Expression of genes involved in miRNA biogenesis in EMSC from menstrual flow of women with and without endometriosis

• