MicroRNAs (miRNAs) are short single-stranded RNA molecules which have a critical role in the regulation of gene expression. Several miRNAs have been shown to be up- or downregulated in different tumor types and there is clear evidence that they are actively involved in cancer development. Depending on their target genes, microRNAs can act both as oncogenes or tumor suppressor genes. Identification of differentially expressed miRNAs and their target genes in cancer is likely to provide essential information on disease pathogenesis and thereby new tools for the clinical management of cancer. Here we aimed to identify differentially expressed miRNAs in pancreatic cancer and to explore their possible role in pancreatic cancer pathogenesis. To this end, we screened miRNA expression levels in 16 established pancreatic cancer cell lines and four normal human pancreatic RNA samples using miRNA arrays. Hierarchical clustering of the miRNA expression data separated the normal and cancer samples into two distinct clusters, indicating a specific miRNA signature in pancreatic cancer different from that seen in normal pancreas. The data analysis (eBayes method and the Benjamini-Hochberg adjustment) revealed a subset of 72 miRNAs which were either up- or downregulated (at least 1.5-fold, adjusted p-value <0.05) in pancreatic cancer compared with the normal samples. Among these were miRNAs previously linked to cancer, for example miR-21 and members of the let-7 family, but also novel differentially expressed miRNAs were identified. Twelve of the differentially expressed miRNAs were validated by qRT-PCR and a median Pearson correlation value of 0.83 was observed between the two methods, thus confirming the reliability of the microarray results. Of the 72 differentially expressed miRNAs, 35 had increased and 37 decreased expression in cancer samples. This is an interesting finding since miRNAs are generally believed to be more often downregulated than upregulated in cancer. Evaluation of the genomic localization of the differentially expressed miRNAs showed clustering at a few specific chromosomal sites suggesting that genomic aberrations might partly underlie the observed expression changes. To identify possible target genes for the differentially expressed miRNAs, we used the GOmir application which utilizes four different target prediction programs. A range of targets were identified, some of which were common for all four programs and thus represent the most probable target genes. Finally, selected miRNAs showing the most frequent differential expression in pancreatic cancer will be characterized and the functional consequences of their aberrant expression on cancer cell phenotype will be studied. By understanding the connections between miRNA expression, gene expression and cancer cell characteristics, we may be able to find new targets for the treatment of pancreatic cancer.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3043.