Dual Regulation of MMP-2 Expression by the Type 1 Insulin-like Growth Factor Receptor
Bibliographic record
Abstract
The matrix metalloproteinase (MMP)-2 has been recognized as a major mediator of basement membrane degradation, angiogenesis, tumor invasion, and metastasis. The factors that regulate its expression have not, however, been fully elucidated. We previously identified the type I insulin-like growth factor (IGF-I) receptor as a regulator of MMP-2 synthesis. The objective of the present study was to investigate the signal transduction pathway(s) mediating this regulation. We show here that in Lewis lung carcinoma subline H-59 cells treated with IGF-I (10 ng/ml), the PI 3-kinase (phosphatidylinositol 3'-kinase) /protein kinase B (Akt) and C-Raf/ERK pathways were activated, and MMP-2 promoter activity, mRNA, and protein synthesis were induced. MMP-2 induction was blocked by the PI 3-kinase inhibitors LY294002 and wortmannin, by overexpression of a dominant-negative Akt or wild-type PTEN (phosphatase and tensin homologue deleted on chromosome 10), and by rapamycin. In contrast, a MEK inhibitor PD98059 failed to reduce MMP-2 promoter activation and actually increased MMP-2 mRNA and protein synthesis by up to 30%. Interestingly, suppression of PI 3-kinase signaling by a dominant-negative Akt enhanced ERK activity in cells stimulated with 10 ng/ml but not with 100 ng/ml IGF-I. Furthermore, at the higher (100 ng/ml) IGF-I concentration, C-Raf and ERK, but not PI 3-kinase activation, was enhanced, and this resulted in down-regulation of MMP-2 synthesis. This effect was reversed in cells expressing a dominant-negative ERK mutant. The results suggest that IGF-I can up-regulate MMP-2 synthesis via PI 3-kinase/Akt/mTOR (the mammalian target of rapamycin) signaling while concomitantly transmitting a negative regulatory signal via the Raf/ERK pathway. The outcome of IGF-IR (the receptor for IGF-I) activation may ultimately depend on factors, such as ligand bioavailability, that can shift the balance preferentially toward one pathway or the other.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".