miRNA-Dependent Regulation of AKT1 Phosphorylation
Bibliographic record
Abstract
The phosphoinositide-3-kinase (PI3K)/AKT pathway regulates cell survival and is over-activated in most human cancers, including ovarian cancer. Following growth factor stimulation, AKT1 is activated by phosphorylation at T308 and S473. Disruption of the AKT1 signaling pathway is sufficient to inhibit the epithelial-mesenchymal transition in epithelial ovarian cancer (EOC) cells. In metastatic disease, adherent EOC cells transition to a dormant spheroid state, characterized previously by low S473 phosphorylation in AKT1. We confirmed this finding and observed that T308 phosphorylation was yet further reduced in EOC spheroids and that the transition from adherent to spheroid growth is accompanied by significantly increased levels of let-7 miRNAs. We then used mechanistic studies to investigate the impact of let-7 miRNAs on AKT1 phosphorylation status and activity in cells. In growth factor-stimulated HEK 293T cells supplemented with let-7a, we found increased phosphorylation of AKT1 at T308, decreased phosphorylation at S473, and enhanced downstream AKT1 substrate GSK-3β phosphorylation. Let-7b and let-7g also deregulated AKT signaling by rendering AKT1 insensitive to growth factor simulation. We uncovered let-7a-dependent deregulation of PI3K pathway components, including PI3KC2A, PDK1, and RICTOR, that govern AKT1 phosphorylation and activity. Together, our data show a new role for miRNAs in regulating AKT signaling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".