Investigation of the Effects of Inhibiting N-glycosylation in Cancer
Bibliographic record
Abstract
Glycosylation, the addition of sugar moieties to nascent proteins, is one of the most common posttranslational modifications. Glycosylation regulates protein structure, function and localization. Most cell surface proteins and secreted proteins are glycosylated by the addition of Asparagine(N)-linked glycans (N-glycans). Aberrant N-glycosylation is a well-accepted feature of malignancy and is a potential prognostic marker for some types of cancer. For example, increased expression of complex N-glycans has been detected in cancers of breast, colon and has been correlated with reduced survival of the patients. Therefore, understanding the role of N-glycosylation in malignancy could be beneficial for developing novel therapeutic and prognostic strategies. \n\tTo examine the role of N-glycosylation in malignancy, we applied chemical biology and genetic approaches. First, we conducted a high throughput screen to identify compounds that could block L-PHA-induced cell death. Our screen identified the cardiac glycoside Na+/K+-ATPase inhibitors as novel inhibitors of N-glycosylation. Further analysis of N-glycans consistently confirmed that inhibition of Na+/K+-ATPase impairs the N-glycosylation, as well as migration and invasion. Interestingly, other studies have shown antimetastatic effects of cardiac glycosides in patients. Thus, our high throughput screen identified Na+/K+-ATPase inhibition as a novel strategy to target the N-glycosylation pathway. \n\tIn addition, we used a genetic approach to investigate the role of N-acetylglucosaminyltransferase I (GlcNAc-TI/Mgat1) in malignancy. Knockdown of GlcNAc-TI decreased the cell-surface expression of complex N-glycans. By confocal microscopy, knockdown of GlcNAc-TI decreased cell surface expression of β1 integrins and increased their localization around the nucleus. Moreover, GlcNAc-TI knockdown decreased the migration and invasion of malignant cells. Next, we investigated the effect of GlcNAc-TI in an orthotopic xenograft mouse model of metastasis. GlcNAc-TI knockdown significantly decreased the lung colony formation of the highly metastatic PC3N7 human prostate cancer cell line in mice. Our results suggest an important role for GlcNAc-TI in tumor metastasis. Interestingly, breast cancer patients with lower expression levels of Mgat1 had lower risk of disease relapse after therapy. Thus, GlcNAc-TI plays an important role in cancer progression and metastasis and GlcNAc-TI inhibitors could have therapeutic benefits for cancer patients. Moreover, expression levels of GlcNAc-TI could be used as a prognostic marker in patients with cancer.
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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".