Ranking the relevance of genes targeted by cancer-associated MiRNAs

Abstract: MicroRNAs control the expression of their target genes by translational repression. They are involved in various biological processes including cancer progression. To uncover the biological role of microRNAs it is necessary to identify their target genes. The small number of experimentally validated target genes makes computer prediction methods very important. However, state of the art prediction tools result in a great number of putative targets. The number of false positives among those putative targets is unknown. This report proposes, investigates and analyses two ways of ranking the biological relevance of putative targets of miRNAs which are associated with breast cancer. One approach characterises values of network properties of the putative microRNA targets in the human Protein-Protein Interaction network and compares them to network property values of validated microRNA targets. Using these results we suggest a simple approach for ranking the relevance of putative targets. The approach consists of testing if a network property value of a putative target differs from the mean value of the network. In addition we study which network property contributes most to ranking using this approach. The second approach identifies commonly overrepresented Gene Ontology categories among putative microRNA targets, validated targets and known breast cancer genes. We investigate possibilities to use the occurrence of a putative target in these categories to rank its biological relevance. Finally we present a number of genes with interesting features considering both approaches. These genes might play a role in breast cancer progression and might be worth investigating further.