Dysregulation of phosphatidylinositol 3‐kinase and downstream effectors in human breast cancer
Bibliographic record
Abstract
Phosphatidylinositol 3-kinase (PI3-K) is a growth factor-activated transforming lipid (and protein) kinase, involved in cell motility and invasion, that has multiple effectors. Relatively little is known about its expression and enzymatic activity in human breast cancer. Since growth factor receptors are amplified in breast cancer, and the tumor suppressor PTEN may be mutated in human breast cancer, it was hypothesized that PI3-K and its downstream effectors would be activated in this disease. In 11 resected tumors analyzed for expression of this kinase, a mean 3-fold increase in protein expression was observed over the corresponding adjacent control tissue. Using an in vitro lipid kinase assay of the immunoprecipitated PI3-K protein, a greater than 2-fold increase in activation was observed. These changes were observed in the absence of an activation of either protein kinase B (PKB, akt1) or p70 S6 kinase (p70 S6K). However, p21-activated kinase (Pak), p38 mitogen-activated protein kinase (p38 MAPK) and mitogen-activated protein kinase-activated protein kinase 2 (MAPKAPK 2) were all overexpressed and demonstrated increased enzyme activity. It may be concluded that aberrant mitogenic signaling in human breast cancer in vivo involves Pak, p38 MAPK and MAPKAPK2 downstream of PI3-K, but neither of PKB or p70 S6K. It is proposed that this pathway may serve as a useful targeting nexus for investigation of small molecule inhibitors in human breast cancer.
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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 | 0.001 |
| 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".