37-kDa Laminin Receptor Precursor Mediates GnRH-II–Induced MMP-2 Expression and Invasiveness in Ovarian Cancer Cells
Bibliographic record
Abstract
GnRH-II enhances ovarian cancer cell invasion in an autocrine manner. We have now found that GnRH-II increases 37-kDa laminin receptor precursor (LRP) production in GnRH receptor (GnRHR)-positive OVCAR-3 and CaOV-3 ovarian cancer cells, while small interfering RNA (siRNA)-mediated depletion of GnRH-II or GnRHR mRNA abrogates this. The invasiveness of ovarian cancer cells is also reduced >85% by siRNA-mediated knockdown of LRP levels and >50% by pretreatment of Matrigel with a synthetic peptide that blocks interactions between laminin and the 67-kDa nonintegrin laminin receptor which comprises two LRP subunits. Conversely, overexpressing LRP in CaOV-3 cells increases their invasiveness 5-fold, while overexpressing LRP with a nonfunctional laminin-binding site does not. Depletion of LRP by siRNA treatment reduces CaOV-3 cell attachment to laminin-coated plates by ∼80% but only reduces their binding to Matrigel by ∼20%. Thus, while LRP influences CaOV-3 cell adhesion to laminin, LRP must act in other ways to enhance invasion. Matrix metalloproteinases (MMPs) are key mediators of invasion, and LRP siRNA treatment of OVCAR-3 and CaOV-3 cells inhibits MMP-2 but not MMP-9 mRNA levels. Overexpressing LRP in these cells increases MMP-2 production specifically, while a laminin-binding deficient LRP does not. Importantly, LRP siRNA treatment abolishes GnRH-II-induced MMP-2 production, and invasion in OVCAR-3 and CaOV-3 cells, which was also seen after MMP-2 siRNA treatment. These results suggest that GnRH-II-induced LRP expression increases the amount of the 67-kDa nonintegrin laminin receptor, which appears to interact with laminin in the extracellular matrix to promote MMP-2 expression and enhance ovarian cancer cell invasion.
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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) | 0.001 | 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 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".