High Histone Deacetylase 2/3 Expression in Non-Functioning Pituitary Tumors
Bibliographic record
Abstract
Epigenetic modification of chromatin is involved in non-malignant pituitary neoplasia by causing abnormal expression of tumor suppressors and oncogenes. These changes are potentially reversible, suggesting the possibility of targeting tumor cells by restoring the expression of epigenetically silenced tumor suppressors. The role of the histone deacetylase (HDAC) family in pituitary tumorigenesis is not known. We report that HDAC2 and 3, Class I HDAC members, are highly expressed in clinically non-functioning pituitary adenomas (NFPAs) compared to normal pituitary (NP) samples as determined by RT-PCR and immunohistochemical staining (IHC). Treatment of a human NFPA derived folliculostellate cell line, PDFS, with the HDAC3 inhibitor RGFP966 for 96 hours resulted in inhibition of cell proliferation by 70%. Furthermore, the combination of RGFP966 with a methyltransferase/DNMT inhibitor, 5'-aza-2'-deoxycytidine, led to the restoration of the expression of several tumor suppressor genes, including STAT1, P16, PTEN, and the large non-coding RNA tumor suppressor MEG3, in PDFS cells. Our data support the hypothesis that both histone modification and DNA methylation are involved in the pathogenesis of human NFPAs and suggest that targeting HDACs and DNA methylation can be incorporated into future therapies.
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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".