Integrative nucleophosmin mutation-associated microRNA and gene expression pattern analysis identifies novel microRNA - target gene interactions in acute myeloid leukemia

Background MicroRNAs are regulators of gene expression, which act mainly by decreasing mRNA levels of their multiple targets. Deregulated microRNA expression has been shown for acute myeloid leukemia, a disease also characterized by altered gene expression associated with distinct genomic aberrations such as nucleophosmin (NPM1) mutations. To shed further light on the role of deregulated microRNA and gene expression in cytogenetically normal acute myeloid leukemia with NPM1 mutation we performed an integrative analysis of microRNA and mRNA expression data sets.Design and Methods Both microRNA and gene expression profiles were investigated in samples from a cohort of adult cytogenetically normal acute myeloid leukemia patients (n=43; median age 46 years, range 23–60 years) with known NPM1 mutation status (n=23 mutated, n=20 wild-type) and the data were integratively analyzed. Putative microRNA-mRNA interactions were validated by quantitative reverse transcriptase polymerase chain reaction, western blotting and luciferase reporter assays. For selected microRNAs, sensitivity of microRNA-overexpressing cells to cytarabine treatment was tested by FACS viability and cell proliferation assays.Results Our integrative approach of analyzing both microRNA- and gene expression profiles in parallel resulted in a refined list of putative target genes affected by NPM1 mutation-associated microRNA deregulation. Of 177 putative microRNA – target mRNA interactions we identified and validated 77 novel candidates with known or potential involvement in leukemogenesis, such as IRF2-miR-20a, KIT-miR-20a and MN1-miR-15a. Furthermore, our data showed that deregulated expression of tumor suppressor microRNAs, such as miR-29a and miR-30c, might contribute to sensitivity to cytarabine, which is observed in NPM1 mutated acute myeloid leukemia.Conclusions Overall, our observations highlight that integrative data analysis approaches can improve insights into leukemia biology, and lead to the identification of novel microRNA - target gene interactions of potential relevance for acute myeloid leukemia treatment.