Identification of microRNA-regulated network motifs for cancer disease pathways

摘要

Biological networks are formed by the interaction between biomolecules is the basis of all biological processes; such as protein-protein interaction networks, metabolic networks, gene regulatory networks and signal transduction networks. Such networks can be decomposed into smaller biological modules, also known as network motifs. Common motifs are auto-regulation loop, feedback loop, feed-forward loop, single-input motif (SIM), multi-input motif and bi-fan. In this study, we examine the regulatory pathways for several human cancer pathways, and identify the above mentioned six types of motifs. Some of the network motifs are interconnected which can be merged together. The present study identifies possible motif-motif interactions (MMIs). On the other hand, it is known that microRNAs (miRNA) could play the role of an oncogene and tumor-suppressor-gene. We coupled the MMI networks with miRNA data to establish a database of miRNA-regulated motifs for various cancer diseases. Among the cancer types we studied, bi-fan and SIM are the modules most often found. Some of the identified motifs are reported in the literature, which suggest the importance of modular structure in cancer formation. Bi-fan bi-fan interaction is the dominant type of MMI. MiRNA-regulated network motifs are identified, where certain bi-fan motifs are highly regulated by miRNAs. Given that a network motif can perform specific biological function, one may expect miRNA-regulated motif may result in observed phenotypic effects. The functional annotation of the network motifs are studied by using DAVID, which conducts Gene Ontology term enrichment analysis. A web-based interface has been set up for query, which can be accessed at: http://ppi.bioinfo.asia.edu.tw/pathway. This web service provides the following functionalities, (1) search for motif types according to cancer pathways, (2) query for MMI, and (3) retrieve miRNA-regulated motifs for a specific cancer type.