Complex <i>N</i> -Glycan and Metabolic Control in Tumor Cells
Bibliographic record
Abstract
Golgi beta1,6N-acetylglucosaminyltransferase V (Mgat5) produces beta1,6GlcNAc-branched complex N-glycans on cell surface glycoproteins that bind to galectins and promote surface residency of glycoproteins, including cytokine receptors. Carcinoma cells from polyomavirus middle T (PyMT) transgenic mice on a Mgat5-/- background have reduced surface levels of epidermal growth factor (EGF) and transforming growth factor-beta (TGF-beta) receptors and are less sensitive to acute stimulation by cytokines in vitro compared with PyMT Mgat5+/+ tumor cells but are nonetheless tumorigenic when injected into mice. Here, we report that PyMT Mgat5-/- cells are reduced in size, checkpoint impaired, and following serum withdrawal, fail to down-regulate glucose transport, protein synthesis, reactive oxygen species (ROS), and activation of Akt and extracellular signal-regulated kinase. To further characterize Mgat5+/+ and Mgat5-/- tumor cells, a screen of pharmacologically active compounds was done. Mgat5-/- tumor cells were comparatively hypersensitive to the ROS inducer 2,3-dimethoxy-1,4-naphthoquinone, hyposensitive to tyrosine kinase inhibitors, to Golgi disruption by brefeldin A, and to mitotic arrest by colcemid, hydroxyurea, and camptothecin. Finally, regulation of ROS, glucose uptake, and sensitivities to EGF and TGF-beta were rescued by Mgat5 expression or by hexosamine supplementation to complex N-glycan biosynthesis in Mgat5-/- cells. Our results suggest that complex N-glycans sensitize tumor cells to growth factors, and Mgat5 is required to balance responsiveness to growth and arrest cues downstream of metabolic flux.
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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".