Sweet Tooth of a Glucose Transporter: GLUT1 C‐terminal Phosphorylation and O‐GlcNacylation effect in Breast Cancer Cell Lines
Bibliographic record
Abstract
Cancer cells have altered metabolism that is largely dependent on aerobic glycolysis. In cancer cells elevated levels of glucose transporters (GLUT) facilitate the high glucose requirements of cancer cells. GLUT proteins allow for the passive transport across the plasma membrane down its concentration gradient. In various cancer tissues as well as human breast cancer cell lines elevated expression of GLUT1 has been reported. Another hallmark of cancer cells is hyper O‐GlcNacylation, which is a post translational modification (PTM) which adds a single N‐acetylglucosamine to either a serine or threonine residue. Only one O‐GlcNacylation site has been identified for GLUT1 (S465). The O‐GlcNacylation site of GLUT1 is in proximity of identified phosphorylation sites suggesting a possibility of interplay among the PTM sites of the C‐terminus. The aim our study is to discern if O‐GlcNacylation of GLUT1(S465) is affected by phosphorylation of neighboring residues and to determine if PTM of these sites regulate the function of GLUT1 and cancer cell metabolism. The single O‐GlcNacylation site in GLUT1 (S465) and neighboring serine/threonine residues were mutated and overexpressed in breast cancer cell lines. We investigated the molecular pathways involve in breast cancer cell metabolism and the effect of overexpression of GLUT1 variants. The GLUT1 variants showed altered levels of O‐GlcNac transferase, O‐GlcNacase and total O‐GlcNacylation of proteins in the cell. Breast cancer cell lines transfected with GLUT1 or it variants showed variable levels of glucose uptake. The results show that PTM of the c‐terminus of GLUT1 generally affects O‐GlcNacylation levels and metabolism of breast cancer cell lines.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".