RETRACTION: Revealing the effects of the herbal pair of euphorbia kansui and glycyrrhiza on hepatocellular carcinoma ascites with integrating network target analysis and experimental validation (Int J Biol Sci. (2016) 12, 5, (594-606), 10.7150/ijbs.14151);Revealing the effects of the herbal pair of Euphorbia kansui and Glycyrrhiza on hepatocellular carcinoma ascites with integrating network target analysis and experimental validation

International Journal of Biological Sciences

Volumn 12, Issue 5, 2016, Pages 594-606

  Zhang, Yanqiong ^a   Lin, Ya ^a,b   Zhao, Haiyu ^a   Guo, Qiuyan ^a   Yan, Chen ^a   Lin, Na ^a  

^a INSTITUTE OF CHINESE MATERIA MEDICA   (China)

^b FUJIAN UNIVERSITY OF TRADITIONAL CHINESE MEDICINE   (China)

Author keywords

Euphorbia kansui; Glycyrrhiza; Hepatocellular carcinoma ascites; Herb herb combination; Network pharmacology

Indexed keywords

HERBACEOUS AGENT;

ANIMAL; BAGG ALBINO MOUSE; CHEMISTRY; CHINESE MEDICINE; DRUG EFFECTS; EUPHORBIA; GLYCYRRHIZA; LIVER CELL CARCINOMA; MALE; METABOLISM; MOUSE; SIGNAL TRANSDUCTION; TUMOR CELL LINE;

ANIMALS; CARCINOMA, HEPATOCELLULAR; CELL LINE, TUMOR; DRUGS, CHINESE HERBAL; EUPHORBIA; GLYCYRRHIZA; MALE; MEDICINE, CHINESE TRADITIONAL; MICE; MICE, INBRED BALB C; SIGNAL TRANSDUCTION;

EID: 84964755807     PISSN: 14492288     EISSN: None     Source Type: Journal    
DOI: 10.7150/ijbs.28890     Document Type: Erratum

References (50)

