Unique mechanisms of growth regulation and tumor suppression upon Apc inactivation in the pancreas
Bibliographic record
Abstract
beta-catenin signaling is heavily involved in organogenesis. Here, we investigated how pancreas differentiation, growth and homeostasis are affected following inactivation of an endogenous inhibitor of beta-catenin, adenomatous polyposis coli (Apc). In adult mice, Apc-deficient pancreata were enlarged, solely as a result of hyperplasia of acinar cells, which accumulated beta-catenin, with the sparing of islets. Expression of a target of beta-catenin, the proto-oncogene c-myc (Myc), was increased in acinar cells lacking Apc, suggesting that c-myc expression is essential for hyperplasia. In support of this hypothesis, we found that conditional inactivation of c-myc in pancreata lacking Apc completely reversed the acinar hyperplasia. Apc loss in organs such as the liver, colon and kidney, as well as experimental misexpression of c-myc in pancreatic acinar cells, led to tumor formation with high penetrance. Surprisingly, pancreas tumors failed to develop following conditional pancreas Apc inactivation. In Apc-deficient acini of aged mice, our studies revealed a cessation of their exaggerated proliferation and a reduced expression of c-myc, in spite of the persistent accumulation of beta-catenin. In conclusion, our work shows that beta-catenin modulation of c-myc is an essential regulator of acinar growth control, and unveils an unprecedented example of Apc requirement in the pancreas that is both temporally restricted and cell-specific. This provides new insights into the mechanisms of tumor pathogenesis and tumor suppression in the pancreas.
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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 | 0.001 |
| 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".