Cyclin G2 inhibits epithelial-to-mesenchymal transition by disrupting Wnt/β-catenin signaling
Bibliographic record
Abstract
Epithelial ovarian cancer (EOC) has the highest mortality rate among gynecological malignancies owing to poor screening methods, non-specific symptoms and limited knowledge of the cellular targets that contribute to the disease. Cyclin G2 is an unconventional cyclin that acts to oppose cell cycle progression. Dysregulation of the cyclin G2 gene (CCNG2) in a variety of human cancers has been reported; however, the role of cyclin G2 in tumorigenesis remains unclear. In this study, we investigated the function of cyclin G2 in EOC. In vitro and in vivo studies using several EOC-derived tumor cell lines revealed that cyclin G2 inhibited cell proliferation, migration, invasion and spheroid formation, as well as tumor formation and invasion. By interrogating cDNA microarray data sets, we found that CCGN2 mRNA is reduced in several large cohorts of human ovarian carcinoma when compared with normal ovarian surface epithelium or borderline tumors of the ovary. Mechanistically, cyclin G2 was found to suppress epithelial-to-mesenchymal transition (EMT), as demonstrated by the differential regulation of various EMT genes, such as Snail, Slug, vimentin and E-cadherin. Moreover, cyclin G2 potently suppressed the Wnt/β-catenin signaling pathway by downregulating key Wnt components, namely LRP6, DVL2 and β-catenin, which could be linked to inhibition of EMT. Taken together, our novel findings demonstrate that cyclin G2 has potent tumor-suppressive effects in EOCs by inhibiting EMT through attenuating Wnt/β-catenin signaling.
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How this classification was reachedexpand
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 | 0.001 |
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 teacher head, 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".