miR-590-3p Targets Cyclin G2 and FOXO3 to Promote Ovarian Cancer Cell Proliferation, Invasion, and Spheroid Formation
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Bibliographic record
Abstract
Ovarian cancer is the leading cause of death from gynecological cancers. MicroRNAs (miRNAs) are small, non-coding RNAs that interact with the 3' untranslated region (3' UTR) of target genes to repress their expression. We have previously reported that miR-590-3p promoted ovarian cancer growth and metastasis, in part by targeting Forkhead box A (FOXA2). In this study, we further investigated the mechanisms by which miR-590-3p promotes ovarian cancer development. Using luciferase reporter assays, real-time PCR, and Western blot analyses, we demonstrated that miR-590-3p targets cyclin G2 (CCNG2) and Forkhead box class O3 (FOXO3) at their 3' UTRs. Silencing of CCNG2 or FOXO3 mimicked, while the overexpression of CCNG2 or FOXO3 reversed, the stimulatory effect of miR-590-3p on cell proliferation and invasion. In hanging drop cultures, the overexpression of mir-590 or the transient transfection of miR-590-3p mimics induced the formation of compact spheroids. Transfection of the CCNG2 or FOXO3 plasmid into the mir-590 cells resulted in the partial disruption of the compact spheroid formation. Since we have shown that CCNG2 suppressed β-catenin signaling, we investigated if miR-590-3p regulated β-catenin activity. In the TOPFlash luciferase reporter assays, mir-590 increased β-catenin/TCF transcriptional activity and the nuclear accumulation of β-catenin. Silencing of β-catenin attenuated the effect of mir-590 on the compact spheroid formation. Taken together, these results suggest that miR-590-3p promotes ovarian cancer development, in part by directly targeting CCNG2 and FOXO3.
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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 it