The cellular regulators PTEN and BMI1 help mediate NEUROGENIN-3–induced cell cycle arrest
Bibliographic record
Abstract
Neurogenin-3 (NEUROG3) is a helix-loop-helix (HLH) transcription factor involved in the production of endocrine cells in the intestine and pancreas of humans and mice. However, the human NEUROG3 loss-of-function phenotype differs subtly from that in mice, but the reason for this difference remains poorly understood. Because NEUROG3 expression precedes exit of the cell cycle and the expression of endocrine cell markers during differentiation, we investigated the effect of lentivirus-mediated overexpression of the human NEUROG3 gene on the cell cycle of BON4 cells and various human nonendocrine cell lines. NEUROG3 overexpression induced a reversible cell cycle exit, whereas expression of a neuronal lineage homolog, NEUROG1 , had no such effect. In endocrine lineage cells, the cellular quiescence induced by short-term NEUROG3 expression required cyclin-dependent kinase inhibitor 1A (CDKN1A)/p 21 CIP1 expression. Expression of endocrine differentiation markers required sustained NEUROG3 expression in the quiescent, but not in the senescent, state. Inhibition of the phosphatase and tensin homolog (PTEN) pathway reversed quiescence by inducing cyclin-dependent kinase 2 (CDK2) and reducing p21 CIP1 and NEUROG3 protein levels in BON4 cells and human enteroids. We discovered that NEUROG3 expression stimulates expression of CDKN2a/p 16 INK4a and BMI1 proto-oncogene polycomb ring finger ( BMI1 ), with the latter limiting expression of the former, delaying the onset of CDKN2a/p 16 INK4a -driven cellular senescence. Furthermore, NEUROG3 bound to the promoters of both CDKN1a/p21 CIP1 and BMI1 genes, and BMI1 attenuated NEUROG3 binding to the CDKN1a / p21CIP1 promoter. Our findings reveal how human NEUROG3 integrates inputs from multiple signaling pathways and thereby mediates cell cycle exit at the onset of differentiation.
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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 | 0.001 |
| 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".