p21 <sup>Cip1</sup> restrains pituitary tumor growth
Bibliographic record
Abstract
As commonly encountered, pituitary adenomas are invariably benign. We therefore studied protective pituitary proliferative mechanisms. Pituitary tumor transforming gene (Pttg) deletion results in pituitary p21 induction and abrogates tumor development in Rb(+/-)Pttg(-/-) mice. p21 disruption restores attenuated Rb(+/-)Pttg(-/-) pituitary proliferation rates and enables high penetrance of pituitary, but not thyroid, tumor growth in triple mutant animals (88% of Rb(+/-) and 72% of Rb(+/-)Pttg(-/-)p21(-/-) vs. 30% of Rb(+/-)Pttg(-/-) mice developed pituitary tumors, P < 0.001). p21 deletion also accelerated S-phase entry and enhanced transformation rates in triple mutant MEFs. Intranuclear p21 accumulates in Pttg-null aneuploid GH-secreting cells, and GH(3) rat pituitary tumor cells overexpressing PTTG also exhibited increased levels of mRNA for both p21 (18-fold, P < 0.01) and ATM (9-fold, P < 0.01). PTTG is abundantly expressed in human pituitary tumors, and in 23 of 26 GH-producing pituitary adenomas with high PTTG levels, senescence was evidenced by increased p21 and SA-beta-galactosidase. Thus, either deletion or overexpression of Pttg promotes pituitary cell aneuploidy and p53/p21-dependent senescence, particularly in GH-secreting cells. Aneuploid pituitary cell p21 may constrain pituitary tumor growth, thus accounting for the very low incidence of pituitary carcinomas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".