High Frequency of <i>PIK3R1</i> and <i>PIK3R2</i> Mutations in Endometrial Cancer Elucidates a Novel Mechanism for Regulation of PTEN Protein Stability
Bibliographic record
Abstract
Abstract We demonstrate that phosphatidylinositol 3-kinase (PI3K) pathway aberrations occur in &gt;80% of endometrioid endometrial cancers, with coordinate mutations of multiple PI3K pathway members being more common than predicted by chance. PIK3R1 (p85α) mutations occur at a higher rate in endometrial cancer than in any other tumor lineage, and PIK3R2 (p85β), not previously demonstrated to be a cancer gene, is also frequently mutated. The dominant activation event in the PI3K pathway appears to be PTEN protein loss. However, in tumors with retained PTEN protein, PI3K pathway mutations phenocopy PTEN loss, resulting in pathway activation. KRAS mutations are common in endometrioid tumors activating independent events from PI3K pathway aberrations. Multiple PIK3R1 and PIK3R2 mutations demonstrate gain of function, including disruption of a novel mechanism of pathway regulation wherein p85α dimers bind and stabilize PTEN. Taken together, the PI3K pathway represents a critical driver of endometrial cancer pathogenesis and a novel therapeutic target. Significance: Our data indicate that the PI3K pathway is targeted in the vast majority of endometrioid endometrial cancers leading to PI3K pathway activation. Frequent oncogenic mutations in PIK3R1 and PIK3R2 provide evidence for their role in endometrial cancer pathophysiology with patient-specific mutations revealing a novel mechanism by which p85α regulates the PI3K pathway through stabilizing PTEN. Cancer Discovery; 1(2); 170–85. ©2011 AACR. Read the Commentary on this article by Herrero-Gonzalez and Di Cristofano, p. 106 This article is highlighted in the In This Issue feature, p. 91
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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".