<i>O</i>-GlcNAcylation of epidermal growth factor receptor and glucose transporter 1 prevents their intrinsic down regulation in breast cancer cells
Bibliographic record
Abstract
The hexosamine biosynthetic pathway (HBP) is upregulated in many cancer cell types leading to upregulation of post-translational modification of proteins by β- N-acetylglucosamine ( O-GlcNAc), the product of HBP. However, our knowledge of the identity of proteins that undergo O-GlcNAcylation in cancer cells and consequently their roles is very limited. We investigated the O-GlcNAcylation of epidermal growth factor receptor (EGFR) and glucose transporter 1 (GLUT1) in T47D and MDA-MB-231 breast cancer cell models. We examined the effect of the loss of putative O-GlcNAcylation sites in EGFR and GLUT1 on cell-signaling pathways and their functional consequences on cell cycle progression and cell metabolism using fluorescence-activated cell sorting analysis and in vitro assays. EGFR and GLUT1 undergo O-GlcNAcylation in T47D and MDA-MB-231 breast cancer cells, which enhances their functions and prevents their intrinsic downregulation. This appears to involve an interplay between phosphorylation, O-GlcNAcylation, and ubiquitination in both proteins. Importantly, perturbing the putative O-GlcNAcylation sites in both proteins adversely affected their stability, functions, and metabolic status of breast cancer cells, including glucose uptake and lactate production. In conclusion, the reprogrammed metabolism in cancer cells extends beyond energy and macromolecule requirements and contributes to cell-signaling events that support the stability and function of cancer promoting proteins.
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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".