Matrix Metalloproteinase-9 Functions as a Tumor Suppressor in Colitis-Associated Cancer
Bibliographic record
Abstract
There is a well-documented association of matrix metalloproteinase-9 (MMP-9) and receptor Notch-1 overexpression in colon cancer. We recently showed that MMP-9 is also upregulated in colitis, where it modulates tissue damage and goblet cell differentiation via proteolytic cleavage of Notch-1. In this study, we investigated whether MMP-9 is critical for colitis-associated colon cancer (CAC). Mice that are wild type (WT) or MMP-9 nullizygous (MMP-9(-/-)) were used for in vivo studies and the human enterocyte cell line Caco2-BBE was used for in vitro studies. CAC was induced in mice using an established carcinogenesis protocol that involves exposure to azoxymethane followed by treatment with dextran sodium sulfate. MMP-9(-/-) mice exhibited increased susceptibility to CAC relative to WT mice. Elevations in tumor multiplicity, size, and mortality were associated with increased proliferation and decreased apoptosis. Tumors formed in MMP-9(-/-) mice exhibited expression of p21(WAF1/Cip1) and increased expression of beta-catenin relative to WT mice. In vitro studies of MMP-9 overexpression showed increased Notch-1 activation with a reciprocal decrease in beta-catenin. Notch and beta-catenin/Wnt signaling have crucial roles in determining differentiation and carcinogenesis in gut epithelia. Despite being a mediator of proinflammatory responses in colitis, MMP-9 plays a protective role and acts as a tumor suppressor in CAC by modulating Notch-1 activation, thereby resulting in activation of p21(WAF1/Cip1) and suppression of beta-catenin.
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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) | 0.001 | 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".