Investigação do perfil de metilação de genes candidatos a biomarcadores na endometriose

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Zimbardi, Daniela [UNESP]
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11449/124006
Resumo: The endometriosis is a multi-factorial and chronic disease affecting 5% to 10% of women in reproductive age characterized by endometrium-like tissue (gland and stromma) outside uterine cavity. Although its etiology is poorly understood, recent evidences have indicated that epigenetic alterations are implicated in the pathophysiology. This hypothesis has been supported by findings surrounding altered DNA methylation pattern of specific genes, as well as by altered levels of expression of epigenetic machinery components in endometriotic lesions compared to eutopic endometrium from the same patient or endometrium of women free of disease. Thus, a better understanding of the role of epigenetic mechanisms in the pathogenesis and progression of endometriosis has become necessary and may contribute to the identification of diagnostic markers and for designing new therapeutic approaches that could benefit and improve the quality of life of women with this condition. In this context, this study aimed to identify differentially methylated genes as candidate biomarkers in endometriosis. The results could be organized in two papers. The first study aimed to investigate the profile of differential DNA methylation in intestinal endometriosis compared to eutopic endometrium of paired samples from the same patient. For this, we carried out a large-scale approach based on microarray containing 27,800 CpG islands, resulting in the identification of 546 genes as hypermethylated and 871 genes as hipomethylated. In silico analysis for the functional classification of differentially methylated genes enabled us to identify sets of genes with functions of transcription factors, chromatin remodeling, besides other functional classes. After conducting a comparative assessment with data available in other large-scale studies of literature, it was possible to recognize recurrent alteratons evolving 227 hypermethylated and 322 hypomethylated ...