The VR23 anticancer proteasome inhibitor also exhibits anti-inflammatory activity through the downregulation of the IL-6-JAK-STAT pathway
Bibliographic record
Abstract
Abstract We previously demonstrated that the novel proteasome inhibitor, VR23, possesses anti-tumor activity without causing any ill-effects to animals. We have now shown that the compound VR23 also possesses potent anti-inflammatory activity. Our data from a monocyte cell model shows that VR23 down-regulates pro-inflammatory cytokines IL-1β, TNF-α, IL-6, and IL-8 at similar efficacy as dexamethasone, a steroid widely used for the control of inflammatory conditions. Studies from a rheumatoid arthritis (RA) cell model show that VR23 can not only down-regulate IL-6 but also inhibit the cell migration. Importantly, the down-regulation of pro-inflammatory cytokines by VR23 is more pronounced in the primary synovial cells from RA patients than those from healthy donors. Since VR23 down-regulates not only STAT3 phosphorylation but also the expression of its downstream pathways, our data is consistent with the notion that VR23 exhibits its anti-inflammatory properties through the downregulation of the IL-6-JAK-STAT signaling pathway. The latter down-regulation is at the level of transcription of several important members of the IL-6-JAK-STAT family. Finally, VR23 effectively reduces neutrophil migration, TNF-α secretion, and tissue inflammation in mice with an LPS-induced acute lung injury. Our data thus suggest that VR23 is an agent with significant potential of controlling cancer as well as acute and chronic inflammatory conditions.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".