Rhus coriaria suppresses angiogenesis, metastasis and tumor growth of breast cancer through inhibition of STAT3, NFκB and nitric oxide pathways
Bibliographic record
Abstract
Recently, we reported that Rhus coriaria exhibits anticancer activities by promoting cell cycle arrest and autophagic cell death of the metastatic triple negative MDA-MB-231 breast cancer cells. Here, we investigated the effect of Rhus coriaria on the migration, invasion, metastasis and tumor growth of TNBC cells. Our current study revealed that non-cytotoxic concentrations of Rhus coriaria significantly inhibited migration and invasion, blocked adhesion to fibronectin and downregulated MMP-9 and prostaglandin E2 (PgE2). Not only did Rhus coriaria decrease their adhesion to HUVECs and to lung microvascular endothelial (HMVEC-L) cells, but it also inhibited the transendothelial migration of MDA-MB-231 cells through TNF-α-activated HUVECs. Furthermore, we found that Rhus coriaria inhibited angiogenesis, reduced VEGF production in both MDA-MB-231 and HUVECs and downregulated the inflammatory cytokines TNF-α, IL-6 and IL-8. The underlying mechanism for Rhus coriaria effects appears to be through inhibiting NFκB, STAT3 and nitric oxide (NO) pathways. Most importantly, by using chick embryo tumor growth assay, we showed that Rhus coriaria suppressed tumor growth and metastasis in vivo. The results described in the present study identify Rhus coriaria as a promising chemopreventive and therapeutic candidate that modulate triple negative breast cancer growth and metastasis.
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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) | 0.001 | 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".