Anticancer activity of a human monoclonal antibody inhibitor of MMP-14
Bibliographic record
Abstract
B215 Over the last 3 decades, there has been a marked improvement in certain cancer remission and survival rates, yet a significant unmet medical need exists by way of treating and prolonging the lives of patients with advanced disease and difficult to treat cancers. Therapies that operate on alternative mechanisms offer a new means to not only slow or halt disease progression but also extend survival. Selective inhibition of the activity of matrix metalloproteinases (MMPs) could provide an attractive non-cytotoxic approach towards improving the therapy of cancers. Antibodies provide the potential for a new generation of protease inhibitors with high levels of potency and selectivity. Combining our human antibody phage display library with automated selection and screening strategies, we have isolated DX-2400, a potent and selective inhibitor of MMP-14. DX-2400 binds to MMP-14 expressing cells and potently inhibits human, mouse and rat MMP-14 activity (Ki blocks proMMP-2 activation of MMP-14/MMP-2 expressing cancer cells. DX-2400 also potently inhibits HUVEC tube formation in vitro . Immunohistochemical analysis on primary human breast tumor tissues reveals an overall MMP-14 detection rate with DX-2400 of 54%. DX-2400 retards tumor progression and metastasis in multiple subcutaneous and orthotopic tumor models in nude mice. Chronic administration of DX-2400 significantly decreases total MMP activity extracted from tumor tissue confirming the proximal role of MMP-14 in activating the cascade of metalloproteinase activity leading to tumor progression. Immunohistochemical analysis of experimental tumor tissue sections reveals a significant decrease in Ki67-positive tumor cells and CD31-positive tumor microvessel hot spots in the tumors from DX-2400-treated animals, demonstrating both anti-tumoral and anti-angiogenic activity of this novel inhibitor. This fully human antibody represents an innovative approach for the inhibition of MMP-14 activity and is a candidate for therapeutic development.
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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 | 0.000 |
| 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".