Patient-derived mutations within the N-terminal domains of p85α impact PTEN or Rab5 binding and regulation
Bibliographic record
Abstract
The p85α protein regulates flux through the PI3K/PTEN signaling pathway, and also controls receptor trafficking via regulation of Rab-family GTPases. In this report, we determined the impact of several cancer patient-derived p85α mutations located within the N-terminal domains of p85α previously shown to bind PTEN and Rab5, and regulate their respective functions. One p85α mutation, L30F, significantly reduced the steady state binding to PTEN, yet enhanced the stimulation of PTEN lipid phosphatase activity. Three other p85α mutations (E137K, K288Q, E297K) also altered the regulation of PTEN catalytic activity. In contrast, many p85α mutations reduced the binding to Rab5 (L30F, I69L, I82F, I177N, E217K), and several impacted the GAP activity of p85α towards Rab5 (E137K, I177N, E217K, E297K). We determined the crystal structure of several of these p85α BH domain mutants (E137K, E217K, R262T E297K) for bovine p85α BH and found that the mutations did not alter the overall domain structure. Thus, several p85α mutations found in human cancers may deregulate PTEN and/or Rab5 regulated pathways to contribute to oncogenesis. We also engineered several experimental mutations within the p85α BH domain and identified L191 and V263 as important for both binding and regulation of Rab5 activity.
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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 | 0.000 |
| 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".