Inhibition of COX-2 in Colon Cancer Modulates Tumor Growth and MDR-1 Expression to Enhance Tumor Regression in Therapy-Refractory Cancers In Vivo
Bibliographic record
Abstract
Higher cyclooxygenase 2 (COX-2) expression is often observed in aggressive colorectal cancers (CRCs). Here, we attempt to examine the association between COX-2 expression in therapy-refractory CRC, how it affects chemosensitivity, and whether, in primary tumors, it is predictive of clinical outcomes. Our results revealed higher COX-2 expression in chemoresistant CRC cells and tumor xenografts. In vitro, the combination of either aspirin or celecoxib with 5-fluorouracil (5-FU) was capable of improving chemosensitivity in chemorefractory CRC cells, but a synergistic effect with 5-FU could only be demonstrated with celecoxib. To examine the potential clinical significance of these observations, in vivo studies were undertaken, which also showed that the greatest tumor regression was achieved in chemoresistant xenografts after chemotherapy in combination with celecoxib, but not aspirin. We also noted that these chemoresistant tumors with higher COX-2 expression had a more aggressive growth rate. Given the dramatic response to a combination of celecoxib + 5-FU, the possibility that celecoxib may modulate chemosensitivity as a result of its ability to inhibit MDR-1 was examined. In addition, assessment of a tissue microarray consisting of 130 cases of CRCs revealed that, in humans, higher COX-2 expression was associated with poorer survival with a 68% increased risk of mortality, indicating that COX-2 expression is a marker of poor clinical outcome. The findings of this study point to a potential benefit of combining COX-2 inhibitors with current regimens to achieve better response in the treatment of therapy-refractory CRC and in using COX-2 expression as a prognostic marker to help identify individuals who would benefit the greatest from closer follow-up and more aggressive therapy.
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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".