<scp>ITGAV</scp> and <scp>SMAD4</scp> influence the progression and clinical outcome of pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive and lethal malignancy with limited treatment options, a fact that underscores the urgent need for more effective therapies to improve patient outcomes. Preclinical studies have shown promise for αV integrin-targeted therapies; however, clinical trials have been disappointing, highlighting the need for further research. In this study, we demonstrate that integrin subunit alpha V (ITGAV) signals through both mothers against decapentaplegic homolog 4 (SMAD4)-dependent or SMAD4-independent pathways, depending on the genetic context. In SMAD4-positive PDAC cells, ITGAV contributes to the transforming growth factor-beta (TGF-β) signaling pathway to regulate proliferation, migration, and invasion. Conversely, in SMAD4-negative PDAC cells, ITGAV influences only proliferation and migration via activation of the mitogen-activated protein kinase (MAPK)/extracellular signal-related kinase (ERK) pathway. High levels of ITGAV are also associated with poor prognostic outcomes in SMAD4 wild-type patients but are not prognostic in SMAD4 mutant patients. Thus, ITGAV contributes to different patterns of PDAC progression. These findings suggest that stratifying PDAC patients based on both SMAD4 status and ITGAV expression could inform more effective integrin-targeted treatment strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".