grb2 heterozygosity rescues embryonic lethality but not tumorigenesis in <i>pten</i> <sup>+/-</sup> mice
Bibliographic record
Abstract
PTEN is a tumor suppressor gene implicated in both sporadic cancers and inherited tumor-prone syndromes. Here we show that pten+/- mice display a partially penetrant embryonic lethality. This lethality is associated with defects in both neural and placental development. Notably, this lethality is completely rescued by grb2 haploinsufficiency. In contrast, grb2 heterozygosity did not alter tumorigenesis in either pten+/- or T cell-specific pten-/- mice. grb2-/hypomorph murine embryonic fibroblasts (MEFs) show decreased activation of both PKB and Erk upon stimulation with epidermal growth factor, whereas grb2-/hypomorph; pten+/- MEFs activate PKB but not Erk normally. Similarly, grb2-/hypomorph fibroblasts die in low serum, and this phenotype is rescued by pten haploinsufficiency. Activation of both PKB and Erk as well as survival in low serum-containing media are all rescued by reexpression of Grb2 containing mutations within the N-terminal Src homology 3 (SH3) domain, but not by C-terminal SH3 domain mutants. The N-terminal SH3 domain mutants fail to bind to Sos, whereas the C-terminal SH3 domain mutants fail to bind to Gab1, suggesting that Erk and PKB activation in fibroblasts in response to epidermal growth factor depends on Gab1 or other C-terminal SH3 domain-interacting proteins, but not on Sos. Thus, PTEN/phosphatidylinositol 3' kinase signaling requires Grb2 during both embryonic development and fibroblast survival, but Grb2 heterozygosity does not effect tumorigenesis in pten-deficient mice. In fibroblasts, survival signals emanating from the epidermal growth factor receptor appear to be PKB-dependent, and this activation depends on the C-terminal SH3 domain of Grb2, likely through the interaction of Grb2 with Gab1.
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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 | 0.000 | 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".