mTOR/MYC Axis Regulates O-GlcNAc Transferase Expression and O-GlcNAcylation in Breast Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
UNLABELLED: Cancers exhibit altered metabolism characterized by increased glucose and glutamine uptake. The hexosamine biosynthetic pathway (HBP) uses glucose and glutamine, and directly contributes to O-linked-β-N-acetylglucosamine (O-GlcNAc) modifications on intracellular proteins. Multiple tumor types contain elevated total O-GlcNAcylation, in part, by increasing O-GlcNAc transferase (OGT) levels, the enzyme that catalyzes this modification. Although cancer cells require OGT for oncogenesis, it is not clear how tumor cells regulate OGT expression and O-GlcNAcylation. Here, it is shown that the PI3K-mTOR-MYC signaling pathway is required for elevation of OGT and O-GlcNAcylation in breast cancer cells. Treatment with PI3K and mTOR inhibitors reduced OGT protein expression and decreased levels of overall O-GlcNAcylation. In addition, both AKT and mTOR activation is sufficient to elevate OGT/O-GlcNAcylation. Downstream of mTOR, the oncogenic transcription factor c-MYC is required and sufficient for increased OGT protein expression in an RNA-independent manner and c-MYC regulation of OGT mechanistically requires the expression of c-MYC transcriptional target HSP90A. Finally, mammary tumor epithelial cells derived from MMTV-c-myc transgenic mice contain elevated OGT and O-GlcNAcylation and OGT inhibition in this model induces apoptosis. Thus, OGT and O-GlcNAcylation levels are elevated via activation of an mTOR/MYC cascade. IMPLICATIONS: Evidence indicates OGT as a therapeutic target in c-MYC-amplified cancers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it