ARID1A Mutations Promote P300-Dependent Endometrial Invasion through Super-Enhancer Hyperacetylation
Bibliographic record
Abstract
Endometriosis affects 1 in 10 women and is characterized by the presence of abnormal endometrium at ectopic sites. ARID1A mutations are observed in deeply invasive forms of the disease, often correlating with malignancy. To identify epigenetic dependencies driving invasion, we use an unbiased approach to map chromatin state transitions accompanying ARID1A loss in the endometrium. We show that super-enhancers marked by high H3K27 acetylation are strongly associated with ARID1A binding. ARID1A loss leads to H3K27 hyperacetylation and increased chromatin accessibility and enhancer RNA transcription at super-enhancers, but not typical enhancers, indicating that ARID1A normally prevents super-enhancer hyperactivation. ARID1A co-localizes with P300 at super-enhancers, and genetic or pharmacological inhibition of P300 in ARID1A mutant endometrial epithelia suppresses invasion and induces anoikis through the rescue of super-enhancer hyperacetylation. Among hyperactivated super-enhancers, SERPINE1 (PAI-1) is identified as an essential target gene driving ARID1A mutant endometrial invasion. Broadly, our findings provide rationale for therapeutic strategies targeting super-enhancers in ARID1A mutant endometrium.
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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) | 0.002 | 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".