The Monoclonal Antibody NEO-201 Enhances Natural Killer Cell Cytotoxicity Against Tumor Cells Through Blockade of the Inhibitory CEACAM5/CEACAM1 Immune Checkpoint Pathway
Bibliographic record
Abstract
Background: Natural killer (NK) cells are essential to innate immunity and participate in cancer immune surveillance. Heterophilic interactions between carcinoembryonic antigen (CEA) on tumor cells and carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) on NK cells inhibit NK cell cytotoxicity against tumor cells. NEO-201 is a humanized IgG1 monoclonal antibody that recognizes members of CEACAM family, expressed specifically on a variety of human carcinoma cell lines and tumor tissues. This investigation was designed to determine whether the binding of NEO-201 with CEACAM5 on tumor cells can block the CEACAM5/CEACAM1 interaction to restore antitumor cytotoxicity of NK cells. Materials and Methods:In vitro functional assays, using various human tumor cell lines as target cells and NK-92 cells as effectors, were conducted to assess the ability of NEO-201 to block the interaction between CEACAM5 on tumor cells and CEACAM1 on NK cells to enhance the in vitro killing of tumor cells by NK-92. NK-92 cells were used as a model of direct NK killing of tumor cells because they lack antibody-dependent cellular cytotoxicity activity. Results: Expression profiling revealed that various human carcinoma cell lines expressed different levels of CEACAM5+ and NEO-201+ cells. Addition of NEO-201 significantly enhanced NK-92 cell cytotoxicity against highly CEACAM5+/NEO-201+ expressing tumor cells, suggesting that its activity is correlated with the level of CEACAM5+/NEO-201+ expression. Conclusions: These findings demonstrate that NEO-201 can block the interaction between CEACAM5 on tumor cells and CEACAM1 on NK cells to reverse CEACAM1-dependent inhibition of NK cytotoxicity.
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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 | 0.001 | 0.001 |
| 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".