SH2 Domain-Containing Phosphatase 2 Is a Critical Regulator of Connective Tissue Mast Cell Survival and Homeostasis in Mice
Bibliographic record
Abstract
Mast cells require KIT receptor tyrosine kinase signaling for development and survival. Here, we report that SH2 domain-containing phosphatase 2 (SHP2) signaling downstream of KIT is essential for mast cell survival and homeostasis in mice. Using a novel mouse model with shp2 deletion within mature mast cells (MC-shp2 knockout [KO]), we find that SHP2 is required for the homeostasis of connective tissue mast cells. Consistently with the loss of skin mast cells, MC-shp2 KO mice fail to mount a passive late-phase cutaneous anaphylaxis response. To better define the phenotype of shp2-deficient mast cells, we used an inducible shp2 knockout approach in bone marrow-derived mast cells (BMMCs) or cultured peritoneal mast cells and found that SHP2 promotes mast cell survival. We show that SHP2 promotes KIT signaling to extracellular signal-regulated kinase (ERK) mitogen-activated protein kinase and downregulation of the proapoptotic protein Bim in BMMCs. Also, SHP2-deficient BMMCs failed to repopulate mast cells in mast cell-deficient mice. Silencing of Bim partially rescued survival defects in shp2-deficient BMMCs, consistent with the importance of a KIT → SHP2 → Ras/ERK pathway in suppressing Bim and promoting mast cell survival. Thus, SHP2 is a key node in a mast cell survival pathway and a new potential therapeutic target in diseases involving mast cells.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".