Abstract
Here, we summarize the identification of possible hub protein in the core VEGF-induced interactome in breast cancer by the application of centrality measures. This approach has been extended to investigate the role of subnetworks in the core interactome. For the identification of subnetworks, we applied a protein network-based approach to find the novel insight in the function of pathways involved in breast cancer. A PPI network was constructed and the complexity of network was simplified to modules using molecular complex detection algorithm. Topological analysis of PPI network was performed to assess the functional significance of selected genes using KEGG and PubAngioGen database. Globally accepted centrality measure, Betweenness centrality, Degree distribution and Clustering co-efficient metrics were used to find the hub protein by scale-free network analysis. The bottleneck nodes in the subnetworks were found to be involved in regulating endothelial cell proliferation, central carbon metabolism, signal complex assembly, Phosphatidylinositol 3-kinase (PI3K), Vascular endothelial growth factor (VEGF), Erb-B receptor tyrosine kinase (ErbB) and prolactin signaling pathway. Wherein, main interconnecting hub nodes find their predominant distribution. Moreover, these main hub nodes were subjected to power graph analysis to further reduce the number of edges to 80% without losing the basic biological information, as it helps us to understand much better about highly interconnected nodes.
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References
Altomare DA, Testa JR (2005) Perturbations of the AKT signaling pathway in human cancer. Oncogene 24(50):7455–7464
Assenov Y, Ramirez F, Schelhorn SE, Lengauer T, Albrecht M (2008) Computing topological parameters of biological networks. Bioinformatics 24(2):282–284
Bader Gary D, Hogue Christopher WV (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform 4:2
Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, Fridman WH, Pages F, Trajanoski Z, Galon J (2009) ClueGo: a cytoscape plug-into decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25:1091–1093
Boudreau N, Myers C (2003) Breast cancer-induced angiogenesis: multiple mechanisms and the role of the microenvironment. Breast Cancer Res 5:140–146
Cao D, Hou M, Guan YS, Jiang M, Yang Y et al (2009) Expression of HIF-1alpha and VEGF in colorectal cancer: association with clinical outcomes and prognostic implications. BMC Cancer 9:432
Cheng D, Knox C, Young N, Stothard P, Damaraju S, Wishart DS (2008) PolySearch: a web-based text mining system for extracting relationships between human diseases, genes, mutations, drugs and metabolites. Nucleic Acids Res 36:W399–W405
Chin C-H, Chen S-H, Wu H-H, Ho C-W, Ko M-T, Lin C-Y (2014) CytoHubba: identifying hub objects and subnetworks from complex interactome. BMC Syst Biol 8(Suppl 4):S11
Couch FJ, Nathanson KL, Offit K (2014) Two decades after BRCA: setting paradigms in personalized cancer care and prevention. Science 343:1466
Cybulski C, Wokolorczyk D, Jakubowska A, Huzarski T, Byrski T, Gronwald J (2011) Risk of breast cancer in women with a CHEK2 mutation with and without a family history of breast cancer. J Clin Oncol 29:3747–3752
Folkman J, Kalluri R (2004) Cancer without disease. Nature 427:787
Gentilini D, Busacca M, Di Francesco S, Vignali M, Viganò P, Di Blasio AM (2007) PI3K/Akt and ERK1/2 signalling pathways are involved in endometrial cell migration induced by 17 beta-estradiol and growth factors. Mol Hum Reprod 13(5):317–322
Huang DW, Sherman BT, Lempicki RA (2008) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57
Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D (2011) Global cancer statistics. CA Cancer J Clin 61(2):69–90
Jiang H, Chen SS, Yang J, Chen J, He B, Zhu LH, Wang L (2012) CREB-binding protein silencing inhibits thrombin-induced endothelial progenitor cells angiogenesis. Mol Biol Rep 39:2773–2779
Ju X, Katiyar S, Wang C, Liu M, Jiao X, Li S, Zhou J, Turner J, Lisanti MP, Russell RG, Mueller SC, Ojeifo J, Chen WS, Hay N, Pestell RG (2007) Akt1 governs breast cancer progression in vivo. Proc Natl Acad Sci USA 104(18):7438–7443
Kanehisa M, Goto S (2000) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28(1):27–30
Kang HJ, Kim HJ, Rih JK, Mattson TL, Kim KW, Cho CH, Isaacs JS, Bae I (2006) BRCA1 plays a role in the hypoxic response by regulating HIF-1 stability and by modulating vascular endothelial growth factor expression. J Biol Chem 281:13047–13056
