Ingredients, Anti-Liver Cancer Effects and the Possible Mechanism of DWYG Formula Based on Network Prediction.
Onco Targets Ther
; 13: 4213-4227, 2020.
Article
em En
| MEDLINE
| ID: mdl-32523357
BACKGROUND: Hepatitis virus infection plays a critical role in liver cancer initiation and development; so the purpose of this study was to investigate the anti-liver cancer effects of DiWuYangGan (DWYG) which was effective for hepatitis. METHODS: Network predictions were performed. Next, several tests, including HPLC, Caco-2 absorption models, MMT, protein chip, Western blotting and H22-tumor-bearing mouse, were carried out to investigate the effects and possible mechanism of DWYG. RESULTS: Network results showed DWYG might be involved in some processes such as STAT cascade. Some target genes may correspondingly participate in these procedures, such as IL-6, CASP3, AKT1, PPAR, and TP53. Diseases associated with DWYG formula may be liver cancer and hepatitis. Potential active compounds might be CUR and ISO. Chemical analysis results showed that ingredients in the formula, including DEO, SCHB, SOLA, SOLB, SCHA, LIQ, ISO, POT, and CHL, could be determined, indicating that DWYG samples for the following experiments were controllable and consistent. Caco-2 absorption of ingredients in DWYG, including DEO, SCHB, SOLA, SOLB, and LIQ, worked very well. In vitro experiment results showed that DWYG could inhibit the growth of cell lines and its effective ingredients might be SCHB, SOLB, SINA, SINB, SOLB, CUR, DEM, BIS, and GER. Further protein results showed that DWYG could upregulate the expressions of some proteins, including ERK1/2, AKT Ser473, BAD Ser112, PRAS40, Thr246, P38, Gsk-3ß, and Ser9. In vivo experiment results showed that DWYG could shrink tumor size, recover ALT and AST, and decrease IL-6 levels. Their possible mechanism might be through the JAK/STAT3 pathway. CONCLUSION: Besides the known pharmacological function of anti-hepatitis, DWYG extract expressed anti-liver cancer effects and the results were consistent partly with network predictions.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Onco Targets Ther
Ano de publicação:
2020
Tipo de documento:
Article