A distinct mechanism of epigenetic reprogramming silences PAX2 and initiates endometrial carcinogenesis
Bibliographic record
Abstract
Functional inactivation of tumor suppressor genes drives cancer initiation, progression, and treatment responses. Most tumor suppressor genes are inactivated through 1 of 2 well-characterized mechanisms: DNA-level mutations, such as point mutations or deletions, and promoter DNA hypermethylation. Here, we report a distinct third mechanism of tumor suppressor inactivation based on alterations to the histone rather than DNA code. We demonstrated that PAX2 is an endometrial tumor suppressor recurrently inactivated by a distinct epigenetic reprogramming event in more than 80% of human endometrial cancers. Integrative transcriptomic, epigenomic, 3D genomic, and machine learning analyses showed that PAX2 transcriptional downregulation is associated with replacement of open/active chromatin features (H3K27ac/H3K4me3) with inaccessible/repressive chromatin features (H3K27me3) in a framework dictated by 3D genome organization. The spread of the repressive H3K27me3 signal resembled a pearl necklace, with its length modulated by cohesin loops, thereby preventing transcriptional dysregulation of neighboring genes. This mechanism, involving the loss of a promoter-proximal superenhancer, was shown to underlie transcriptional silencing of PAX2 in human endometrial cancers. Mouse and human preclinical models established PAX2 as a potent endometrial tumor suppressor. Functionally, PAX2 loss promoted endometrial carcinogenesis by rewiring the transcriptional landscape via global enhancer reprogramming. The discovery that most endometrial cancers originate from a recurring epigenetic alteration carries profound implications for their diagnosis and treatment.
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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".