Identification of hepatocellular carcinoma-related genes with a machine learning and network analysis

Journal of Computational Biology

Volumn 22, Issue 1, 2015, Pages 63-71

  Gui, Tuantuan ^a,b   Dong, Xiao ^c,d   Li, Rudong ^a   Li, Yixue ^a,c   Wang, Zhen ^a,c  

^a Shanghai Jiao Tong University Affiliated Sixth People s Hospital   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c SHANGHAI CENTER FOR BIOINFORMATION TECHNOLOGY   (China)

^d ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

Author keywords

Hepatocellular carcinoma; maximum relevance minimum redundancy; protein protein interaction.

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; GENE ONTOLOGY; GENE REGULATORY NETWORK; GENETIC DATABASE; GENETICS; HUMAN; LIVER CELL CARCINOMA; LIVER TUMOR; TUMOR GENE;

ARTIFICIAL INTELLIGENCE; CARCINOMA, HEPATOCELLULAR; DATABASES, GENETIC; GENE ONTOLOGY; GENE REGULATORY NETWORKS; GENES, NEOPLASM; HUMANS; LIVER NEOPLASMS; MODELS, GENETIC;

EID: 84920276400     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2014.0122     Document Type: Article

References (51)

1. Bignotti, E., Todeschini, P., Calza, S., et al. 2010. Trop-2 overexpression as an independent marker for poor overall survival in ovarian carcinoma patients. Eur. J. Cancer 46, 944-953.
2. Bogdanov, P., and Singh, A.K. 2010. Molecular function prediction using neighborhood features. IEEE/ACM Trans. Comput. Biol. Bioinform. 7, 208-217.
3. Chatoo, W., Abdouh, M., David, J., et al. 2009. The polycomb group gene Bmi1 regulates antioxidant defenses in neurons by repressing p53 pro-oxidant activity. J. Neurosci. 29, 529-542.
4. Chen, Z.J. 2005. Ubiquitin signalling in the NF-jB pathway. Nat. Cell Biol. 7, 758-765.
5. Cherian, M. 2003. Metallothioneins in human tumors and potential roles in carcinogenesis. Mut. Res. 533, 201-209.
6. Chou, K.-C. 1995. Prediction of protein structural classes. Biochem. Mol. Biol. 30, 275-349.
7. Chou, K.C. 2011. Some remarks on protein attribute prediction and pseudo amino acid composition. J. Theor. Biol. 273, 236-247.
8. Chou, K.C., and Shen, H.B. 2006. Predicting eukaryotic protein subcellular location by fusing optimized evidencetheoretic k-nearest neighbor classifiers. J. Proteome Res. 5, 1888-1897.
9. Chou, K.C., and Shen, H.B. 2008. Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc. 3, 153-162.
10. Chris Ding, H.P. 2005. Minimum redundancy feature selection from microarray gene expression data. J. Bioinform. Comput. Biol. 3, 185-205.
11. De Jay, N., Papillon-Cavanagh, S., Olsen, C., et al. 2013. mRMRe: an R package for parallelized mRMR ensemble feature selection. Bioinformatics 29, 2365-2368.
12. Dijkstra, E.W. 1959. A note on two problems in connexion with graphs. Num. Math. 1, 269-271.
13. Dziegiel, P., Forgacz, J., and Suder, E., et al. 2003. Prognostic significance of metallothionein expression in correlation with Ki-67 expression in adenocarcinoma of large intestine. Histol. Histopathol. 18, 401-407.
14. El-Serag, H.B., and Rudolph, K.L. 2007. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology 132, 2557-2576.
15. Fong, D., Moser, P., Krammel, C., et al. 2008a. High expression of TROP2 correlates with poor prognosis in pancreatic cancer. Br. J. Cancer 99, 1290-1295.
16. Fong, D., Spizzo, G., Gostner, J.M., et al. 2008b. TROP2: a novel prognostic marker in squamous cell carcinoma of the oral cavity. Mod. Pathol. 21, 186-191.
17. Garrett, S.H., Sens, M.A., and Shukla, D., et al. 2000. Metallothionein isoform 1 and 2 gene expression in the human prostate: downregulation of MT-1X in advanced prostate cancer. Prostate 43, 125-135.
18. Goulding, H., Jasani, B., Pereira, H., et al. 1995. Metallothionein expression in human breast cancer. Br. J. Cancer 72, 968-972.
19. Huang, T., Cui, W., Hu, L., et al. 2009. Prediction of pharmacological and xenobiotic responses to drugs based on time course gene expression profiles. PloS ONE 4, e8126.
20. Huangda, W., Sherman, B.T., and Lempicki, R.A. 2009a. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1-13.
21. Huangda, W., Sherman, B.T., and Lempicki, R.A. 2009b. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44-57.
22. Jaromir Gumulec, M.R., Vojtech, A., Rene, K., and Michal, M. 2014. Metallothionein-immunohistochemical cancer biomarker: a meta-analysis. PloS ONE 9, e85346.
23. Jayasurya, A., Bay, B.H., Yap, W.M., et al. 2000. Proliferative potential in nasopharyngeal carcinoma: correlation with metallothionein expression and tissue zinc levels. Carcinogenesis 21, 1809-1812.
24. Jemal, A., Bray, F., Center, M.M., et al. 2011. Global cancer statistics. CA Cancer J. Clin. 61, 69-90.
