PET imaging of cyclooxygenase-2 (COX-2) in a pre-clinical colorectal cancer model
Bibliographic record
Abstract
BACKGROUND: Cyclooxygenase-2 (COX-2) is the inducible isoform of the cyclooxygenase enzyme family. COX-2 is involved in tumor development and progression, and frequent overexpression of COX-2 in a variety of human cancers has made COX-2 an important drug target for cancer treatment. Non-invasive imaging of COX-2 expression in cancer would be useful for assessing COX-2-mediated effects on chemoprevention and radiosensitization using COX-2 inhibitors as an emerging class of anti-cancer drugs, especially for colorectal cancer. Herein, we describe the radiopharmacological analysis of [(18)F]Pyricoxib, a novel radiolabeled COX-2 inhibitor, for specific PET imaging of COX-2 in colorectal cancer. METHODS: Uptake of [(18)F]Pyricoxib was assessed in human colorectal cancer cell lines HCA-7 (COX-2 positive) and HCT-116 (COX-2 negative). Standard COX-2 inhibitors were used to test for specificity of [(18)F]Pyricoxib for COX-2 binding in vitro and in vivo. PET imaging, biodistribution, and radiometabolite analyses were included into radiopharmacological evaluation of [(18)F]Pyricoxib. RESULTS: Radiotracer uptake in COX-2 positive HCA-7 cells was significantly higher than in COX-2 negative HCT-116 cells (P < 0.05). COX-2 inhibitors, celecoxib, rofecoxib, and SC58125, blocked uptake of [(18)F]Pyricoxib in HCA-7 cells in a concentration-dependent manner. The radiotracer was slowly metabolized in mice, with approximately 60 % of intact compound after 2 h post-injection. Selective COX-2-mediated tumor uptake of [(18)F]Pyricoxib in HCA-7 xenografts was confirmed in vivo. Celecoxib (100 mg/kg) selectively blocked tumor uptake by 16 % (PET image analysis; P < 0.05) and by 51 % (biodistribution studies; P < 0.01). CONCLUSIONS: The novel PET radiotracer [(18)F]Pyricoxib displays a promising radiopharmacological profile to study COX-2 expression in cancer in vivo.
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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 | 0.000 |
| 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".