Coexpression network analysis in chronic hepatitis B and C hepatic lesions reveals distinct patterns of disease progression to hepatocellular carcinoma

Journal of Molecular Cell Biology

Volumn 4, Issue 3, 2012, Pages 140-152

  He, Danning ^a,b   Liu, Zhi Ping ^a   Honda, Masao ^c   Kaneko, Shuichi ^c   Chen, Luonan ^a  

^a SIBS Novo Nordisk Translational Research Centre for PreDiabetes   (China)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c KANAZAWA UNIVERSITY   (Japan)

Author keywords

disease progression; gene coexpression network; hepatitis B and C virus; hepatocellular carcinoma; systems biology

Indexed keywords

CELL PROTEIN; MEMBRANE PROTEIN; PROTEIN TYROSINE KINASE;

APOPTOSIS; ARTICLE; CANCER GROWTH; COMPARATIVE STUDY; ENDOCYTOSIS; EXTERNAL VALIDITY; GENE EXPRESSION; GENE IDENTIFICATION; HEPATITIS B; HEPATITIS C; HUMAN; INTERNAL VALIDITY; LIVER CARCINOGENESIS; LIVER CELL CARCINOMA; MEMBRANE TRANSPORT; MICROARRAY ANALYSIS; NONHUMAN; SIGNAL TRANSDUCTION; VIRUS CELL INTERACTION; VIRUS INFECTION;

APOPTOSIS; CARCINOMA, HEPATOCELLULAR; DISEASE PROGRESSION; HEPACIVIRUS; HEPATITIS B VIRUS; HEPATITIS B, CHRONIC; HEPATITIS C, CHRONIC; HUMANS; LIVER; LIVER NEOPLASMS;

HEPATITIS B VIRUS; HEPATITIS C VIRUS;

EID: 84861893428     PISSN: 16742788     EISSN: 17594685     Source Type: Journal    
DOI: 10.1093/jmcb/mjs011     Document Type: Article

References (40)

