The polypeptide GALNT6 Displays Redundant Functions upon Suppression of its Closest Homolog GALNT3 in Mediating Aberrant O-Glycosylation, Associated with Ovarian Cancer Progression
Bibliographic record
Abstract
Epithelial ovarian cancer (EOC) represents the most lethal gynecologic malignancy; a better understanding of the molecular mechanisms associated with EOC etiology could substantially improve EOC management. Aberrant O-glycosylation in cancer is attributed to alteration of N-acetylgalactosaminyltransferases (GalNAc-Ts). Reports suggest a genetic and functional redundancy between GalNAc-Ts, and our previous data are indicative of an induction of GALNT6 expression upon GALNT3 suppression in EOC cells. We performed single GALNT3 and double GALNT3/T6 suppression in EOC cells, using a combination of the CRISPR-Cas9 system and shRNA-mediated gene silencing. The effect of single GALNT3 and double GALNT3/T6 inhibition was monitored both in vitro (on EOC cells roliferation, migration, and invasion) and in vivo (on tumor formation and survival of experimental animals). We confirmed that GALNT3 gene ablation leads to strong and rather compensatory GALNT6 upregulation in EOC cells. Moreover, double GALNT3/T6 suppression was significantly associated with stronger inhibitory effects on EOC cell proliferation, migration, and invasion, and accordingly displayed a significant increase in animal survival rates compared with GALNT3-ablated and control (Ctrl) EOC cells. Our data suggest a possible functional redundancy of GalNAc-Ts (GALNT3 and T6) in EOC, with the perspective of using both these enzymes as novel EOC biomarkers and/or therapeutic targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".