A Pituitary-Derived MEG3 Isoform Functions as a Growth Suppressor in Tumor Cells
Bibliographic record
Abstract
Human pituitary adenomas are the most common intracranial neoplasm. Typically monoclonal in origin, a somatic mutation is a prerequisite event in tumor development. To identify underlying pathogenetic mechanisms in tumor formation, we compared the difference in gene expression between normal human pituitary tissue and clinically nonfunctioning pituitary adenomas by cDNA-representational difference analysis. We cloned a cDNA, the expression of which was absent in these tumors, that represents a novel transcript from the previously described MEG3, a maternal imprinting gene with unknown function. It was expressed in normal human gonadotrophs, from which clinically nonfunctioning pituitary adenomas are derived. Additional investigation by Northern blot and RT-PCR demonstrated that this gene was also not expressed in functioning pituitary tumors as well as many human cancer cell lines. Moreover, ectopic expression of this gene inhibits growth in human cancer cells including HeLa, MCF-7, and H4. Genomic analysis revealed that MEG3 is located on chromosome 14q32.3, a site that has been predicted to contain a tumor suppressor gene involved in the pathogenesis of meningiomas. Taken together, our data suggest that MEG3 may represent a novel growth suppressor, which may play an important role in the development of human pituitary adenomas.
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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".