Cyclooxygenase-2 Functions as a Downstream Mediator of Lysophosphatidic Acid to Promote Aggressive Behavior in Ovarian Carcinoma Cells
Bibliographic record
Abstract
Elevated levels of the bioactive lipid lysophosphatidic acid (LPA) are detectable in the majority of patients with both early- and late-stage ovarian cancer, suggesting that LPA promotes early events in ovarian carcinoma dissemination. LPA contributes to the development, progression, and metastasis of ovarian cancer in part by inducing the expression of genes that contribute to proliferation, survival, or invasion, including cyclooxgenase-2 (COX-2) and matrix metalloproteinase-2 (MMP-2). We have previously shown that LPA promotes proMMP-2 activation and MMP-2-dependent migration and invasion in ovarian cancer cells. The purpose of the current study was to determine whether the effect of LPA on acquisition of the metastatic phenotype in ovarian cancer cells is mediated via a COX-2-dependent mechanism. Immunohistochemical analysis of 173 ovarian tumors showed strong COX-2 immunoreactivity in 63% of tumor specimens, including 50% of borderline tumors. LPA increased COX-2 protein expression in a time- and concentration-dependent manner in two of three immortalized borderline ovarian epithelial cells as well as in four of six ovarian cancer cell lines. This was accomplished by both activation of the Edg/LPA receptor and LPA-mediated transactivation of the epidermal growth factor receptor, which increased COX-2 expression via the Ras/mitogen-activated protein kinase pathway. COX-2 also played a role in LPA-induced invasion and migration, as treatment with the COX-2 specific inhibitor NS-398 reduced LPA-induced proMMP-2 protein expression and activation and blocked MMP-dependent motility and invasive activity. These data show that COX-2 functions as a downstream mediator of LPA to potentiate aggressive cellular behavior.
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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".