Circulating Estrogens in Endometrial Cancer Cases and Their Relationship with Tissular Expression of Key Estrogen Biosynthesis and Metabolic Pathways
Bibliographic record
Abstract
BACKGROUND: Endometrial cancer is the most common gynecological malignancy. Estrogen exposure is strongly associated with endometrial cancer. Whereas this cancer occurs predominantly in postmenopausal women lacking estrogen production by ovaries, the conversion of adrenal androgen-estrogen precursors to estradiol (E(2)), estrone (E(1)), and its sulfate (E(1)-S) has been well documented in peripheral tissues. EXPERIMENTAL DESIGN: We initially explored whether circulating levels of estrogens, measured by validated mass spectrometry assays, differ in women with endometrial cancer (n = 126) compared with healthy women (n = 110). We then evaluated by quantitative real-time PCR from purified RNA whether the expression profile of 19 estrogen-related synthesis and metabolic genes is modified in peritumoral normal endometrium (n = 36) compared with tumoral (n = 49) tissues. RESULTS: In endometrial cancer cases, circulating levels of E(1), E(2), and E(1)-S were significantly higher compared with unaffected controls. In agreement with plasma levels, findings support an enhanced biosynthesis of E(2) in tumors. The expression of E(2) biosynthesis pathways [E(1)-S (sulfatase) --> E(1) (17beta-hydroxysteroid dehydrogenase) --> E(2)] was shown to predominate in peritumoral normal endometrium and was significantly increased in tumors. In addition, the inactivation pathways mediated by several uridine diphosphate-glucuronosyltransferases were also enhanced in endometrial tumors compared with peritumoral normal endometrium. CONCLUSION: We concluded that the higher levels of circulating estrogens in women with endometrial cancer are likely associated with an imbalance of multiple biotransformation pathways in endometrial tumor tissues.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".