Topology preservation of disease-specific networks via TFmiR

Various methods for identifying differentially expressed genes yield quite different results. Here, we showed that key genes in regulatory networks derived by downstream analysis from lists of differentially expressed genes are a more robust alternative for the understanding of disease processes. As a basis for this, we used regulatory networks involving transcription factors, microRNAs, and target genes that we predicted with our TFmiR web server [1] from a set of differentially expressed genes and identified hotspot degree genes using this tool. Then we applied the ILP formulation of minimum dominating set [2] to find the key dominators in the underlying networks. Here, we processed RNA-Seq data taken from The Cancer Genome Atlas (TCGA) for matched tumor and normal samples of hepatocellular carcinoma (liver cancer) and breast cancer patients. Differentially expressed genes were identified by four different bioinformatics tools. While the overlap between the sets of significant differentially expressed genes was only 26 % in liver cancer and 28 % in breast cancer, we found that the topology of the regulatory networks constructed using TFmiR for the different sets of differentially expressed genes was highly similar with respect to hub degree nodes and dominators. This suggests that key genes identified in regulatory networks derived from differentially expressed genes may be a more robust basis for understanding diseases processes than simply inspecting the lists of differentially expressed genes. [1] TFmiR: A Web Server for Constructing and Analyzing Disease-specific Transcription Factor and miRNA co-regulatory Networks. Mohamed Hamd, Christian Spaniol, Maryam Nazarieh , Volkhard Helms . Nucleic Acid Research, 2015. Available at: http://service.bioinformatik.uni-saarland.de/tfmir [2] Identification of Key Player Genes in Gene Regulatory Networks. Maryam Nazarieh , Andreas Wiese, Thorsten Will, Mohamed Hamed, Volkhard Helms . BMC System Biology, 2016. Available at: http://apps.cytoscape.org/apps/mcds , https://github.com/maryamNazarieh/KeyRegulatoryGenes