miR-21 down-regulation promotes apoptosis and inhibits invasion and migration abilities of OVCAR3 cells
Bibliographic record
Abstract
PURPOSE: To investigate the influence of miR-21 down-regulation on cell proliferation, apoptosis, invasion and migration of ovarian papillary adenocarcinoma cell lines (OVCAR3). METHODS: Short-hairpin RNA (shRNA), specifically targeting miR-21, was constructed and transfected into OVCAR3 cells using the pSIREN-RetroQ linear vector (pSIREN-miR-21). The expression of miR-21 was detected with stem-loop real-time RT-PCR in OVCAR3 cells. Cell proliferation and apoptosis were monitored using the MTT assay and flow cytometry, respectively. Cell migration and invasion were assessed using the transwell migration and scratch-wound assay, respectively. Western-bloting was used for PDCD4 protein expression. RESULTS: pSIREN-miR-21 suppressed miR-21 expression in OVCAR3 cells. miR-21 expression levels in pSIREN-miR-21 cells was 0.3 ± 0.1, which was significantly lower when compared with pSIREN-miR-21-Neg and control groups (P < 0.01). Cell inhibition rate in the pSIREN-miR-21 group was higher than the control group (29.4% vs 9.0%, P < 0.01), as was the percentage of apoptotic and necrotic cells. By transwell migration assay, the number of cells migrating in the pSIREN-miR-21 group was significantly lower than in the control group. In addition, fewer cells were observed in the wounded area of the pSIREN-miR-21 group following the scratch-wound assay. PDCD4 expression was increased in OVCAR-3 cells transfected by pSIREN-miR-21 compared with vector-control transfected cells. Moreover, the optical density of the transfected cells was significantly lower than the two control groups. CONCLUSION: Down-regulation of miR-21 dramatically increased apoptotic cell death and decreased cell proliferation, invasion and migration in OVCAR3 cells. MiR-21 may play an important role in the biological behaviors of epithelial ovarian carcinoma cells through negative control of the expression of PDCD4.
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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 | 0.001 |
| 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".