Identification of subtype specific miRNA-mRNA functional regulatory modules in matched miRNA-mRNA expression data: multiple myeloma as a case.

Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it is important to identify subtype specific miRNA-mRNA modules. In this study, we integrated the Ping-Pong algorithm and multiobjective genetic algorithm to identify subtype specific miRNA-mRNA functional regulatory modules (MFRMs) through integrative analysis of three biological data sets: GO biological processes, miRNA target information, and matched miRNA and mRNA expression data. We applied our method on a heterogeneous disease, multiple myeloma (MM), to identify MM subtype specific MFRMs. The constructed miRNA-mRNA regulatory networks provide modular outlook at subtype specific miRNA-mRNA interactions. Furthermore, clustering analysis demonstrated that heterogeneous MFRMs were able to separate corresponding MM subtypes. These subtype specific MFRMs may aid in the further elucidation of the pathogenesis of each subtype and may serve to guide MM subtype diagnosis and treatment.