Uncovering the anticancer mechanism of Compound Kushen Injection against HCC by integrating quantitative analysis, network analysis and experimental validation

Scientific Reports

Volumn 8, Issue 1, 2018, Pages

  Gao, Li ^a   Wang, Ke Xin ^a   Zhou, Yu Zhi ^a   Fang, Jian Song ^b   Qin, Xue Mei ^a   Du, Guan Hua ^a,c  

^a SHANXI UNIVERSITY   (China)

^b GUANGZHOU UNIVERSITY OF CHINESE MEDICINE   (China)

^c INSTITUTE OF MATERIA MEDICA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85043528724     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-017-18325-7     Document Type: Article

References (61)

1. Singal, A. G. & El-Serag, H. B. Hepatocellular Carcinoma From Epidemiology to Prevention: Translating Knowledge into Practice. Clin Gastroenterol Hepatol 13, 2140-2151 (2015).
2. Yang, J. D. & Roberts, L. R. Hepatocellular carcinoma: A global view. Nat Rev Gastroenterol Hepatol 7, 448-458 (2010).
3. Laurent-Puig, P. et al. Genetic alterations associated with hepatocellular carcinomas define distinct pathways of hepatocarcinogenesis. Gastroenterology 120, 1763-1773 (2001).
4. Boyault, S. et al. Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets. Hepatology (Baltimore, Md.) 45, 42-52 (2007).
5. Gao, R. et al. Serum metabolomics to identify the liver disease-specific biomarkers for the progression of hepatitis to hepatocellular carcinoma. Sci rep 5, 18175 (2015).
6. Fitian, A. I. & Cabrera, R. Disease monitoring of hepatocellular carcinoma through metabolomics. World J Hepatol 9, 1-17 (2017).
7. Dutta, R. & Mahato, R. I. Recent advances in hepatocellular carcinoma therapy. Pharmacology & therapeutics 173, 106-117 (2017).
8. Guo, Y. M. et al. Efficacy of Compound Kushen Injection in relieving cancer-related pain: a systematic review and meta-analysis. Evid based complement alternat med 2015, 840742 (2015).
9. Ma, X. et al. The therapeutic efficacy and safety of compound kushen injection combined with transarterial chemoembolization in unresectable hepatocellular carcinoma: an update systematic review and meta-analysis. Frontiers in pharmacology 7, 70 (2016).
10. Qu, Z. et al. Identification of candidate anti-cancer molecular mechanisms of Compound Kushen Injection using functional genomics. Oncotarget 7, 66003-66019 (2016).
11. Hopkins, A. L. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 4, 682-690 (2008).
12. Zhang, Y. et al. Thyroid hormone synthesis: a potential target of a Chinese herbal formula Haizao Yuhu Decoction acting on iodinedeficient goiter. Oncotarget 7, 51699-51712 (2016).
13. Gao, L. et al. Molecular targets of Chinese herbs: a clinical study of hepatoma based on network pharmacology. Sci rep 6, 24944 (2016).
14. Fang, J. et al. Network pharmacology-based study on the mechanism of action for herbal medicines in Alzheimer treatment. J Ethnopharmacol 196, 281-292 (2017).
15. Su, W. H. et al. OncoDB. HCC: an integrated oncogenomic database of hepatocellular carcinoma revealed aberrant cancer target genes and loci. Nucleic Acids Res 35, D727-731 (2007).
16. Lee, L. et al. Liverome: a curated database of liver cancer-related gene signatures with self-contained context information. BMC genomics 12(Suppl 3), S3 (2011).
17. Anitha, P., Anbarasu, A. & Ramaiah, S. Gene network analysis reveals the association of important functional partners involved in antibiotic resistance: A report on an important pathogenic bacterium Staphylococcus aureus. Gene 575, 253-263 (2016).
18. Wishart, D. S. et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37, D603-610 (2009).
19. Markley, J. L. et al. New bioinformatics resources for metabolomics. Pac Symp Biocomput 2007, 157-168 (2007).
20. Li, Z. Y., He, P., Sun, H. F., Qin, X. M. & Du, G. H. (1)H NMR based metabolomic study of the antifatigue effect of Astragali Radix. Mol Biosyst 10, 3022-3030 (2014).
21. Li, Z., Li, A., Gao, J., Li, H. & Qin, X. Kidney tissue targeted metabolic profiling of unilateral ureteral obstruction rats by NMR. Front Pharmacol 7, 307 (2016).
22. Tu, H. et al. Efficacy of compound kushen injection in combination with induction chemotherapy for treating adult patients newly diagnosed with acute leukemia. Evid based complement alternat med 2016, 3121402 (2016).
23. Wang, S., Lian, X., Sun, M., Luo, L. & Guo, L. Efficacy of Compound Kushen injection plus radiotherapy on nonsmall-cell lungcancer: A systematic review and meta-analysis. J Cancer Res Ther 12, 1298-1306 (2016).
24. Lavecchia, A. & Cerchia, C. In silico methods to address polypharmacology: current status, applications and future perspectives. Drug Discov Today 21, 288-298 (2016).
25. Creixell, P. et al. Pathway and network analysis of cancer genomes. Nat Methods 12, 615-621 (2015).
26. Ru, J. et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 6, 13 (2014).
27. Chen, C. Y. TCM Database@Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico. PloS one 6, e15939 (2011).
28. Xue, R. et al. TCMID: Traditional Chinese Medicine integrative database for herb molecular mechanism analysis. Nucleic Acids Res 41, D1089-1095 (2013).
