ABSTRACT
In this chapter we discuss current approaches to the analysis and biological interpretation of microRNA profiling data utilizing systems biology tools. Using Gene Ontology and Pathway Enrichment analysis in combination with the knowledge mining of cancer-related information we have developed an analysis pipeline that allows for global functional profiling of differentially expressed microRNA in cancer. To illustrate the utility of these methods, were view the main results of our recently published studies including comparison of predicted targets for five published datasets of aberrantly expressed microRNAs in human cancers and in-depthanalysis of functions and pathways affected by an overexpressed cluster of miRNAs in hepatocellular carcinoma. Using combinatorial enrichment analysis – a modification of GO enrichment analysis, we have identified Gene Ontology categories as well as biological functions, disease categories, toxicological categories, and signaling pathways that are: targeted by multiple microRNAs; statistically significantly enriched with target genes; and known to be affected in specific cancers. Our results suggest that coexpressed miRNAs provide systemic compensatory response to the cancerspecific phenotypic changes by downregulating functional categories and signaling pathways that are known to be abnormally activated in a particular cancer.
