Literature data have revealed that a number of oral squamous cell carcinoma (OSCC) can develop from dysplastic lesions, which can be classified as leukoplakias and erythroplakias. The biological behavior of these precancerous lesions and the identification of which ones will undergo malignant transformation are poorly understood. The proportion of leukoplakias that develops to OSCC depends on clinical follow-up, but it is estimated a malignant transformation rate of 1-2% per year. Risk factors for OSCC development involve lesion size and degree of dysplasia. Furthermore, leukoplakia recurrence can occur despite of its removal or cancer can develop outside of the visible lesion. There is no efficient treatment that can prevent the OSCC onset. Histological grading difficulties, no effective treatment of leukoplakia and the limited number of studies in this area justify the use of molecular studies that allow the identification of biomarkers for evaluation of progression risk and to contribute to the identification of molecular targets for treatment. microRNAs (miRNAs) are small, non-coding endogenous RNAs that negatively regulate gene expression at the post-transcriptional and or translational level. Accumulating evidence suggests that the deregulation of miRNAs not only results in cancer progression, but also promotes tumor initiation. Using global gene expression analysis in 30 leukoplakia (3 of them were positive for Human Papillomavirus), we identified a set of genes differentially expressed previously described in oral carcinomas. In this study, we will evaluate 20 leukoplakia matched with contralateral normal mucosal from the same patients for global microRNAs (miRNAs) expression analysis (Agilent Human miRNA Microarray). Using bioinformatics tools, these data will be integrated with the large-scale expression analysis aiming to identify molecular markers of tumor initiation or progression. Putative molecular markers and their regulators will be selected and validated by transcript expression analysis (RT-qPCR).
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