Cell Intrinsic Deregulated ß-Catenin Signaling Promotes Expansion of Bone Marrow Derived Connective Tissue Type Mast Cells, Systemic Inflammation, and Colon Cancer
Bibliographic record
Abstract
Mast cells constitutively express ß-catenin and expand in solid tumors such as colon and skin cancer. However, the role of ß-catenin signaling in mast cells and the cause or effect of mast cell expansion and tumor growth has yet to be established. In earlier studies we used mast cell depletion and protease staining approaches, to provide evidence for a causative role of mast cells in small bowel polyposis, and related specific phenotypes and distributions of tumor infiltrating mast cells to stages of tumor growth. Here we report that, stabilization of ß-catenin expands mast cells to promote high incidence of colon polyposis and infrequent small bowel polyps and skin cancer. Expression of a dominant acting ß-catenin in mast cells (5CreCAT) stimulated maturation and expression of granule stored proteases. Both mucosal and connective tissue type mast cells accumulated in colonic small bowel polyps independent of gender, and mice developed chronic systemic inflammation with splenomegaly. Reconstitution of polyposis-prone mice with bone marrow from 5CreCAT mice resulted in focal expansion of connective tissue like mast cells, which are normally rare in benign polyps and characteristically expand during adenoma-to-carcinoma transition. Our findings highlight a hitherto unknown contribution of ß-catenin signaling in mast cells to their maturation and to increased risk of colon cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".