Suppression of Cancer Progression by MGAT1 shRNA Knockdown
Bibliographic record
Abstract
Oncogenic signaling promotes tumor invasion and metastasis, in part, by increasing the expression of tri- and tetra- branched N-glycans. The branched N-glycans bind to galectins forming a multivalent lattice that enhances cell surface residency of growth factor receptors, and focal adhesion turnover. N-acetylglucosaminyltransferase I (MGAT1), the first branching enzyme in the pathway, is required for the addition of all subsequent branches. Here we have introduced MGAT1 shRNA into human HeLa cervical and PC-3-Yellow prostate tumor cells lines, generating cell lines with reduced transcript, enzyme activity and branched N-glycans at the cell surface. MGAT1 knockdown inhibited HeLa cell migration and invasion, but did not alter cell proliferation rates. Swainsonine, an inhibitor of α-mannosidase II immediately downstream of MGAT1, also inhibited cell invasion and was not additive with MGAT1 shRNA, consistent with a common mechanism of action. Focal adhesion and microfilament organization in MGAT1 knockdown cells also indicate a less motile phenotype. In vivo, MGAT1 knockdown in the PC-3-Yellow orthotopic prostate cancer xenograft model significantly decreased primary tumor growth and the incidence of lung metastases. Our results demonstrate that blocking MGAT1 is a potential target for anti-cancer therapy.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".