EGF-induced trophoblast secretion of MMP-9 and TIMP-1 involves activation of both PI3K and MAPK signalling pathways
Bibliographic record
Abstract
Epidermal growth factor (EGF) is present in the maternal-fetal environment and has an important role in placental development. Matrix metalloproteinase-9 (MMP-9) expression/activation is a pre-requisite in extravillous trophoblast invasion. Whereas EGF up-regulates MMP-9 activity in a variety of cell types, there is no direct evidence for the stimulation of MMP-9 and tissue inhibitor of metalloproteinase-1 (TIMP-1) secretion by EGF in extravillous trophoblasts. In addition, the signalling pathways involved in this regulation are not clear. In the present study, we have examined the possible involvement of the phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) pathways in the regulation of the MMP-9/TIMP-1 system by EGF in vitro. We used a well-established invasive extravillous trophoblast cell line (HTR8/Svneo) and measured gene and protein expression by semi-quantitative RT-PCR and western analysis respectively. MMP activity was determined by zymography. We showed for the first time that EGF activated both PI3K/Akt and MAPK/extracellular-signal regulated kinase (ERK) signalling in HTR8/SVneo, and increased both MMP-9 and TIMP-1 mRNAs and protein concentrations. Interfering with either signalling pathway via PI3K inhibitor LY294002 or MEK inhibitor U0126 in EGF-stimulated HTR8/SVneo cells blocked the induction of MMP-9 and TIMP-1. LY294002 inhibited Akt phosphorylation, but had no effect on ERK phosphorylation; U0126 suppressed ERK phosphorylation without interfering with the phosphorylation of Akt. In addition, expression of constitutively active Akt (Myr-Akt1, Myr-Akt2, Myr-Akt3) was not sufficient to induce proMMP-9 and TIMP-1 secretion. Our results suggest that the activation of both PI3K and MAPK pathways in extravillous trophoblasts is necessary for the up-regulation of MMP-9 and TIMP-1 expression by EGF.
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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".