P1.26 Micrornas' Expression Profile and their Correlation with Clinical Outcome in head and Neck Squamous Cell Carcinoma

Head-Neck squamous cell carcinoma (HNSCC) is the sixth leading cause of cancer in the world. Recent studies have shown that p53 mutations represent an important determinant of the malignancy of oral lesions. The TNM staging system does not adequately address the molecular heterogeneity of HNSCC tumors. miRNAs' expression profile is emerging among the best markers for diagnosis, staging and treatment of cancer. The present project aims at characterizing miRNAs signatures with prognostic, predictive or diagnostic power in HNSCC and at identifying possible correlations with TP53 status. Patients with histologically proven HNSCC who underwent surgical treatment without any previous chemo/radio-therapeutic treatment were included in the study. Two biopsies, from the tumor itself and normal tissue, were obtained for each patient and submitted to RNA and genomic DNA extraction.TP53 status was assessed in 114 patients, by direct sequencing of exons 2 to11, and 68 out of these showed TP53 mutations. TP53 status was also evaluated in the normal counterparts and a wild-type TP53 sequence was found in all cases. microRNAs' expression profiling was performed on a subset of 66 patients using the Agilent platform. Seventy-two miRNAs are differentially regulated in the HNSCC samples when compared with their normal tissue counterparts (using p-value<10-3 and fold change>2 as cut-off). Preliminary results from the integration between microRNAs' expression data and clinical information evidenced a correlation between the expression of some microRNAs and clinical outcome. The percentage of TP53 mutations (60%) in our HNSCC population is higher than the previously established TP53 mutation rate in this cancer in Italy (IARC Database: www-p53.iarc.fr). Microarray analysis indicates that microRNAs are strongly modulated between HNSCC tumor and non-tumor samples and many of the altered microRNAs in our data, are concordant with previous reports. Ongoing analyses are integrating microRNAs' expression data with clinical information in order to evaluate the predictive/prognostic power of the modulated microRNAs and the correlation with TP53 status in tumors.