1. Alexandros, K., and David, M. (2006). Support vector machines in R. J Stat. Softw. 15, 9.
2. Ashfaq, U.A., Javed, T., Rehman, S., et al. (2011). An overview of HCV molecular biology, replication and immune responses. Virol. J 8, 161.
3. Blanchard, E., Belouzard, S., Goueslain, L., et al. (2006). Hepatitis C virus entry depends on clathrin-mediated endocytosis. Virol. J. 80, 6964-6972.
4. Bonilla Guerrero, R., and Roberts, L.R. (2005). The role of hepatitis B virus integrations in the pathogenesis of human hepatocellular carcinoma. J. Hepatol. 42, 760-777.
5. Bouchard, M.J., and Navas-Martin, S. (2011). Hepatitis B and C virus hepatocarcinogenesis: lessons learned and future challenges. Cancer Lett. 305, 123-143.
6. Chen, X., Cheung, S.T., So, S., et al. (2002). Gene expression patterns in human liver cancers. Mol. Biol. Cell 13, 1929-1939.
7. Chen, X., Higgins, J., Cheung, S.T., et al. (2004). Novel endothelial cell markers in hepatocellular carcinoma. Mod. Pathol. 17, 1198-1210.
8. Chen, L., Wang, R.S., and Zhang, X.S. (2009). Biomolecular Networks: Methods and Applications in Systems Biology. New Jersey: John Wiley & Sons, Inc.
9. Chen, L., Liu, R., Liu, Z.P., et al. (2012). Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers. Sci. Rep. 2, 342.
10. Chung, Y.L., Sheu, M.L., and Yen, S.H. (2003). Hepatitis C virus NS5A as a potential viral Bcl-2 homologue interacts with Bax and inhibits apoptosis in hepatocellular carcinoma. Int. J. Cancer 107, 65-73.
11. de Chassey, B., Navratil, V., Tafforeau, L., et al. (2008). Hepatitis C virus infection protein network. Mol. Syst. Biol. 4, 230.
12. Deng, Y.B., Nagae, G., Midorikawa, Y., et al. (2010). Identification of genes preferentially methylated in hepatitis C virus-related hepatocellular carcinoma. Cancer Sci. 101, 1501-1510.
13. Dewey, F.E., Perez, M.V., Wheeler, M.T., et al. (2011). Gene coexpression network topology of cardiac development, hypertrophy, and failure. Circ. Cardiovasc. Genet. 4, 26-35.
14. Dong, J., and Horvath, S. (2007). Understanding network concepts in modules. BMC Syst. Biol. 1, 24.
15. Gautier, L., Cope, L., Bolstad, B.M., et al. (2004). affy-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20, 307-315.
16. Guidotti, L.G., Rochford, R., Chung, J., et al. (1999). Viral clearance without destruction of infected cells during acute HBV infection. Science 284, 825-829.
17. Honda, M., Yamashita, T., Ueda, T., et al. (2006). Different signaling pathways in the livers of patients with chronic hepatitis B or chronic hepatitis C. Hepatology 44, 1122-1138.
18. Iizuka, N., Oka, M., Mori, N., et al. (2002). Comparison of gene expression profiles between hepatitis B virus-and hepatitis C virus-infected hepatocellular carcinoma by oligonucleotide microarray data on the basis of a supervised learning method. Cancer Res. 62, 3939-3944.
19. Ivliev, A.E., Hoen, P.A., and Sergeeva, M.G. (2010). Coexpression network analysis identifies transcriptional modules related to proastrocytic differentiation and sprouty signaling in glioma. Cancer Res. 70, 10060-10070.
20. Lan, K.H., Sheu, M.L., Hwang, S.J., et al. (2002). HCV NS6A interacts with p53 and inhibits p53-mediated apoptosis. Oncogene 21, 4801-4811.
21. Langfelder, P., Zhang, B., andHorvath, S. (2007).Defining clusters froma hierarchical cluster tree: the Dynamic Tree Cut library for R.Bioinformatics 24, 719-720.
22. Langfelder, P., Luo, R., Oldham, M.C., et al. (2011). Is my network module preserved and reproducible? PLoS Comput. Biol. 7, e1001057.
23. Liu, Z.P., Wang, Y., Zhang, X.S., et al. (2012). Network-based analysis of complex diseases. IET Syst. Biol. 6, 22-33.
24. Mas, V.R., Maluf, D.G., Archer, K.J., et al. (2009). Genes involved in viral carcinogenesis and tumor initiation in hepatitis C virus-induced hepatocellular carcinoma. Mol. Med. 15, 85-94.
25. Miller, J.A., Horvath, S., and Geschwind, D.H. (2010). Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc. Natl Acad. Sci. USA 107, 12698-12703.
26. Oldham, M.C., Konopka, G., Iwamoto, K., et al. (2008). Functional organization of the transcriptome in human brain. Nat. Neurosci. 11, 1271-1282.
27. Perz, J.F., Armstrong, G.L., Farrington, L.A., et al. (2006). The contributions of hepatitis B virus and hepatitis C virus infections to cirrhosis and primary liver cancer worldwide. J. Hepatol. 45, 529-538.
28. Rabe, B., Delaleau, M., Bischof, A., et al. (2009). Nuclear entry of hepatitis B virus capsids involves disintegration to protein dimers followed by nuclear reassociation to capsids. PLoS Pathog. 5, e1000563.
29. Ravasz, E., Somera, A.L., Mongru, D.A., et al. (2002). Hierarchical organization of modularity in metabolic networks. Science 297, 1551-1555.
30. Seeger, C., Zoulim, F., and Mason, W.S. (2007). Fields Virology. Philadelphia: Lippincott Williams & Wilkins.
31. Smyth, G.K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, Article 3.
32. Stuart, J.M., Segal, E., Koller, D., et al. (2003). A gene-coexpression network for global discovery of conserved genetic modules. Science 202, 249-255.
33. Troyanskaya, O., Cantor, M., Sherlock, G., et al. (2001). Missing value estimation methods for DNA microarrays. Bioinformatics 17, 520-525.
34. Tsai, W.L., and Chung, R.T. (2010). Viral hepatocarcinogenesis. Oncogene 29, 2309-2324.
35. Ura, S., Honda, M., Yamashita, T., et al. (2009). Differential microRNA expression between hepatitis B and hepatitis C leading disease progression to hepatocellular carcinoma. Hepatology 49, 1098-1112.
36. Wang, H., He, X., Band, M., et al. (2005). A study of inter-lab and inter-platform agreement of DNA microarray data. BMC Genomics 6, 71.
37. Wu, Z.J., Zhu, Y., Huang, D.R., et al. (2010). Constructing the HBV-human protein interaction network to understand the relationship between HBV and hepatocellular carcinoma. J. Exp. Clin. Cancer Res. 29, 146.
38. Wurmbach, E., Chen, Y.B., Khitrov, G., et al. (2007). Genome-wide molecular profiles of HCV-induced dysplasia and hepatocellular carcinoma. Hepatology 45, 938-947.
39. Yip, A., and Horvath, S. (2007). Gene network interconnectedness and the generalized topological overlap measure. BMC Bioinf. 8, 22.
40. Zhang, B., and Horvath, S. (2005). A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, Article 17.