Alteration of Pituitary Tumor Transforming Gene-1 Regulates Trophoblast Invasion via the Integrin/Rho-Family Signaling Pathway
Bibliographic record
Abstract
Trophoblast invasion ability is an important factor in early implantation and placental development. Recently, pituitary tumor transforming gene 1 (PTTG1) was shown to be involved in invasion and proliferation of cancer. However, the role of PTTG1 in trophoblast invasion remains unknown. Thus, in this study we analyzed PTTG1 expression in trophoblasts and its effect on trophoblast invasion activity and determined the mechanism through which PTTG1 regulates trophoblast invasion. Trophoblast proliferation and invasion abilities, regardless of PTTG1 expression, were analyzed by quantitative real-time polymerase chain reaction, fluorescence-activated cell sorting analysis, invasion assay, western blot, and zymography after treatment with small interfering RNA against PTTG1 (siPTTG1). Additionally, integrin/Rho-family signaling in trophoblasts by PTTG1 alteration was analyzed. Furthermore, the effect of PTTG1 on trophoblast invasion was evaluated by microRNA (miRNA) mimic and inhibitor treatment. Trophoblast invasion was significantly reduced through decreased matrix metalloproteinase (MMP)-2 and MMP-9 expression when PTTG1 expression was inhibited by siPTTG1 (p < 0.05). Furthermore, knockdown of PTTG1 increased expression of integrin alpha 4 (ITGA4), ITGA5, and integrin beta 1 (ITGB1); otherwise, RhoA expression was significantly decreased (p < 0.05). Treatment of miRNA-186-5p mimic and inhibitor controlled trophoblast invasion ability by altering PTTG1 and MMP expression. PTTG1 can control trophoblast invasion ability via regulation of MMP expression through integrin/Rho-family signaling. In addition, PTTG1 expression and its function were regulated by miRNA-186-5p. These results help in understanding the mechanism through which PTTG1 regulates trophoblast invasion and thereby implantation and placental development.
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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".