Cyclooxygenase-2 Confers Growth Advantage to Syngeneic Pancreatic Cancer Cells
Bibliographic record
Abstract
Objectives: Targeting the cyclooxygenase-2 (COX-2)/prostanoid pathway is considered an intriguing approach for therapy and prevention of several cancers. However, the molecular mechanisms that underlie the protumorigenic properties of COX-2 in pancreatic cancer (PaCa) are still poorly understood. The purpose of the present study was to characterize the phenotype of COX-2 expressing syngeneic PaCa cells. Methods: Cyclooxygenase-2-negative MIA PaCa-2 cells were stably transduced with COX-2 or control viruses (MP2+COX-2 and MP2−COX-2). Prostaglandin E2 (PGE2) production was measured by liquid chromatography and tandem mass spectrometry. Anchorage-dependent and -independent cell growth was analyzed by cell count and 3-dimensional collagen cell culture system, respectively. Changes in apoptotic gene expression were measured by a polymerase chain reaction array. The growth of tumors in vivo was evaluated in a xenograft animal model. Results: Stable expression of COX-2 increased anchorage-dependent and -independent cell growth, which was accompanied by elevated PGE2 production. Several significant differences in apoptotic gene expression were detected between MP2+COX-2 and MP2−COX-2 cells. Furthermore, MP2+COX-2 cells grew faster than MP2−COX-2 cells in a xenograft animal model. Conclusions: Our results will provide the basis for more mechanistic studies on the role of COX-2 in PaCa and may help to develop novel therapeutic strategies aiming at the COX-2/prostanoid pathway. Abbreviations: COX-2 - cyclooxygenase-2, PGE2 - prostaglandin E2, PaCa - pancreatic cancer, LC-MS/MS - liquid chromatography and tandem mass spectrometry, AA - arachidonic acid, cPLA2 - cytoplasmic phospholipase A2, mPGES - microsomal prostaglandin E synthases, cPGES - cytoplasmic prostaglandin E synthases
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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) | 0.001 | 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) | 0.002 | 0.001 |
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".