Data from Suppression of Extracellular Vesicle VEGF-C–mediated Lymphangiogenesis and Pancreatic Cancer Early Dissemination By a Selective HDAC1/2 Inhibitor
Bibliographic record
Abstract
Abstract Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer characterized by early dissemination and poor drug response. Therefore, it is an unmet medical need to develop new strategies for treatment. As aberrant activation of ERK due to KRAS activating mutation is a driving force for PDAC, a brake system that can terminate ERK signaling represents an ideal druggable target. Herein, we demonstrate that forced expression of dual specificity phosphatase-2 (DUSP2), a specific ERK phosphatase, abrogated tumor formation and loss of Dusp2 facilitated Kras-driven PDAC progression. We report that a selective HDAC1/2 inhibitor (B390) has multifaceted therapeutic potential in PDAC by restoring the expression and function of DUSP2. In vitro study showed that treatment with B390 inhibited growth and migration abilities of PDAC cells, decreased extracellular vesicle-associated VEGF-C expression, and suppressed lymphatic endothelial cell proliferation. In vivo, B390 not only suppressed tumor growth by increasing tumor cell death, it also inhibited lymphangiogenesis and lymphovascular invasion. Taken together, our data demonstrate that B390 was able to alleviate loss of DUSP2-mediated pathologic processes, which provides the proof-of-concept evidence to demonstrate the potential of using selective HDAC1/2 inhibitors in PDAC treatment and suggests reinstating DUSP2 expression may be a strategy to subside PDAC 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.005 | 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".