Distinct epithelial-to-mesenchymal transitions induced by <i>PIK3CA</i>H1047R and <i>PIK3CB</i>
Bibliographic record
Abstract
ABSTRACT The most common PIK3CA mutation, producing the H1047R mutant of p110α, arises in myriad malignancies and is typically observed in low-grade breast tumours. In contrast, amplification is observed for wild-type PIK3CB, encoding p110β, and occurs at low frequency but in aggressive, high-grade metastatic tumours. We hypothesized that mutant p110αH1047R and wild-type p110β give rise to distinct transformed phenotypes. We show that p110αH1047R and wild-type p110β, but not wild-type p110α, transform MCF-10A cells and constitutively stimulate phosphoinositide 3-kinase (PI3K)-AKT pathway signalling. However, their resultant morphological transformed phenotypes are distinct. p110αH1047R induced an epithelial-to-mesenchymal transition (EMT) commensurate with SNAIL (also known as SNAI1) induction and loss of E-cadherin. Upon p110β expression, however, E-cadherin expression was maintained despite cells readily delaminating from epithelial sheets. Distinct from the prominent filopodia in p110αH1047R-expressing cells, p110β induced formation of lamellipodia, and these cells migrated with significantly greater velocity and decreased directionality. p110β-induced phenotypic alterations were accompanied by hyperactivation of RAC1; the dependency of transformation of p110β-binding to Rac1 revealed using a Rac1-binding mutant of p110β. Thus, PIK3CB amplification induces a transformed phenotype that is dependent upon a p110β-Rac1 signalling loop and is distinct from the transformed phenotype induced by p110αH1047R.
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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) | 0.001 | 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".