Identification of Estrogen Response Element in the Aquaporin-2 Gene That Mediates Estrogen-Induced Cell Migration and Invasion in Human Endometrial Carcinoma
Bibliographic record
Abstract
BACKGROUND: Accumulating evidence suggests that aquaporins (AQP) can facilitate cell migration, invasion, and proliferation in tumor development in addition to water transport. OBJECTIVE: The aim of this study was to examine AQP2 expression in the endometrial tissues from patients with endometrial carcinoma (EC) and determine the roles and mechanisms of AQP2 in estrogen-related cell migration, invasion, adhesion, and proliferation of Ishikawa (IK) cells. APPROACH: AQP2 expression levels were measured in human endometrial cells and estradiol (E(2))-treated IK cells, and the estrogen-response element was identified. After blocking down and up-regulating the endogenous expression of AQP2 in IK cells, cell morphology, capacity for invasion, migration and adhesion, and expression markers of membrane/cytoskeleton were analyzed. RESULTS: AQP2 was expressed in endometrial tissues from patients with EC and endometriosis, both of which are estrogen-dependent diseases. In IK cells, E(2) dose-dependently increased AQP2 expression, which was blocked by the estrogen receptor inhibitor ICI182780. An estrogen-response element was identified in the AQP2 promoter. E(2) significantly increased the migration, invasion, adhesion, and proliferation of IK cells. AQP2 knockdown attenuated E(2)-enhanced migration, invasion, and adhesion. AQP2 knockdown reduced not only the E(2)-enhanced expression of F-actin and annexin-2 but also the E(2)-induced alteration of cell morphology. Moreover, higher expression levels of F-actin and annexin-2 were detected in the endometrial tissues from patients with EC. CONCLUSIONS: AQP2 mediates E(2)-enhanced migration, invasion, and adhesion through alteration of F-actin and annexin-2 expression and reorganization of F-actin, and inhibition of AQP may be a potential method for antitumor therapy.
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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 | 0.000 | 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) | 0.001 | 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".