Study on the mechanism of USP7 promoting endometriosis by regulating DNMT1 deubiquitination level
Bibliographic record
Abstract
Endometriosis is characterized by aberrant epigenetic regulation, and our study reveals that both Ubiquitin Specific Protease 7 (USP7) and DNA methyltransferase 1 (DNMT1) are significantly overexpressed in endometriosis tissues. Functional analyses in ectopic endometrial stromal cells (EESCs) indicate that elevated USP7 levels markedly enhance cellular proliferation, migration, and invasion, whereas silencing DNMT1 mitigates these oncogenic properties. Notably, USP7 and DNMT1 co-localize within the nucleus and interact directly, with USP7 modulating DNMT1 stability by attenuating its ubiquitination. The reduction in DNMT1 protein levels following USP7 silencing was reversed by proteasome inhibition, underscoring the pivotal role of USP7-mediated deubiquitination in maintaining DNMT1 stability. Furthermore, treatment with the USP7 inhibitor FT-671 significantly reduced DNMT1 protein expression while leaving its mRNA levels unaffected, and FT-671 effectively suppressed EESCs proliferation, migration, and invasion. Collectively, these findings suggest that USP7 contributes to the pathogenesis of endometriosis by sustaining DNMT1 expression and promoting aberrant cellular behaviors, thereby representing a promising therapeutic target for this disease.
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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 | 0.000 |
| 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".