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Characterization of Wild-Type and Mutated RET Proto-Oncogene Associated with Familial Medullary Thyroid Cancer

  • Masbi, Mohammad Hosein (Noor Genetic Diagnostic Laboratory, Ahvaz Jundishapur University of Medical) ;
  • Mohammadiasl, Javad (Department of Medical Genetics, Faculty of Medicine, Ahvaz Jundishapur University of Medical) ;
  • Galehdari, Hamid (Faculty of Science, Genetic Department, Shahid Chamran University) ;
  • Ahmadzadeh, Ahmad (Health Research Institute, Thalassemia and Hemoglobinopathies Research Center, Ahvaz Jundishapur University of Medical Sciences) ;
  • Tabatabaiefar, Mohammad Amin (Department of Medical Genetics, Faculty of Medicine, Ahvaz Jundishapur University of Medical) ;
  • Golchin, Neda (Noor Genetic Diagnostic Laboratory, Ahvaz Jundishapur University of Medical) ;
  • Haghpanah, Vahid (Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences Tehran) ;
  • Rahim, Fakher (Health Research Institute, Hearing Research Center, Ahvaz Jundishapur University)
  • Published : 2014.03.01

Abstract

Background: We aimed to assess RET proto-oncogene polymorphisms in three different Iranian families with medullary thyroid cancer (MTC), and performed molecular dynamics simulations and free energy stability analysis of these mutations. Materials and Methods: This study consisted of 48 patients and their first-degree relatives with MTC confirmed by pathologic diagnosis and surgery. We performed molecular dynamics simulations and free energy stability analysis of mutations, and docking evaluation of known RET proto-oncogene inhibitors, including ZD-6474 and ponatinib, with wild-type and mutant forms. Results: The first family consisted of 27 people from four generations, in which nine had the C.G2901A (P.C634Y) mutation; the second family consisted of six people, of whom three had the C.G2901T (P.C634F) mutation, and the third family, who included 12 individuals from three generations, three having the C.G2251A (P.G691S) mutation. The automated 3D structure of RET protein was predicted using I-TASSER, and validated by various protein model verification programs that showed more than 96.3% of the residues in favored and allowed regions. The predicted instability indices of the mutated structures were greater than 40, which reveals that mutated RET protein is less thermo-stable compared to the wild-type form (35.4). Conclusions: Simultaneous study of the cancer mutations using both in silico and medical genetic procedures, as well as onco-protein inhibitor binding considering mutation-induced drug resistance, may help in better overcoming chemotherapy resistance and designing innovative drugs.

Keywords

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