The Association between Functional Polymorphisms of COX-2 and Serum PGE2 Level in ESCC Patients in North of Iran
Bibliographic record
Abstract
Background: Esophageal cancer is recognized as one of the most fatal diseases around the world. Many factors are involved in the development of esophageal cancer, including genetic factors and inflammation. Cyclooxygenase-2 (COX-2) and its downstream signaling are the most important proinflammatory factors contributing to cancer. The present study aimed to evaluate the relationship between the polymorphisms and expression of COX-2 and prostaglandin-E2 (PGE2) level in patients with esophageal squamous cell carcinoma (ESCC) in Golestan Province (Iran), situated on the “esophageal cancer belt”. Methods: In this case-control study, blood and biopsy samples were obtained from ESCC patients and healthy controls. The COX-2 polymorphisms for -1195, -1290, -765, and +8473 SNPs were assayed using PCR-RFLP assay, while the level of PGE2 was measured using an ELISA kit. In addition, real-time PCR assay and immunohistochemistry (IHC) were performed to assay mRNA and protein expression of COX-2, respectively. Results: An association was found between 8473TC genotype and risk of ESCC (OR= 5.417, P= 0.036). In addition, mRNA and protein expression of COX-2 in ESCC patients was higher than the controls (P=0.001 and P=0.048, respectively). Based on the findings, the level of PGE-2 was significantly higher in ESCC patients, compared to the controls (P= 0.045). However, ROC curve analysis revealed PGE2 is a weak biomarker for diagnosis of ESCC. There was a significant relationship between the level of PGE2 and 8473CC, 8473TC, -765CC, and -1290AA genotypes (P= 0.028, P= 0.022, P= 0.024, and P= 0.011, respectively). Conclusion: Based on our results, functional polymorphisms of COX-2 (8473CC, 8473TC, - 765CC, and -1290AA) increase PGE2 level and carriers of these polymorphisms might be more susceptible to ESCC.
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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 | 0.003 | 0.001 |
| 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) | 0.000 | 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".