1. Forner A, Llovet JM, Bruix J. Hepatocellular carcinoma. Lancet. 2012; 379: 1245-1255.
2. Sherman M. Recurrence of hepatocellular carcinoma. N Engl J Med. 2008; 359: 2045-2047
3. Cavazzoni E, Bugiantella W, Graziosi L, et al. Malignant ascites: pathophysiology and treatment. Int J Clin Oncol. 2013; 18: 1-9.
4. Chung M, Kozuch P. Treatment of malignant ascites. Curr Treat Options Oncol. 2008; 9: 215-233.
5. Tamsma J. The pathogenesis of malignant ascites. Cancer Treat Res. 2007; 134: 109-118.
6. Yu FR, Lian XZ, Guo HY, et al. Isolation and characterization of methyl esters and derivatives from Euphorbia kansui (Euphorbiaceae) and their inhibitory effects on the human SGC-7901 cells. J Pharm Pharm Sci. 2005; 8: 528-535.
7. Nie S, Li Z, Liang A, et al. Effects of processing on specific toxicity and pharmacodynamics of radix Kansui, radix Achyranthis bidentatae and semen Armeniacae amarum. Zhongguo Zhong Yao Za Zhi. 1996; 21: 153-6, 190.
8. Yan X, Zhang L, Guo J, et al. Processing of kansui roots stir-baked with vinegar reduces kansui-induced hepatocyte cytotoxicity by decreasing the contents of toxic terpenoids and regulating the cell apoptosis pathway. Molecules. 2014; 19: 7237-54.
9. Hou YC, Lin SP, Chao PD. Liquorice reduced cyclosporine bioavailability by activating P-glycoprotein and CYP 3A. Food Chem. 2012; 135: 2307-12.
10. Wang X, Zhang H, Chen L, et al. Liquorice, a unique “guide drug” of traditional Chinese medicine: a review of its role in drug interactions. J Ethnopharmacol. 2013; 150: 781-90.
11. Sheela ML, Ramakrishna MK, Salimath BP. Angiogenic and proliferative effects of the cytokine VEGF in Ehrlich ascites tumor cells is inhibited by Glycyrrhiza glabra. Int Immunopharmacol. 2006; 6: 494-8.
12. Song WQ. Utilization pattern of Gansui-Banxia-Tang in clinics. J Tradit Chin Med. 1993; 34: 492 In Chinese.
13. Zhang Y, Guo X, Wang D, et al. A systems biology-based investigation into the therapeutic effects of Gansui Banxia Tang on reversing the imbalanced network of hepatocellular carcinoma. Sci Rep. 2014; 4: 4154.
14. Li M, Qiao C, Qin L, et al. Application of traditional Chinese medicine injection in treatment of primary liver cancer: a review. J Tradit Chin Med. 2012; 32: 299-307.
15. van der Greef J, van Wietmarschen H, Schroën J, et al. Systems biology-based diagnostic principles as pillars of the bridge between Chinese and Western medicine. Planta Med. 2010; 76: 2036-47.
16. Chen CY-C. TCM Database@Taiwan: The World’s Largest Traditional Chinese Medicine Database for Drug Screening In Silico. PLoS ONE 2011; 6: e15939.
17. Chen JY, Mamidipalli S, Huan T. HAPPI: an online database of comprehensive human annotated and predicted protein interactions. BMC Genomics. 2009; 10 Suppl 1: S16.
18. Matthews L, Gopinath G, Gillespie M, et al. Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res. 2009; 37: D619–D622.
19. Brown KR, Jurisica I. Online predicted human interaction database. Bioinformatics. 2005; 21: 2076-2082.
20. Aranda B, Achuthan P, Alam-Faruque Y, et al. The IntAct molecular interaction database in 2010. Nucleic Acids Res. 2010; 38: D525–D531.
21. Keshava Prasad TS, Goel R, et al. Human Protein Reference Database – 2009 update. Nucleic Acids Res 2009; 37: D767–D772.
22. Ceol A, Chatr Aryamontri A, Licata L, et al. MINT, the molecular interaction database: 2009 update. Nucleic Acids Res. 2010; 38: D532-D539.
23. Lehne B, Schlitt T. Protein-protein interaction databases: keeping up with growing interactomes. Hum Genomics. 2009; 3: 291-297.
24. Beuming T, Skrabanek L, Niv MY, et al. PDZBase: a protein-protein interaction database for PDZ-domains. Bioinformatics. 2005; 21: 827-828.
25. Zhang Y, Wang D, Tan S, et al. A systems biology-based investigation into the pharmacological mechanisms of Wu Tou Tang acting on rheumatoid arthritis by integrating network analysis. Evidence-Based Complementary and Alternative Medicine. 2013; 2013: 548498.
26. Li S, Zhang ZQ, Wu LJ, et al. Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network. IET Syst Biol. 2007; 1: 51-60.
27. Zsoldos Z, Reid D, Simon A, Sadjad BS, Johnson AP. eHiTS: an innovative approach to the docking and scoring function problems. Curr Protein Pept Sci. 2006; 7: 421-435.
