Epidermal Growth Factor-induced Phosphatidylinositol 3-Kinase Activation and DNA Synthesis
Bibliographic record
Abstract
In previous work we showed that the phosphatidylinositol 3-kinase (PI3-kinase), not the mitogen-activated protein kinase, pathway is necessary and sufficient to account for insulin- and epidermal growth factor (EGF)-induced DNA synthesis in rat hepatocytes. Here, using a dominant-negative p85, we confirmed the key role of EGF-induced PI3-kinase activation and sought to identify the mechanism by which this is effected. Our results show that EGF activates PI3-kinase with a time course similar to that of the association of p85 with three principal phosphotyrosine proteins (i. e. PY180, PY105, and PY52). We demonstrated that each formed a distinct p85-associated complex. PY180 and PY52 each constituted about 10% of EGF-activated PI3-kinase, whereas PY105 was responsible for 80%. PY105 associated with Grb2 and SHP-2, and although it behaved like Gab1, none of the latter was detected in rat liver. We therefore cloned a cDNA from rat liver, which was found to be 95% homologous to the mouse Grb2-associated binder 2 (Gab2) cDNA sequence. Using a specific Gab2 antibody, we demonstrated its expression in and association with p85, SHP-2, and Grb2 upon EGF treatment of rat hepatocytes. Gab2 accounted for most if not all of the PY105 species, since immunoprecipitation of Gab2 with specific antibodies demonstrated parallel immunodepletion of Gab2 and PY105 from the residual supernatants. We also found that the PI3-kinase activity associated with Gab2 was totally abolished by dominant negative p85. Thus, Gab2 appears to be the principal EGF-induced PY protein recruiting and activating PI3-kinase and mitogenesis.
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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) | 0.002 | 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".