Loss of ATG4B and ATG4A results in two-stage cell cycle defects in pancreatic ductal adenocarcinoma cells
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) exhibits elevated levels of autophagy, which promote tumor progression and treatment resistance. ATG4B is an autophagy-related cysteine protease under consideration as a potential therapeutic target, but it is largely unexplored in PDAC. Here, we investigated the clinical and functional relevance of ATG4B expression in PDAC. Using two PDAC patient cohorts, we found that low ATG4B mRNA or protein expression is associated with worse patient survival outcomes, poorly differentiated PDAC tumors and a lack of survival benefit from adjuvant chemotherapy. In PDAC cell lines, ATG4B knockout reduced proliferation, abolished processing of LC3B (also known as MAP1LC3B), and reduced GABARAP and GABARAPL1 levels, but increased ATG4A levels. ATG4B and ATG4A double knockout lines displayed a further reduction in proliferation, characterized by delays in G1-S phase transition and mitosis. Pro-LC3B accumulated aberrantly at the centrosome with a concomitant increase in centrosomal proteins PCM1 and CEP131, which was rescued by exogenous ATG4B. The two-stage cell cycle defects following ATG4B and ATG4A loss have important therapeutic implications for PDAC.
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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 | 0.001 |
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".