COX-2-Dependent and COX-2-Independent Mode of Action of Celecoxib in Human Liver Cancer Cells
Bibliographic record
Abstract
Celecoxib (Celebrex((R)), Pfizer) is a selective cyclooxygenase-2 (COX-2) inhibitor with chemopreventive and antitumor effects. However, it is now well known that celecoxib has several COX-2-independent activities. To better understand COX-2-independent molecular mechanisms underlying the antitumor activity of celecoxib, we investigated the expression profile of the celecoxib-treated COX-2-positive (Huh7) and COX-2-negative (HepG2) liver cancer cell lines, using microarray analysis. Celecoxib treatment resulted in significantly altered expression levels of 240 and 403 transcripts in Huh7 and HepG2 cells, respectively. Confirmation of the microarray results was performed for selected genes by semiquantitative RT-PCR. A pathway/functional analysis of celecoxib-affected transcripts, using ingenuity pathway analysis and exploring biological association networks, revealed that celecoxib modulates expression of numerous genes involved in a variety of cellular processes, including cell death, cellular growth and proliferation, lipid metabolism, and energy turnover. Some of these processes were common for both HCC cell lines and seem to be coupled with NF-κB signaling, while others were cell-specific and possibly linked to the presence or the absence of COX-2 activity in the corresponding cell line. Many novel genes emerged from our analyses that were not previously reported to be affected by celecoxib. Further studies on selected celecoxib-responsive genes will establish if they may serve as potential molecular targets for more effective therapeutic strategies in HCC.
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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) | 0.002 | 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".