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Protein-protein Interaction Network Analyses for Elucidating the Roles of LOXL2-delta72 in Esophageal Squamous Cell Carcinoma

  • Wu, Bing-Li (Department of Biochemistry and Molecular Biology, Shantou University Medical College) ;
  • Zou, Hai-Ying (Department of Biochemistry and Molecular Biology, Shantou University Medical College) ;
  • Lv, Guo-Qing (Department of Biochemistry and Molecular Biology, Shantou University Medical College) ;
  • Du, Ze-Peng (Department of Pathology, Shantou Central Hospital, Affiliated Shantou Hospital of Sun Yat-sen University) ;
  • Wu, Jian-Yi (Department of Biochemistry and Molecular Biology, Shantou University Medical College) ;
  • Zhang, Pi-Xian (Department of Biochemistry and Molecular Biology, Shantou University Medical College) ;
  • Xu, Li-Yan (Institute of Oncologic Pathology, Shantou University Medical College) ;
  • Li, En-Min (Department of Biochemistry and Molecular Biology, Shantou University Medical College)
  • Published : 2014.03.01

Abstract

Lysyl oxidase-like 2 (LOXL2), a member of the lysyl oxidase (LOX) family, is a copper-dependent enzyme that catalyzes oxidative deamination of lysine residues on protein substrates. LOXL2 was found to be overexpressed in esophageal squamous cell carcinoma (ESCC) in our previous research. We later identified a LOXL2 splicing variant LOXL2-delta72 and we overexpressed LOXL2-delta72 and its wild type counterpart in ESCC cells following microarray analyses. First, the differentially expressed genes (DEGs) of LOXL2 and LOXL2-delta72 compared to empty plasmid were applied to generate protein-protein interaction (PPI) sub-networks. Comparison of these two sub-networks showed hundreds of different proteins. To reveal the potential specific roles of LOXL2- delta72 compared to its wild type, the DEGs of LOXL2-delta72 vs LOXL2 were also applied to construct a PPI sub-network which was annotated by Gene Ontology. The functional annotation map indicated the third PPI sub-network involved hundreds of GO terms, such as "cell cycle arrest", "G1/S transition of mitotic cell cycle", "interphase", "cell-matrix adhesion" and "cell-substrate adhesion", as well as significant "immunity" related terms, such as "innate immune response", "regulation of defense response" and "Toll signaling pathway". These results provide important clues for experimental identification of the specific biological roles and molecular mechanisms of LOXL2-delta72. This study also provided a work flow to test the different roles of a splicing variant with high-throughput data.

