Categorization and Estimation of Relative Connectivity of Genes from Meta-OFTEN Network

Authors: U. Kairov, T. Karpenyuk, E. Ramanculov, A. Zinovyev

Abstract:

The most common result of analysis of highthroughput data in molecular biology represents a global list of genes, ranked accordingly to a certain score. The score can be a measure of differential expression. Recent work proposed a new method for selecting a number of genes in a ranked gene list from microarray gene expression data such that this set forms the Optimally Functionally Enriched Network (OFTEN), formed by known physical interactions between genes or their products. Here we present calculation results of relative connectivity of genes from META-OFTEN network and tentative biological interpretation of the most reproducible signal. The relative connectivity and inbetweenness values of genes from META-OFTEN network were estimated.

Keywords: Microarray, META-OFTEN, gene network.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328092

References:

[1] van-t Veer L.J., Dai H., van de Vijver M.J. et al. "Gene expression profiling predicts clinical outcome of breast cancer". Nature, 415:530-6, 2002.
[2] van de Vijver M.J., van't Veer L.J. et al. "ðÉ gene-expression signature as a predictor of survival in breast cancer". N. Engl. J. Med., 347:1999- 2009, 2002.
[3] Wang Y., Klijn J.G., Zhang Y., Sieuwerts A.M. et al. "Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer" Lancet, 365(9460):671-9, 2005.
[4] Cobleigh M.A., Tabesh B., Bitterman P., Baker J., Cronin M., Liu M.L., Borchik R., Mosquera J.M., Walker M.G., Shak S. "Tumor gene expression and prognosis in breast cancer patients with 10 or more positive lymph nodes" Clin. Cancer Res., 11(24 Pt 1):8623-31, 2005.
[5] Chuang H.-Y. et al. "Network-based classification of breast cancer metastasis" Mol. Syst. Biol., 3:140, 2007.
[6] Rapaport F., Zinovyev A., Dutreix M., Barillot E., Vert J.-P. "Classification of microarray data using gene networks" BMC Bioinformatics, 8:35, 2007.
[7] Foekens J. A. et al. "Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer" J. Clin. Oncol., 24:1665-1671, 2006.
[8] Finocchiaro G. et al. "Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME" Nucleic Acids Res., 35(7): 2343, 2007.
[9] Reyal F., van Vliet M.H., Armstrong N.J., Horlings H.M., de Visser K.E., Kok M., Teschendorff A.E., Mook S., van 't Veer L., Caldas C., Salmon R.J., van de Vijver M.J., Wessels L.F. "A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer" Breast Cancer Res., 10(6):R93, 2008.
[10] Kairov U., Karpenyuk T., Ramanculov E., Zinovyev A. "Network analysis of gene lists for finding reproducible prognostic breast cancer gene signatures" Bioinformation, 8(16):773-6, 2012.
[11] Cline M., Smoot M., Cerami E. et al. "Integration of biological networks and gene expression data using Cytoscape" Nature Protocols, 2:2366 - 2382, 2007.
[12] Zinovyev A. et al. "BiNoM: a Cytoscape plugin for manipulating and analyzing biological networks" Bioinformatics, 24(6):876, 2008.
[13] Huang D.W., Sherman B.T., Lempicki R.A. "Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists" Nucleic Acids Res., 37(1):1-13, 2009.
[14] Barillot E., Calzone L., Hupe P., Vert J.-P., Zinovyev A. "Computational Systems Biology of Cancer" CRC Press Inc, Chapman & Hall/CRC Mathematical & Computational Biology, 452ÐÇ., 2012.
[15] Pinna G., Zinovyev A., Araujo N., Morozova N., Harel-Bellan A. "Analysis of the growth control network specific for human lung adenocarcinoma cells" Math. Model. Nat. Phenom., 7(01):337-368, 2012.
[16] Chen J., Sam L., Huang Y., Lee Y., Li J., Liu Y., Xing H.R., Lussier Y.A. "Protein interaction network underpins concordant prognosis among heterogeneous breast cancer signatures" J Biomed. Inform., 43(3): 385-396, 2010.