Molecular analyses of thyroid tumors for diagnosis of malignancy on fine-needle aspiration biopsies and for prognosis of invasiveness on surgical specimens

High throughput genetic and genomic analyses have allowed the identification of series of genes exhibiting either distinct expression profiles or a particular mutational status in the different types or subtypes of thyroid tumors. The use of molecular data to improve the preoperative diagnosis of thyroid cancer on materiel from fine-needle aspiration biopsy (FNAB) is in the course of validation by numerous teams throughout the world. We have proposed a molecular test based on the expression level of a series of 19 genes, capable of discriminating malignant from benign tumors [15]. A prospective study aiming at the clinical validation of the molecular test has been performed on a cohort of 730 patients with a thyroid nodule. In patients subjected to tumor resection (≈ 220), the preoperative molecular diagnosis (generated on FNAB material from analyses of the expression level of the 19 genes) was compared to the postoperative diagnosis given by the pathologist (used as reference). Treatment and follow-up of the serious forms of thyroid cancer should benefit by the early identification of tumors with a metastatic potential using molecular characteristics differentiating invasive and non-invasive thyroid carcinomas. We have performed genetic and genomic analyses on a series of 200 papillary thyroid carcinomas (non-invasive or NI-PTC, 50%; invasive or I-PTC, 50%). BRAFV600E mutation or/and RET/PTC gene rearrangement have been detected in less than 25% of NI-PTC but in more than 75% of I-PTC. Pan-genomic analyses (Agilent microarray) revealed that 1373 genes are differentially expressed (fold change greater than 2) in NI-PTC as compared to I-PTC samples. The majority of genes (≈ 1200) are overexpressed in I-PTC. Data related to the two domains: diagnosis and prognosis of thyroid cancer will be presented at 2011 International H.P. KLOTZ conference on Clinical Endocrinology.