MicroRNA-378a-5p Targets Cyclin G2 to Inhibit Fusion and Differentiation in BeWo Cells1
Bibliographic record
Abstract
MicroRNAs are expressed abundantly in the placenta throughout pregnancy. We have previously reported that microRNA (miR)-378a-5p promoted trophoblast migration and invasion. To further understand the role of miR-378a-5p during placental development, we investigated whether it may regulate the differentiation of syncytiotrophoblast (STB). Using a choriocarcinoma cell line, BeWo, we found that miR-378a-5p was down-regulated during forskolin-induced STB differentiation. Transfection of a miR-378a-5p mimic into BeWo cells decreased the formation of multinucleated STB, increased E-cadherin, and decreased the expression level of STB marker genes. On the other hand, transfection of anti-miR-378a-5p resulted in an increase in formation of multinucleated STB and expression of STB marker genes, as well as the loss of E-cadherin. Bioinformatic analysis revealed that miR-378a-5p has four potential binding sites at the 3' untranslated region (UTR) of cyclin G2 (CCNG2). Using luciferase reporter assays, we showed that miR-378a-5p decreased the luciferase activity of reporter constructs that contain CCNG2 3' UTR. In addition, miR-378a-5p decreased, whereas anti-miR-378a-5p increased, CCNG2 mRNA levels. Overexpression of CCNG2 increased the expression of syncytin-1 and fusion index and reversed the inhibitory effects of miR-378a-5p. In contrast, silencing of CCNG2 using siRNA increased E-cadherin and decreased syncytin-1 levels. These findings provide initial evidence that CCNG2 promotes STB differentiation and suggest that miR-378a-5p exerts an inhibitory role in STB differentiation, in part, by down-regulating CCNG2 expression, in the BeWo cell model.
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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 | 0.001 |
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".