Kang Z, Zhu H, Luan H, Han F, Jiang W (2014) Curculigoside A induces angiogenesis through VCAM-1/Egr-3/CREB/VEGF signaling pathway. Neuroscience 267:232–240
Khurana P, Tiwari D, Sugadev R, Sarkar S, Singh SB (2016) A comprehensive assessment of networks and pathways of hypoxia-associated proteins and identification of responsive protein modules. Netw Model Anal Health Inform Bioinform 5:17
Li P, Liu Y, Wang H, He Y, Wang X, He Y, Lv F, Chen H, Pang X, Liu M, Shi T, Yi Z (2014) PubAngioGen: a database and knowledge for angiogenesis and related diseases. Nucleic Acids Res 10:1093–1139
Maragoudakis ME, Tsopanoglou NE, Andriopoulou P (2002) Mechanism of thrombin-induced angiogenesis. Biochem Soc Trans 30(2):173–177
Mukohara T (2015) PI3K mutations in breast cancer: prognostic and therapeutic implications. Breast Cancer 7:111–123
Petit AM, Rak J, Hung M-C, Rockwell P, Goldstein N, Fendly B, Kerbel RS (1997) Neutralizing antibodies against EGF and ErbB-2/neu receptor tyrosine kinases down-regulate VEGF production by tumor cells in vitro and in vivo: angiogenic implications for signal transduction therapy of solid tumors. Am J Pathol 151:1523–1530
Prager GW, Poettler M (2012) Angiogenesis in cancer. Basic mechanisms and therapeutic advances. Hamostaseologie 322:105–114
Raman K (2010) Construction and analysis of protein–protein interaction networks. Autom Exp 2:2
Ran J, Li H, Fu J, Liu L, Xing Y, Li X, Shen H, Chen Y, Jiang X, Li Y (2013) Construction and analysis of the protein–protein interaction network related to essential hypertension. BMC Syst Biol 7:32
Relf M, LeJeune S, Scott PA, Fox S, Smith K, Leek R (1997) Expression of the angiogenic factors vascular endothelial cell growth factor, acidic and basic fibroblast growth factor, tumor growth factor beta-1, platelet-derived endothelial cell growth factor, placenta growth factor, and pleiotrophin in human primary breast cancer and its relation to angiogenesis. Cancer Res 57:963–969
Royer L, Reimann M, Andreopoulos B, Schroeder M (2008) Unravelling protein networks with power graph analysis. PLoS Comput Biol 4(7):e1000108
Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N, Klitgord N, Simon C, Boxem M, Milstein S, Rosenberg J, Goldberg DS, Zhang LV, Wong SL, Franklin G, Li S, Albala JS, Lim J, Fraughton C, Llamosas E, Cevik S, Bex C, Lamesch P, Sikorski RS, Vandenhaute J, Zoghbi HY, Smolyar A, Bosak S, Sequerra R, Doucette-Stamm L, Cusick ME, Hill DE, Roth FP, Vidal M (2005) Towards a proteome-scale map of the human protein–protein interaction network. Nature 437:1173–1178
Schuringa JJ, Schepers H, Vellenga E, Kruijer W (2001) Ser727‐dependent transcriptional activation by association of p300 with STAT3 upon IL‐6 stimulation. FEBS Lett 495:71–76
Semenza GL (2000) Hypoxia, clonal selection, and the role of HIF-1 in tumor progression. Crit Rev Biochem Mol Biol 352:71–103
Shannon P, Markiel A (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447–D452
Takeshita T, Yamamoto Y, Yamamoto-Ibusuki M, Inao T, Sueta A, Fujiwara S, Omoto Y, Iwase H (2015) Prognostic role of PIK3CA mutations of cell-free DNA in early-stage triple negative breast cancer. Cancer Sci 106(11):1582–1589
Vallabhajosyula RR, Chakravarti D, Lutfeali S, Ray A, Raval A, (2009) Identifying Hubs in Protein Interaction Networks. PLoS ONE 4(4):e5344
Wei D, Le X, Zheng L, Wang L, Frey JA, Gao AC, Peng Z, Huang S, Xiong HQ, Abbruzzese JL, Xie K (2003) Stat3 activation regulates the expression of vascular endothelial growth factor and human pancreatic cancer angiogenesis and metastasis. Oncogene 22:319–329
Yu D, Hung M-C (2000) Overexpression of ErbB2 in cancer and ErbB2-targeting strategies. Oncogene 19:6115–6121
Yu H, Kim PM, Sprecher E, Trifinov V, Gerstein M (2007) The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol 3(4):e59
Zhuang D-Y, Jiang L, He Q-Q, Zhou P, Yue T (2015) Identification of hub subnetwork based on topological features of genes in breast cancer. Int J Mol Med 35:664–674
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The authors are thankful to Registrar, Kuvempu University for providing all the facilities to complete this work and also thankful to Mr. Pavan kumar G S for his help in the designing of figures.
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Belenahalli Shekarappa, S., Kandagalla, S., Gollapalli, P. et al. Topology of protein–protein interaction network and edge reduction co-efficiency in VEGF signaling of breast cancer. Netw Model Anal Health Inform Bioinforma 6, 17 (2017). https://doi.org/10.1007/s13721-017-0157-6
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DOI: https://doi.org/10.1007/s13721-017-0157-6