Systems‐Based Analysis of the Pancreatic Cancer‐Specific Glycome Reveals ST6GAL1 as a Driver of Human and Murine Disease
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDA) is the 3 rd leading cause of cancer‐death in the U.S.. Glycans, such as CA‐19‐9, are biomarkers of PDA, but their roles in PDA biology are unclear. Herein, we utilized lectin microarray technology to compare the glycomes of human and murine PDA. We observed common aberrant patterns of glycosylation across both species, including increased levels of α‐2,3‐ and α‐2,6‐sialic acids, bisecting GlcNAc and poly‐LacNAc. Using single cell sequencing and histological data, we identified ST6GAL1, which underlies α‐2,6‐sialic acid, as a potential driver in human PDA. We created a novel mouse in which a pancreas‐specific genetic deletion of ST6GAL1 overlays the well‐established KC mouse model. Analysis of our model showed delayed cancer formation and a significant reduction in fibrosis. Our results highlight the utility of the KC model as an accurate reflection of human disease and identify ST6GAL1 as a key driver of pancreatic cancer initiation and progression.
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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) | 0.001 | 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".