UTILIZAÇÃO DE METODOLOGIAS PARA ANÁLISE COMPARATIVA DE SEQUÊNCIAS NUCLEOTÍDICAS DE UM GENE RELACIONADO AO CÂNCER DE PELE - Santos Neto, Antonio Alves dos (2015)
The p53 gene is considered one of the most intensively studied genes from the genomic point of view and is related to the most common types of skin cancers, which show a trend of increasing incidence in modern human populations. DNA sequences of this gene are available in genomic databases with public access on the Internet and provide useful information for a wide range of applications. This research aimed to employ methods of comparative analysis of nucleotide sequences for evaluating mutations in the p53 gene in different countries, and evaluate the applicability of bioinformatics tools available on the web environment. Investigations were carried out to verify the most frequent mutations in the p53 gene whose sequences are deposited in human genomic databases located in the United States (NCBI), Europe (EBI) and Japan (DDBJ). In the NCBI database we found 194 mutant sequences of the p53 gene, and six of them were described as coming from people with skin cancer. In EBI database 62 mutant sequences of the p53 gene were found, and 50 were from patients with skin cancer. In DDBJ database we found 4075 mutant sequences for the same gene, but not identified as coming from patients with cancer. The original sequence of the p53 gene was compared with the mutant sequences derived from patients with various types of skin cancers, through the CLUSTALW and MAFFT bioinformatics tools. Studies comparing the mutant sequences allowed to establish relationships among the most frequent mutations and that might be related to the disease in different countries. The results showed the feasibility of the proposed approach, and allowed the identification of common characteristics between the analyzed mutants. It was possible to identify the gene regions most sensitive to changes in nucleotide sequences in the p53 gene, which might be related to the origin of the pathology. It was also possible to identify that the mutations commonly occur in very close areas, both for the sequences of the NCBI database as to those collected from EBI database.