New cancer drugs targeting the biosynthesis of estrogens and androgens
Bibliographic record
Abstract
Abstract The enzymes involved in the synthesis of steroids are very interesting therapeutic targets. By reducing the levels of androgens and estrogens that stimulate the proliferation of cancer cells, a potent and selective inhibitor of a key‐steroidogenic enzyme may become an alternative or a complementary strategy to the use of an antiandrogen or an antiestrogen for the treatment of prostate cancer or breast and endometrial cancers, respectively. Five enzymes, namely 17α‐hydroxylase 17α‐lyase, aromatase, 17β‐hydroxysteroid dehydrogenases, 5α‐reductases, and steroid sulfatase were especially studied and found to be interesting targets for the development of inhibitors as potential cancer drugs. The present review will summarize the role of these five enzymes and their inhibitors with a special highlight about the molecules more recently reported in the literature and exhibiting dual therapeutic action. Drug Dev Res 69:304–318, 2008. © 2008 Wiley‐Liss, Inc.
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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 | 0.001 | 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) | 0.005 | 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".