25. Jin, R., Bay, B.H., Chow, V.T., and Tan, P.H. 2001. Metallothionein 1F mRNA expression correlates with histological grade in breast carcinoma. Breast Cancer Res. Treat. 66, 265-272.
26. Joseph, M.G., Banerjee, D., Kocha, W., et al. 2001. Metallothionein expression in patients with small cell carcinoma of the lung: correlation with other molecular markers and clinical outcome. Cancer 92, 836-842.
27. Karaoz, U., Murali, T.M., Letovsky, S., et al. 2004. Whole-genome annotation by using evidence integration in functional-linkage networks. Proc. Natl. Acad. Sci. USA 101, 2888-2893.
28. Kourmpetis, Y.A.I., van Dijk, A.D.J., Bink, M.C.A.M., et al. 2010. Bayesian Markov random field analysis for protein function prediction based on network data. PloS ONE 5, e9293.
29. Letovsky, S., and Kasif, S. 2003. Predicting protein function from protein/protein interaction data: a probabilistic approach. Bioinformatics 19, i197-i204.
30. Li, B.Q., Zhang, J., Huang, T., et al. 2012. Identification of retinoblastoma related genes with shortest path in a proteinprotein interaction network. Biochimie 94, 1910-1917.
31. Llovet, J.M., Burroughs, A., and Bruix, J. 2003. Hepatocellular carcinoma. Lancet 362, 1907-1917.
32. Muhlmann, G., Spizzo, G., Gostner, J., et al. 2009. TROP2 expression as prognostic marker for gastric carcinoma. J. Clin. Pathol. 62, 152-158.
33. Nabieva, E., Jim, K., Agarwal, A., et al. 2005. Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps. Bioinformatics 21 Suppl 1, i302-i310.
34. Nartey, N.O., Banerjee, D., and Cherian, M.G. 1987a. Immunohistochemical localization of metallothionein in cell nucleus and cytoplasm of fetal human liver and kidney and its changes during development. Pathology 19, 233-238.
35. Nartey, N., Cherian, M.G., and Banerjee, D. 1987b. Immunohistochemical localization of metallothionein in human thyroid tumors. Am. J. Pathol. 129, 177-182.
36. Neo, S.Y., Leow, C.K., Vega, V.B., et al. 2004. Identification of discriminators of hepatoma by gene expression profiling using a minimal dataset approach. Hepatology 39, 944-953.
37. Ng, K.L., Ciou, J.S., and Huang, C.H. 2010. Prediction of protein functions based on function-function correlation relations. Comput. Biol. Med. 40, 300-305.
38. Peng, B., Gu, Y., Xiong, Y., et al. 2012. Microarray-assisted pathway analysis identifies MT1X & NFkappaB as mediators of TCRP1-associated resistance to cisplatin in oral squamous cell carcinoma. PloS ONE 7, e51413.
39. Ripani, E., Sacchetti, A., Corda, D., and Alberti, S. 1998. Human TROP-2 is a tumor-associated calcium signal transducer. Int. J. Cancer 76, 671-676.
40. Schmid, K.W., Ellis, I., Gee, J.M., et al. 1993. Presence and possible significance of immunocytochemically demonstrable metallothionein over-expression in primary invasive ductal carcinoma of the breast. Virchows Arch. A Pathol. Anat. Histopathol. 422, 153-159.
41. Sharan, R., Ulitsky, I., and Shamir, R. 2007. Network-based prediction of protein function. Mol. Syst. Biol. 3, 88.
42. Shibata, R., Mori, T., Du, W., et al. 2006. Overexpression of cyclase-associated protein 2 in multistage hepatocarcinogenesis. Clin. Cancer Res. 12, 5363-5368.
43. Smoot, M.E., Ono, K., Ruscheinski, J., et al. 2011. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27, 431-432.
44. Studer, R., Vogt, C.P., Cavigelli, M., et al. 1997. Metallothionein accretion in human hepatic cells is linked to cellular proliferation. Biochem. J. 328, 63-67.
45. Szklarczyk, D., Franceschini, A., Kuhn, M., et al. 2011. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 39, D561-D568.
46. Tan, Y., Sinniah, R., Bay, B.H., and Singh, G. 1999. Metallothionein expression and nuclear size in benign, borderline, and malignant serous ovarian tumours. J. Pathol. 189, 60-65.
47. Tao, X., Zheng, J.M., Xu, A.M., et al. 2007. Downregulated expression of metallothionein and its clinicopathological significance in hepatocellular carcinoma. Hepatol. Res. 37, 820-827.
48. Trerotola, M., Cantanelli, P., Guerra, E., et al. 2013. Upregulation of Trop-2 quantitatively stimulates human cancer growth. Oncogene 32, 222-233.
49. Tsuchiya, M., Parker, J.S., Kono, H., et al. 2010. Gene expression in nontumoral liver tissue and recurrence-free survival in hepatitis C virus-positive hepatocellular carcinoma. Mol. Cancer 9, 74.
50. Wang, H., Pan, K., Zhang, H.K., et al. 2008a. Increased polycomb-group oncogene Bmi-1 expression correlates with poor prognosis in hepatocellular carcinoma. J. Cancer Res. Clin. Oncol. 134, 535-541.
51. Wang, J., Day, R., Dong, Y., et al. 2008b. Identification of Trop-2 as an oncogene and an attractive therapeutic target in colon cancers. Mol. Cancer Ther. 7, 280-285.