28. Cushing TD, Hao X, Shin Y, Andrews K, et al. Discovery and in vivo evaluation of (S)-N-(1-(7-fluoro-2-(pyridin-2-yl)quinolin-3-yl)ethyl)-9H-purin-6-amine (AMG319) and related PI3Kδ inhibitors for inflammation and autoimmune disease. J Med Chem. 2015; 58: 480-511.
29. Warne T, Moukhametzianov R, Baker JG, et al. The structural basis for agonist and partial agonist action on a β(1)-adrenergic receptor. Nature. 2011; 469: 241-4.
30. Hao C, Shi Y, Yu J, et al. The therapeutic function of the chemokine RANTES on the H22 hepatoma ascites model. Mol Cell Biochem. 2012; 367: 93-102.
31. Zhang J, Wang X, Lu H. Amifostine increases cure rate of cisplatin on ascites hepatoma 22 via selectively protecting renal thioredoxin reductase. Cancer Lett. 2008; 260: 127-36.
32. Wang Y, Juan LV, Ma X, et al. Specific hemosiderin deposition in spleen induced by a low dose of cisplatin: altered iron metabolism and its implication as an acute hemosiderin formation model. Curr Drug Metab. 2010; 11: 507-15.
33. Wang GP, Guan YS, Jin XR, et al. Development of novel 5-fluorouracil carrier erythrocyte with pharmacokinetics and potent antitumor activity in mice bearing malignant ascites. J Gastroenterol Hepatol. 2010; 25: 985-90.
34. Zhang Y, Bai M, Zhang B, et al. Uncovering pharmacological mechanisms of Wu-tou decoction acting on rheumatoid arthritis through systems approaches: drug-target prediction, network analysis and experimental validation. Sci Rep. 2015; 5: 9463.
35. Zhang Y, Guo X, Xiong L, et al. MicroRNA-101 suppresses SOX9-dependent tumorigenicity and promotes favorable prognosis of human hepatocellular carcinoma. FEBS Lett. 2012; 586: 4362-70.
36. Lin ZY, Huang YQ, Zhang YQ, et al. MicroRNA-224 inhibits progression of human prostate cancer by downregulating TRIB 1. Int J Cancer. 2014; 135: 541-50.
37. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001; 25: 402-8.
38. Zhang Y, Li Z, Yang M, et al. Identification of GRB2 and GAB1 coexpression as an unfavorable prognostic factor for hepatocellular carcinoma by a combination of expression profile and network analysis. PLoS One. 2013; 8: e85170.
39. Zhang Y, Guo X, Yang M, et al. Identification of AKT kinases as unfavorable prognostic factors for hepatocellular carcinoma by a combination of expression profile, interaction network analysis and clinical validation. Mol Biosyst. 2014; 10: 215-22.
40. Xu H, Zhang Y, Lei Y, et al. A Systems Biology-Based Approach to Uncovering the Molecular Mechanisms Underlying the Effects of Dragon's Blood Tablet in Colitis, Involving the Integration of Chemical Analysis, ADME Prediction, and Network Pharmacology. PLoS One. 2014; 9: e101432.
41. [Internet] http://www.genecards.org/cgi-bin/carddisp.pl?gene=ADRB1
42. Kessel I, Makhoul IR, Sujov P. Congenital hypothyroidism and nonimmune hydrops fetalis: associated? Pediatrics. 1999; 103: E9.
43. Ladmakhi MH, Buys N, Vanderpooten A, et al. Myocardial beta-adrenergic receptor characteristics in T(3)-induced ascites and in broiler lines differing in ascites susceptibility. Avian Pathol. 1997; 26: 293-303.
44. [Internet] http://www.genecards.org/cgi-bin/carddisp.pl?gene=PIK3CG
45. Tapia-Abellán A, Ruiz-Alcaraz AJ, Antón G, et al. Regulatory role of PI3K-Akt on the release of IL-1β in peritoneal macrophages from the ascites of cirrhotic patients. Clin Exp Immunol. In press.
46. Tapia-Abellán A, Ruiz-Alcaraz AJ, Hernández-Caselles T, et al. Role of MAP kinases and PI3K-Akt on the cytokine inflammatory profile of peritoneal macrophages from the ascites of cirrhotic patients. Liver Int. 2013; 33: 552-60.
47. [Internet] http://www.genecards.org/cgi-bin/carddisp.pl?gene=AVPR2
48. Sakaida I. Tolvaptan for the treatment of liver cirrhosis oedema. Expert Rev Gastroenterol Hepatol. 2014; 8: 461-70.
49. Watson H, Jepsen P, Wong F, et al. Satavaptan treatment for ascites in patients with cirrhosis: a meta-analysis of effect on hepatic encephalopathy development. Metab Brain Dis. 2013; 28: 301-5.
50. Habib S, Boyer TD. Vasopressin V2-receptor antagonists in patients with cirrhosis, ascites and hyponatremia. Therap Adv Gastroenterol. 2012; 5: 189-97.