References

  1. Peinado H, Del Carmen Iglesias-de la Cruz M, Olmeda D, et al (2005). A molecular role for lysyl oxidase-like 2 enzyme in snail regulation and tumor progression. EMBO J, 24, 3446-58. https://doi.org/10.1038/sj.emboj.7600781
  2. Zou Q, Yang ZL, Yuan Y, et al (2013). Clinicopathological features and CCT2 and PDIA2 expression in gallbladder squamous/adenosquamous carcinoma and gallbladder adenocarcinoma. World J Surg Oncol, 11, 143. https://doi.org/10.1186/1477-7819-11-143
  3. Zhu X, Gerstein M, Snyder M (2007). Getting connected: analysis and principles of biological networks. Genes Dev, 21, 1010-24. https://doi.org/10.1101/gad.1528707
  4. Zhu XL, Ai ZH, Wang J, et al (2012). Weighted gene coexpression network analysis in identification of endometrial cancer prognosis markers. Asian Pac J Cancer Prev, 13, 4607-11. https://doi.org/10.7314/APJCP.2012.13.9.4607
  5. Parkin DM, Bray F, Ferlay J, et al (2005). Global cancer statistics, 2002. CA Cancer J Clin, 55, 74-108. https://doi.org/10.3322/canjclin.55.2.74
  6. Pavlopoulos GA, Secrier M, Moschopoulos CN, et al (2011). Using graph theory to analyze biological networks. BioData Min, 4, 10. https://doi.org/10.1186/1756-0381-4-10
  7. Peng L, Ran YL, Hu H, et al (2009). Secreted LOXL2 is a novel therapeutic target that promotes gastric cancer metastasis via the Src/FAK pathway. Carcinogenesis, 30, 1660-9. https://doi.org/10.1093/carcin/bgp178
  8. Ruckert F, Joensson P, Saeger HD, et al (2010). Functional analysis of LOXL2 in pancreatic carcinoma. Int J Colorectal Dis, 25, 303-11. https://doi.org/10.1007/s00384-009-0853-5
  9. Skotheim RI, Nees M (2007). Alternative splicing in cancer: noise, functional, or systematic? Int J Biochem Cell Biol, 39, 1432-49. https://doi.org/10.1016/j.biocel.2007.02.016
  10. Venables JP (2006). Unbalanced alternative splicing and its significance in cancer. Bioessays, 28, 378-86. https://doi.org/10.1002/bies.20390
  11. Wang GS, Cooper TA (2007). Splicing in disease: disruption of the splicing code and the decoding machinery. Nat Rev Genet, 8, 749-61. https://doi.org/10.1038/nrg2164
  12. WP, Tzou WS (2009). Computational methods for discovering gene networks from expression data. Brief Bioinform, 10, 408-23.
  13. Wu B, Li C, Zhang P, et al (2013). Dissection of miRNA-miRNA interaction in esophageal squamous cell carcinoma. PLoS One, 8, e73191. https://doi.org/10.1371/journal.pone.0073191
  14. Zhou YQ, He C, Chen YQ, et al (2003). Altered expression of the RON receptor tyrosine kinase in primary human colorectal adenocarcinomas: generation of different splicing RON variants and their oncogenic potential. Oncogene, 22, 186-97. https://doi.org/10.1038/sj.onc.1206075
  15. Lehne B, Schlitt T (2009). Protein-protein interaction databases: keeping up with growing interactomes. Hum Genomics, 3, 291-7.
  16. Keshava Prasad TS, Goel R, Kandasamy K, et al (2009). Human Protein Reference Database--2009 update. Nucleic Acids Res, 37 (Database issue), D767-72. https://doi.org/10.1093/nar/gkn892
  17. Kim Y, Boyd CD, Csiszar K (1995). A new gene with sequence and structural similarity to the gene encoding human lysyl oxidase. J Biol Chem, 270, 7176-82. https://doi.org/10.1074/jbc.270.13.7176
  18. Koh GC, Porras P, Aranda B, et al (2012). Analyzing proteinprotein interaction networks. J Proteome Res, 11, 2014-31. https://doi.org/10.1021/pr201211w
  19. Li CG, Gruidl M, Eschrich S, et al (2008). Insig2 is associated with colon tumorigenesis and inhibits Bax-mediated apoptosis. Int J Cancer, 123, 273-82. https://doi.org/10.1002/ijc.23510
  20. Li M, Wu X, Wang J, et al (2012). Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression data. BMC Bioinformatics, 13, 109. https://doi.org/10.1186/1471-2105-13-109
  21. Li TY, Xu LY, Wu ZY, et al (2012). Reduced nuclear and ectopic cytoplasmic expression of lysyl oxidase-like 2 is associated with lymph node metastasis and poor prognosis in esophageal squamous cell carcinoma. Hum Pathol, 43, 1068-76. https://doi.org/10.1016/j.humpath.2011.07.027
  22. Liu HX, Cartegni L, Zhang MQ, et al (2001). A mechanism for exon skipping caused by nonsense or missense mutations in BRCA1 and other genes. Nat Genet, 27, 55-8.
  23. Ma Z, Guo W, Niu HJ, et al (2012). Transcriptome network analysis reveals potential candidate genes for esophageal squamous cell carcinoma. Asian Pac J Cancer Prev, 13, 767-73. https://doi.org/10.7314/APJCP.2012.13.3.767
  24. Pan XH (2012). Pathway crosstalk analysis based on proteinprotein network analysis in ovarian cancer. Asian Pac J Cancer Prev, 13, 3905-9. https://doi.org/10.7314/APJCP.2012.13.8.3905
  25. Chatr-Aryamontri A, Breitkreutz BJ, Heinicke S, et al (2013). The BioGRID interaction database: 2013 update. Nucleic Acids Res, 41 (Database issue), D816-23. https://doi.org/10.1093/nar/gks1158
  26. Bindea G, Mlecnik B, Hackl H, et al (2009). ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics, 25, 1091-3. https://doi.org/10.1093/bioinformatics/btp101
  27. Blencowe BJ (2006). Alternative splicing: new insights from global analyses. Cell, 126, 37-47. https://doi.org/10.1016/j.cell.2006.06.023
  28. Caffarel MM, Chattopadhyay A, Araujo AM, et al (2013). Tissue transglutaminase mediates the pro-malignant effects of oncostatin M receptor over-expression in cervical squamous cell carcinoma. J Pathol, 231, 168-79. https://doi.org/10.1002/path.4222
  29. Cline MS, Smoot M, Cerami E, et al (2007). Integration of biological networks and gene expression data using Cytoscape. Nat Protoc, 2, 2366-82. https://doi.org/10.1038/nprot.2007.324
  30. Fong SF, Dietzsch E, Fong KS, et al (2007). Lysyl oxidase-like 2 expression is increased in colon and esophageal tumors and associated with less differentiated colon tumors. Genes Chromosomes Cancer, 46, 644-55. https://doi.org/10.1002/gcc.20444
  31. Gao YH, Li TY, Gao ZF, et al (2008). Expression of LOXL2 protein in cholangiocarcinoma tissues and relation with EMT. Zhonghua Pu Tong Wai Ke Za Zhi, 23, 794-7.
  32. Herranz N, Dave N, Millanes-Romero A, et al (2012). Lysyl oxidase-like 2 deaminates lysine 4 in histone H3. Mol Cell, 46, 369-76. https://doi.org/10.1016/j.molcel.2012.03.002
  33. Ke L (2002). Mortality and incidence trends from esophagus cancer in selected geographic areas of China circa 1970-90. Int J Cancer, 102, 271-4. https://doi.org/10.1002/ijc.10706
  34. Barker HE, Chang J, Cox TR, et al (2011). LOXL2-mediated matrix remodeling in metastasis and mammary gland involution. Cancer Res, 71, 1561-72. https://doi.org/10.1158/0008-5472.CAN-10-2868
  35. Ahn SG, Dong SM, Oshima A, et al (2013). LOXL2 expression is associated with invasiveness and negatively influences survival in breast cancer patients. Breast Cancer Res Treat, 141, 89-99. https://doi.org/10.1007/s10549-013-2662-3
  36. Assenov Y, Ramirez F, Schelhorn SE, et al (2008). Computing topological parameters of biological networks. Bioinformatics, 24, 282-4. https://doi.org/10.1093/bioinformatics/btm554
  37. Barabasi AL, Oltvai ZN (2004). Network biology: understanding the cell's functional organization. Nat Rev Genet, 5, 101-13. https://doi.org/10.1038/nrg1272

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