Inflammation Induced by MMP-9 Enhances Tumor Regression of Experimental Breast Cancer
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Bibliographic record
Abstract
Matrix metalloproteinases (MMPs) have been suggested as therapeutic targets in cancer treatment, but broad-spectrum MMP inhibitors have failed in clinical trials. Recent data suggest that several MMPs including MMP-9 exert both pro- and antitumorigenic properties. This is also the case of the natural inhibitors of MMPs, tissue inhibitor of metalloproteinases (TIMPs). The inhibitor of MMP-9 is TIMP-1, and high levels of this enzyme have been associated with decreased survival in breast cancer. Inflammation is one hallmark of cancer progression, and MMPs/TIMPs may be involved in the local immune regulation. We investigated the role of MMP-9/TIMP-1 in regulating innate antitumor immunity in breast cancer. Breast cancers were established in nude mice and treated with intratumoral injections of adenoviruses carrying the human TIMP-1 or MMP-9 gene (AdMMP-9). In vivo microdialysis for sampling of cancer cell-derived (human) and stroma-derived (murine) proteins, immunostainings, as well as cell cultures were performed. We report a dose-dependent decrease of tumor growth and angiogenesis after AdMMP-9 treatment. In addition to increased generation of endostatin, AdMMP-9 promoted an antitumor immune response by inducing massive neutrophil infiltration. Neutrophil depletion prior to gene transfer abolished the therapeutic effects of AdMMP-9. Additionally, AdMMP-9 activated tumor-infiltrating macrophages into a tumor-inhibiting phenotype both in vivo and in vitro. AdMMP-9 also inhibited tumor growth in immune-competent mice bearing breast cancers. Adenoviruses carrying the human TIMP-1 gene had no effect on tumor growth or the immune response. Our novel data identify MMP-9 as a potent player in modulating the innate immune response into antitumor activities.
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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) | 0.000 | 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 | 0.000 |
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 it