MicroRNA (
miRNA) plays an important role in the degradation and inhibition of mRNAs and is a kind of essential
drug targets for
cancer therapy. To facilitate the clinical
cancer research, we proposed a network-based strategy to identify the
cancer-related
miRNAs and to predict their targeted genes based on the gene expression profiles. The strategy was validated by using the data sets of
acute myeloid leukemia (AML), breast invasive
carcinoma (BRCA), and kidney renal clear cell
carcinoma (KIRC). The results showed that in the top 20
miRNAs ranked by their degrees, 90.0% (18/20), 70.0% (14/20), and 70.0% (14/20)
miRNAs were found to be associated with the
cancers for AML, BRCA, and KIRC, respectively. The KEGG pathways and GO terms enriched with the genes that were predicted as the targets of the
cancer-related
miRNAs were significantly associated with the biological processes of
cancers. In addition, several genes, which were predicted to be regulated by more than three
miRNAs, were identified to be the potential
drug targets annotated by using the human
protein atlas database. Our results demonstrated that the proposed strategy can be helpful for predicting the
miRNA-
mRNA interactions in
tumorigenesis and identifying the
cancer-related
miRNAs as the potential
drug targets.