Identification of Mutations in Distinct Regions of p85 Alpha in Urothelial Cancer
Bibliographic record
Abstract
Bladder cancers commonly show genetic aberrations in the phosphatidylinositol 3-kinase signaling pathway. Here we have screened for mutations in PIK3R1, which encodes p85α, one of the regulatory subunits of PI3K. Two hundred and sixty-four bladder tumours and 41 bladder tumour cell lines were screened and 18 mutations were detected. Thirteen mutations were in C-terminal domains and are predicted to interfere with the interaction between p85α and p110α. Five mutations were in the BH domain of PIK3R1. This region has been implicated in p110α-independent roles of p85α, such as binding to and altering the activities of PTEN, Rab4 and Rab5. Expression of these mutant BH-p85α forms in mouse embryonic fibroblasts with p85α knockout indicated that all forms, except the truncation mutants, could bind and stabilize p110α but did not increase AKT phosphorylation, suggesting that BH mutations function independently of p110α. In a panel of 44 bladder tumour cell lines, 80% had reduced PIK3R1 mRNA expression relative to normal urothelial cells. This, along with mutation of PIK3R1, may alter BH domain functioning. Our findings suggest that mutant forms of p85α may play an oncogenic role in bladder cancer, not only via loss of ability to regulate p110α but also via altered function of the BH domain.
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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 | 0.001 | 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 | 0.000 |
| 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".