TEM8 Tri-specific Killer Engager binds both tumor and tumor stroma to specifically engage natural killer cell anti-tumor activity
Bibliographic record
Abstract
BACKGROUND: The tumor microenvironment contains stromal cells, including endothelial cells and fibroblasts, that aid tumor growth and impair immune cell function. Many solid tumors remain difficult to cure because of tumor-promoting stromal cells, but current therapies targeting tumor stromal cells are constrained by modest efficacy and toxicities. TEM8 is a surface antigen selectively upregulated on tumor and tumor stromal cells, endothelial cells and fibroblasts that may be targeted with specific natural killer (NK) cell engagement. METHODS: A Tri-specific Killer Engager (TriKE) against TEM8-'cam1615TEM8'-was generated using a mammalian expression system. Its function on NK cells was assessed by evaluation of degranulation, inflammatory cytokine production, and killing against tumor and stroma cell lines in standard co-culture and spheroid assays. cam1615TEM8-mediated proliferation and STAT5 phosphorylation in NK cells was tested and compared with T cells by flow cytometry. NK cell proliferation, tumor infiltration, and tumor and tumor-endothelium killing by cam1615TEM8 and interleukin-15 (IL-15) were assessed in NOD scid gamma (NSG) mice. RESULTS: cam1615TEM8 selectively stimulates NK cell degranulation and inflammatory cytokine production against TEM8-expressing tumor and stromal cell lines. The increased activation translated to superior NK cell killing of TEM8-expressing tumor spheroids. cam1615TEM8 selectively stimulated NK cell but not T cell proliferation in vitro and enhanced NK cell proliferation, survival, and tumor infiltration in vivo. Finally, cam1615TEM8 stimulated NK cell killing of tumor and tumor endothelial cells in vivo. CONCLUSIONS: Our findings indicate that the cam1615TEM8 TriKE is a novel anti-tumor, anti-stroma, and anti-angiogenic cancer therapy for patients with solid tumors. This multifunctional molecule works by selectively targeting and activating NK cells by costimulation with IL-15, and then targeting that activity to TEM8+ tumor cells and TEM8+ tumor stroma.
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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) | 0.003 | 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".