Abstract
Wilms tumor, or nephroblastoma, is a cancer of the kidneys that typically occurs in children and rarely in adults. Around 10% of Wilms tumor patients are diagnosed having a concurrent syndrome that enhances the risk of Wilms tumor. A screening method for early detection of Wilms tumor in these patients would be beneficial, since the size or stage of a tumor is related to outcome. We introduce a miRNA pathway analysis methodology that takes into account the topology and regulation mechanisms of the gene regulatory networks and identify disrupted sub-paths in known pathways, using miRNA expressions. The methodology was applied on a miRNA-expression study and a predictive model was developed, using machine-learning (decision-tree induction) approaches. The model is able to identify putative mechanisms that underlie and govern the Wilms tumor phenotype, and discriminate between diseased and healthy subjects. Initial experimental results are promising and in line with the relevant biomedical literature.