Comparison of the effects of EM‐652 (SCH57068), tamoxifen, toremifene, droloxifene, idoxifene, GW‐5638 and raloxifene on the growth of human ZR‐75‐1 breast tumors in nude mice
Bibliographic record
Abstract
EM-652 exerts pure antiestrogenic activity in the mammary gland and endometrium, while tamoxifen, the antiestrogen most widely used for the treatment of breast cancer, exerts mixed antiestrogenic-estrogenic activity in these tissues. Our objective was to compare the agonistic and antagonistic effects of EM-652 with tamoxifen and 5 other antiestrogens on the growth of ZR-75-1 human breast xenografts in ovariectomized nude mice. During the 23 weeks of treatment at a daily oral dose of 50 microg, EM-652 was the only compound that decreased tumor size relative to pretreatment values, whereas the 6 other antiestrogens only decreased to various extents the progression rate stimulated by estrone. Under estrone stimulation, all groups of animals had more than 60% of their tumors in the progression category except for the EM-652-treated group, where only 7% of the tumors progressed. In the absence of estrone stimulation, progression was seen in 60%, 33%, 21% and 12% of tumors in the tamoxifen-, idoxifene-, toremifene- and raloxifene-treated groups, respectively, while only 4% of tumors progressed in the EM-652-treated group. The agonistic and antagonistic actions of each antiestrogen were also measured on endometrial epithelial cell thickness. Our present findings indicate that EM-652, in addition to being the most potent antiestrogen on human breast tumor growth, has no agonistic effect in breast and endometrial tissues. Since previous data have shown benefits of EM-652 on bone density and lipid profile, this compound could be an ideal candidate for chemoprevention of breast and uterine cancers, while protecting against osteoporosis and cardiovascular disease.
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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 | 0.001 | 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".