Topology of protein–protein interaction network and edge reduction co-efficiency in VEGF signaling of breast cancer

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.