Abstract
In this paper we create and analyze a protein-protein interaction network (PPIN) of colorectal cancer (CRC). First we identify proteins that are related to the CRC (set of seed proteins). Using this set we generate the CRC PPIN with the help of Cytoscape. We analyze this PPIN in a twofold manner. We first extract important topological features for proteins in the network which we use to determine CRC essential proteins. Next we perform a modular analysis by discovering CRC significant functional terms through the process of GO enrichment within densely connected subgroups (clusters) of the PPIN. The modular analysis results in a mapping from the CRC significant terms to CRC significant proteins. Finally, we combine the topological and modular evidence for the proteins in the CRC PPIN, exclude the initial seed proteins and obtain a list of proteins that could be taken as possible bio-markers for CRC.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kreeger, P.K., Lauffenburger, D.A.: Cancer systems biology: a network modeling perspective. Carcinogenesis 31(1), 2–8 (2010)
Consortium, U., et al.: UniProt: a hub for protein information. Nucleic Acids Res. gku989 (2014)
Alberghina, L., Höfer, T., Vanoni, M.: Molecular networks and system-level properties. J. Biotechnol. 144(3), 224–233 (2009)
Wachi, S., Yoneda, K., Wu, R.: Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues. Bioinformatics 21(23), 4205–4208 (2005)
Rhodes, D.R., Chinnaiyan, A.M.: Integrative analysis of the cancer transcriptome. Nat. Genet. 37, S31–S37 (2005)
Mani, K.M., Lefebvre, C., Wang, K., Lim, W.K., Basso, K., Dalla-Favera, R., Califano, A.: A systems biology approach to prediction of oncogenes and molecular perturbation targets in B-cell lymphomas. Mol. Syst. Biol. 4(1), 169 (2008)
Jonsson, P.F., Bates, P.A.: Global topological features of cancer proteins in the human interactome. Bioinformatics 22(18), 2291–2297 (2006)
Aragues, R., Sander, C., Oliva, B.: Predicting cancer involvement of genes from heterogeneous data. BMC Bioinform. 9(1), 1 (2008)
Forbes, S.A., Bindal, N., Bamford, S., Cole, C., Kok, C.Y., Beare, D., Jia, M., Shepherd, R., Leung, K., Menzies, A., et al.: COSMIC: mining complete cancer genomes in the catalogue of somatic mutations in cancer. Nucleic Acids Res. gkq929 (2010)
Maglott, D., Ostell, J., Pruitt, K.D., Tatusova, T.: Entrez gene: gene-centered information at NCBI. Nucleic Acids Res. 33(Suppl. 1), D54–D58 (2005)
Aranda, B., Blankenburg, H., Kerrien, S., Brinkman, F.S., Ceol, A., Chautard, E., Dana, J.M., De Las Rivas, J., Dumousseau, M., Galeota, E., et al.: PSICQUIC and PSISCORE: accessing and scoring molecular interactions. Nat. Methods 8(7), 528–529 (2011)
Bader, G.D., Betel, D., Hogue, C.W.: BIND: the biomolecular interaction network database. Nucleic Acids Res. 31(1), 248–250 (2003)
Liu, T., Lin, Y., Wen, X., Jorissen, R.N., Gilson, M.K.: BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 35(Suppl. 1), D198–D201 (2007)
Stark, C., Breitkreutz, B.J., Reguly, T., Boucher, L., Breitkreutz, A., Tyers, M.: BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 34(Suppl. 1), D535–D539 (2006)
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
Bader, G.D., Hogue, C.W.: An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform. 4(1), 1 (2003)
Morris, J.H., Apeltsin, L., Newman, A.M., Baumbach, J., Wittkop, T., Su, G., Bader, G.D., Ferrin, T.E.: clusterMaker: a multi-algorithm clustering plugin for cytoscape. BMC Bioinform. 12(1), 1 (2011)
Bindea, G., Mlecnik, B., Hackl, H., Charoentong, P., Tosolini, M., Kirilovsky, A., Fridman, W.H., Pagès, F., Trajanoski, Z., Galon, J.: ClueGO: a cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25(8), 1091–1093 (2009)
Alvord, G., Roayaei, J., Stephens, R., Baseler, M.W., Lane, H.C., Lempicki, R.A.: The david gene functional classification tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol. 8(9), 183 (2007)
Maere, S., Heymans, K., Kuiper, M.: BiNGO: a cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21(16), 3448–3449 (2005)
Acknowledgement
The work in this paper was partially financed by the Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, as part of the “Analysis of nutrigenomic data” project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Ristovski, Z., Trivodaliev, K., Kalajdziski, S. (2018). Analysis of Protein Interaction Network for Colorectal Cancer. In: Stojanov, G., Kulakov, A. (eds) ICT Innovations 2016. ICT Innovations 2016. Advances in Intelligent Systems and Computing, vol 665. Springer, Cham. https://doi.org/10.1007/978-3-319-68855-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-68855-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-68854-1
Online ISBN: 978-3-319-68855-8
eBook Packages: EngineeringEngineering (R0)