Revista de investigación de oncología Acceso abierto

Abstracto

Investigation of Non-Synonymous Snps in Genes Associated with Oxidative Stress that may be Important in Thyroid Carcinogenesis

Teixeira ES1, Dal’ Bó IF1, Nascimento M1, Leão SLS1, Ferreira Filho AC1, Torres IOS1, Rabi LT1,2, Peres KC1; Cunha LL3, Bufalo NE1,4,5, Ward LS1*

Thyroid cells have intense circulation of free radicals and oxidizing metabolites such as hydrogen peroxide, from the synthesis of thyroid hormones, and iodide, from the iodination of thyroglobulin. Without an efficient antioxidant system, the generation of reactive oxygen species (ROS) can cause deleterious effects leading to DNA damage. ROS have been associated with many diseases, including cancer. Mitochondrial superoxide dismutase MnSOD (SOD2), glutathione peroxidase (GPX-1), glucose-6-phosphate dehydrogenase (G6PD), and p22phox (one of the subunits of the NOX enzyme complex) are transcribed by the SOD2, GPX-1, G6PD and CYBA genes, respectively. They play an important role in the generation of reactive species and in redox control and are crucial in cellular protection against oxidative stress. Genetic variants can affect protein function and therefore promote disturbances of redox balance, which increases the risk of cell damage by ROS. The connection between oxidative stress and thyroid diseases has been extensively investigated and suggests an important role for SOD2, GPX-1, G6PD and CYBA variants. To better understand the role of variants in the function of the corresponding proteins and their potential effect on thyroid carcinogenesis, we used bioinformatics tools to perform in silico analyzes of non-synonymous SNPs (nsSNPs) of these genes. A total of 1662 nsSNPs were retrieved from the NCBI database dbSNP data and analyzed by a suite of computational platforms: SIFT, PROVEAN, PolyPhen 2.0, PANTHER, SNAP 2, PhD-SNP, SNPs and GO, PMut, Mupro and I-Mutant v3. 23 nsSNPs were predicted by the tool consensus to be harmful. In conclusion, we demonstrate that in silico study can provide a solid foundation and assist researchers in the selection of SNPs, optimizing laboratory experimental analyses.