29. Xu, H. 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 9, e101432 (2014).
30. Liang, X., Li, H. & Li, S. A novel network pharmacology approach to analyse traditional herbal formulae: the Liu-Wei-Di-Huang pill as a case study. Mol Biosyst 10, 1014-1022 (2014).
31. Zhang, B., Wang, X. & Li, S. An integrative platform of TCM network pharmacology and its application on a herbal formula, Qing-Luo-Yin. Evid based complement alternat med 2013, 456747 (2013).
32. Fiandalo, M. V. & Kyprianou, N. Caspase control: protagonists of cancer cell apoptosis. Exp Oncol 34, 165-175 (2012).
33. Giannelli, G. et al. Clinical role of MMP-2/TIMP-2 imbalance in hepatocellular carcinoma. Int J Cancer 97, 425-431 (2002).
34. Rotte, A., Martinka, M. & Li, G. MMP2 expression is a prognostic marker for primary melanoma patients. Cell Oncol (Dordr) 35, 207-216 (2012).
35. Zhao, Y. et al. RNAi silencing of c-Myc inhibits cell migration, invasion, and proliferation in HepG2 human hepatocellular carcinoma cell line: c-Myc silencing in hepatocellular carcinoma cell. Cancer Cell Int 13, 23 (2013).
36. Lasserre, C., Christa, L., Simon, M. T., Vernier, P. & Brechot, C. A novel gene (HIP) activated in human primary liver cancer. Cancer Res 52, 5089-5095 (1992).
37. Christa, L. et al. Hepatocarcinoma-intestine-pancreas/pancreatic associated protein (HIP/PAP) is expressed and secreted by proliferating ductules as well as by hepatocarcinoma and cholangiocarcinoma cells. Am J Pathol 155, 1525-1533 (1999).
38. Dieckgraefe, B. K. et al. Expression of the regenerating gene family in inflammatory bowel disease mucosa: Reg Ialpha upregulation, processing, and antiapoptotic activity. J Investig Med 50, 421-434 (2002).
39. Zhu, Y. et al. System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia. Sci rep 5, 17068 (2015).
40. Annibaldi, A. & Widmann, C. Glucose metabolism in cancer cells. Curr Opin Clin Nutr Metab Care 13, 466-470 (2010).
41. Ma, T. et al. Metabonomics applied in exploring the antitumour mechanism of physapubenolide on hepatocellular carcinoma cells by targeting glycolysis through the Akt-p53 pathway. Sci rep 6, 29926 (2016).
42. Vander Heiden, M. G., Cantley, L. C. & Thompson, C. B. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science (New York, N. Y.) 324, 1029-1033 (2009).
43. Chesney, J. et al. Fructose-2, 6-bisphosphate synthesis by 6-phosphofructo-2-kinase/fructose-2, 6-bisphosphatase 4 (PFKFB4) is required for the glycolytic response to hypoxia and tumor growth. Oncotarget 5, 6670-6686 (2014).
44. Hirschhaeuser, F., Sattler, U. G. & Mueller-Klieser, W. Lactate: a metabolic key player in cancer. Cancer Res 71, 6921-6925 (2011).
45. Dang, C. V. Links between metabolism and cancer. Genes Dev 26, 877-890 (2012).
46. Jose, C., Bellance, N. & Rossignol, R. Choosing between glycolysis and oxidative phosphorylation: a tumor's dilemma? Biochim Biophys Acta 1807, 552-561 (2011).
47. Broggini-Tenzer, A., Vuong, V. & Pruschy, M. Metabolism of tumors under treatment: mapping of metabolites with quantitative bioluminescence. Radiother Oncol 99, 398-403 (2011).
48. Le, A. et al. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab 15, 110-121 (2012).
49. Turcan, S. et al. IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype. Nature 483, 479-483 (2012).
50. Ye, H. et al. HIT: linking herbal active ingredients to targets. Nucleic Acids Res 39, D1055-1059 (2011).
51. Gong, J. et al. ChemMapper: a versatile web server for exploring pharmacology and chemical structure association based on molecular 3D similarity method. Bioinformatics (Oxford, England) 29, 1827-1829 (2013).
52. Jensen, L. J. et al. STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 37, D412-416 (2009).
53. Lopes, C. T. et al. Cytoscape Web: an interactive web-based network browser. Bioinformatics (Oxford, England) 26, 2347-2348 (2010).
54. de Jong, H., Geiselmann, J., Hernandez, C. & Page, M. Genetic Network Analyzer: qualitative simulation of genetic regulatory networks. Bioinformatics (Oxford, England) 19, 336-344 (2003).
55. Vastrik, I. et al. Reactome: a knowledge base of biologic pathways and processes. Genome Biol 8, R39 (2007).
56. Wang, J. et al. The mir-675-5p regulates the progression and development of pancreatic cancer via the UBQLN1-ZEB1-mir200 axis. Oncotarget 8, 24978-24987 (2017).
57. Li, Y. et al. Long non-coding RNA MALAT1 promotes gastric cancer tumorigenicity and metastasis by regulating vasculogenic mimicry and angiogenesis. Cancer Lett 395, 31-44 (2017).
58. Feng, T. et al. Growth factor progranulin promotes tumorigenesis of cervical cancer via PI3K/Akt/mTOR signaling pathway. Oncotarget 7, 58381-58395 (2016).
59. Liu, H. et al. Correlations between TBL1XR1 and recurrence of colorectal cancer. Sci rep 7, 44275 (2017).
60. Cuperlovic-Culf, M. et al. (1)H NMR metabolomics analysis of renal cell carcinoma cells: Effect of VHL inactivation on metabolism. Int J Cancer 138, 2439-2449 (2016).
61. Gao, J. et al. Metscape: a Cytoscape plug-in for visualizing and interpreting metabolomic data in the context of human metabolic networks. Bioinformatics (Oxford, England) 26, 971-973 (2010).