NG2 targets tumorigenic Rb inactivation in Pit1-lineage pituitary cells
Bibliographic record
Abstract
The proteoglycan neuron-glial antigen 2 (NG2) is expressed by oligodendrocyte progenitors, pericytes, and some cancerous cells where it is implicated in tumor development. We examined mice with NG2-driven pRb inactivation. Unexpectedly, NG2-Cre:pRb(flox/flox) mice developed pituitary tumors with high penetrance. Adenohypophysial neoplasms developed initially as multifocal lesions; by 1 year, large tumors showed brain invasion. Immunohistochemistry identified these as Pit1-lineage neoplasms, with variable immunoreactivity for growth hormone, prolactin, thyrotropin, and α-subunit of glycoprotein hormones. Other than modest hyperprolactinemia, circulating hormone levels were not elevated. To determine the role of NG2 in the pituitary, we investigated NG2 expression. Immunoreactivity was identified in anterior and posterior lobes but not in the intermediate lobe of the mouse pituitary; in the adenohypophysis, folliculostellate cells had the strongest NG2 immunoreactivity but showed no proliferation in response to Rb inactivation. Pit1-positive adenohypophysial cells were positive for NG2, but corticotroph and gonadotroph cells were negative. RT-PCR revealed NG2 expression in normal human pituitary and human pituitary tumors; immunohistochemistry localized NG2 in nontumorous human adenohypophysis with strongest positivity in folliculostellate cells, and in tumors of all types except corticotrophs. Functional studies in GH4 mammosomatotrophs showed that NG2 increases prolactin (PRL), reduces growth hormone (GH) expression, and enhances cell adhesion without influencing proliferation. In conclusion, NG2-driven pRb inactivation results in pituitary tumors that mimic endocrinologically inactive Pit1-lineage human pituitary tumors. This model identifies a role for NG2 in pituitary cell-type-specific functions and unmasks a protective role from Rb inactivation in folliculostellate cells; it can be used for further research, including preclinical testing of novel 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) | 0.001 | 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".