<i>HMGA1</i>-pseudogene expression is induced in human pituitary tumors
Bibliographic record
Abstract
Numerous studies have established that High Mobility Group A (HMGA) proteins play a pivotal role on the onset of human pituitary tumors. They are overexpressed in pituitary tumors, and, consistently, transgenic mice overexpressing either the Hmga1 or the Hmga2 gene develop pituitary tumors. In contrast with HMGA2, HMGA1 overexpression is not related to any rearrangement or amplification of the HMGA1 locus in these tumors. We have recently identified 2 HMGA1 pseudogenes, HMGA1P6 and HMGA1P7, acting as competitive endogenous RNA decoys for HMGA1 and other cancer related genes. Here, we show that HMGA1 pseudogene expression significantly correlates with HMGA1 mRNA levels in growth hormone and nonfunctioning pituitary adenomas likely inhibiting the repression of HMGA1 through microRNAs action. According to our functional studies, these HMGA1 pseudogenes enhance the proliferation and migration of the mouse pituitary tumor cell line, at least in part, through their upregulation. Our results point out that the overexpression of HMGA1P6 and HMGA1P7 could contribute to increase HMGA1 levels in human pituitary tumors, and then to pituitary tumorigenesis.
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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 | 0.001 |
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".