ANALYSIS OF THE EXPRESSION PROFILE OF TTF-1, FOXE1, PAX8 AND DREAM GENES IN PATIENTS WITH THYROID NODULES

• Grant number: 12/23884-9
• Support type: Scholarships in Brazil - Master
• Effective date (Start): April 01, 2013
• Effective date (End): March 31, 2015
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal researcher: Laura Sterian
• Grantee: Fernando de Assis Batista
• Home Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Thyroid nodules, benign and malignant, have become increasingly frequent, impeling the search for markers for their diagnosis and prognosis. Three thyroid-specific transcription factors are involved in maintaining the differentiation of the gland and its carcinogenesis: TTF-1, FOXE1 and PAX8. The expression levels of these genes are related to the degree of tissue differentiation in thyroid tumors. The transcriptional repressor DREAM is also involved in thyroid-specific gene expression through interaction with the thyroglobulin gene and the transcription factors TTF-1, FOXE1 and PAX8. DREAM can also act as an intracellular endogenous effector of TSH receptor activating cAMP signaling. An increased expression of DREAM is related to the thyroid enlargement and nodular development. The study of the DREAM gene has already begun during the student's Undergraduate Research (FAPESP 2011/06474-9), in which we searched for mutations in this gene in patients with DTC. The purpose of this project is to analyze the expression of TTF-1, FOXE1, PAX8 and DREAM genes in benign and malignant thyroid tumor tissues and identify possible mutations in the DREAM gene in patients with thyroid nodules. For that purpose, DNA and RNA will be extracted from thyroid tumor tissues from 100 patients with DTC and another 100 patients with benign nodules. The analysis of gene expression will be performed by real time PCR and the detection of mutations in DREAM gene will be done by automatic sequencing. The data obtained will be correlated to clinical features and patients' outcomes.