Cyclooxygenase inhibitors block uterine tumorigenesis in <i>HMGA1a</i> transgenic mice and human xenografts
Bibliographic record
Abstract
Uterine cancer is a common cause for cancer death in women and there is no effective therapy for metastatic disease. Thus, research is urgently needed to identify new therapeutic agents. We showed previously that all female HMGA1a transgenic mice develop malignant uterine tumors, indicating that HMGA1a causes uterine cancer in vivo. We also demonstrated that HMGA1a up-regulates cyclooxygenase-2 (COX-2) during tumorigenesis in this model. Similarly, we found that HMGA1a and COX-2 are overexpressed in human leiomyosarcomas, a highly malignant uterine cancer. Although epidemiologic studies indicate that individuals who take COX inhibitors have a lower incidence of some tumors, these inhibitors have not been evaluated in uterine cancer. Here, we show that HMGA1a mice on sulindac (a COX-1/COX-2 inhibitor) have significantly smaller uterine tumors than controls. To determine if COX inhibitors are active in human uterine cancers that overexpress HMGA1a, we treated cultured cells with sulindac sulfide or celecoxib (a specific COX-2 inhibitor). Both drugs block anchorage-independent growth in high-grade human uterine cancer cells that overexpress HMGA1a (MES-SA cells). In contrast, neither inhibitor blocked transformation in cells that do not overexpress HMGA1a. Moreover, xenograft tumors from MES-SA cells were significantly inhibited in mice on sulindac. More strikingly, no tumors formed in mice on celecoxib. These preclinical studies suggest that COX inhibitors could play a role in preventing tumor onset or progression in uterine cancers with dysregulation of the HMGA1a-COX-2 pathway. Importantly, these drugs have lower toxicity than chemotherapeutic agents used to treat advanced-stage uterine cancers.
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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 | 0.000 | 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) | 0.000 | 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".