Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.
ABSTRACT. To identify potential targets for the early treatment and prevention of gastric cancer, microRNA (miRNA) expression profiles of precancerous lesions of gastric cancer were investigated. The miRNA microarray dataset GSE24839 was downloaded from Gene Expression Omnibus (GEO) and included 10 Helicobacter pylori-related gastritis samples and 10 gastric intestinal metaplasia samples. Differentially expressed miRNAs (DEMs) were screened using the Student t-test; P < 0.05 was considered to be statistically significant. Co-expression networks of total miRNAs and DEMs were constructed based on the Pearson correlation coefficient for the two diseases. Target genes of the DEMs were retrieved using miRecords and pathway-enrichment analysis was performed using a hypergeometric test. A total of 20 DEMs were obtained for H. pylori-related gastritis and gastric intestinal metaplasia samples, including 12 up-regulated and 8 down-regulated miRNAs. The identified DEMs appear to play key roles in gastric cancer, as the average degree of the DEM sub-network was higher than that of the total miRNA co-expression network. Furthermore, target genes for 6 DEMs (hsa-miR-106b, hsa-miR-193a-3p, hsa-miR-204, hsa-miR-30e, hsa-miR-519d, and hsa-miR-524-5p) are in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including signal transduction, cell growth and death, and transport and catabolism. Among the target genes, 5 (RAB22A, SOX4, IKZF2, PLAG1, and BTBD7) were of interest because they can be simultaneously regulated by several DEMs. These findings suggest that these genes may be targets for modulating gastric cancer progression.
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