with sustained cytotoxic function and reduced cellular exhaustion compared to IL-15 alone. These findings reveal that TAB16 offers a targeted approach to block ADAM17 function and enhance NK cell proliferation and anti-tumor function. Funding Sources NIH R01CA203348 Topic Categories Innate Immune Responses and Host Defense: Molecular Mechanisms (INM)
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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) | 0.004 | 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".