SOX2 is required independently in both stem and differentiated cells for pituitary tumorigenesis in <i>p27</i> null mice
Bibliographic record
Abstract
Abstract Loss of P27 predominantly results in development of murine pituitary intermediate lobe (IL) tumours. We previously showed that the pleiotropic protein P27 can drive repression of the transcription factor Sox2 . This interaction plays an important role during development of p27 -/- IL tumours because loss of one copy of Sox2 diminishes tumorigenesis. Here, we have explored the cellular origin and mechanisms underlying melanotroph tumorigenesis in p27 -/- IL. We show that IL hyperplasia is associated with reduced cellular differentiation, while levels of SOX2 increase in both stem cells (SC) and melanotrophs. Using loss-of-function and lineage tracing approaches, we demonstrate that SOX2 is required cell-autonomously in p27 -/- melanotrophs and SCs for tumorigenesis. This is supported by studies deleting the Sox2 regulatory region 2 ( Srr2 ), which is the target of P27 repressive action. Single cell transcriptomic analysis reveals that activation of a SOX2-dependent MAPK pathway in SCs is important for p27 -/- tumorigenesis. Our data highlight different roles of SOX2 following loss of p27 , according to the cellular context. Furthermore, we uncover a tumor-promoting function for SCs, which is SOX2-dependant. In conclusion, our results imply that targeting SCs, in addition to tumour cells themselves, may represent an efficient anti-tumoral strategy in certain contexts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".