Macrophage Elastase (Matrix Metalloproteinase-12) Suppresses Growth of Lung Metastases
Bibliographic record
Abstract
Matrix metalloproteinases (MMP) have been implicated in virtually all aspects of tumor progression. However, the recent failure of clinical trials employing synthetic MMP inhibitors in cancer chemotherapy has led us to hypothesize that some MMPs may actually serve the host in its defense against tumor progression. Here we show that mice deficient in macrophage elastase (MMP-12) develop significantly more gross Lewis lung carcinoma pulmonary metastases than their wild-type counterparts both in spontaneous and experimental metastasis models. The numbers of micrometastases between the two groups are equivalent; thus, it seems that MMP-12 affects lung tumor growth, and not metastasis formation, per se. MMP-12 is solely macrophage derived in this model, being expressed by tumor-associated macrophages and not by tumor or stromal cells. The presence of MMP-12 is associated with decreased tumor-associated microvessel density in vivo and generates an angiostatic>angiogenic tumor microenvironment that retards lung tumor growth independent of the production of angiostatin. These data define a role for MMP-12 in suppressing the growth of lung metastases and suggest that inhibitors designed to specifically target tumor-promoting MMPs may yet prove effective as cancer therapeutics.
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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) | 0.001 | 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 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".