BackgroundCurrent evidence implicates aberrant microRNA expression patterns in human malignancies; measurement of microRNA expression may have diagnostic and prognostic applications. Roles for microRNAs in head and neck squamous cell carcinomas (HNSCC) are largely unknown. HNSCC, a smoking-related cancer, is one of the most common malignancies worldwide but reliable diagnostic and prognostic markers have not been discovered so far. Some studies have evaluated the potential use of microRNA as biomarkers with clinical application in HNSCC.MethodsMicroRNA expression profile of oral squamous cell carcinoma samples was determined by means of DNA microarrays. We also performed gain-of-function assays for two differentially expressed microRNA using two squamous cell carcinoma cell lines and normal oral keratinocytes. The effect of the over-expression of these molecules was evaluated by means of global gene expression profiling and cell proliferation assessment.ResultsAltered microRNA expression was detected for a total of 72 microRNAs. Among these we found well studied molecules, such as the miR-17-92 cluster, comprising potent oncogenic microRNA, and miR-34, recently found to interact with p53. HOX-cluster embedded miR-196a/b and miR-10b were up- and down-regulated, respectively, in tumor samples. Since validated HOX gene targets for these microRNAs are not consistently deregulated in HNSCC, we performed gain-of-function experiments, in an attempt to outline their possible role. Our results suggest that both molecules interfere in cell proliferation through distinct processes, possibly targeting a small set of genes involved in cell cycle progression.ConclusionsFunctional data on miRNAs in HNSCC is still scarce. Our data corroborate current literature and brings new insights into the role of microRNAs in HNSCC. We also show that miR-196a and miR-10b, not previously associated with HNSCC, may play an oncogenic role in this disease through the deregulation of cell proliferation. The study of microRNA alterations in HNSCC is an essential step to the mechanistic understanding of tumor formation and could lead to the discovery of clinically relevant biomarkers.

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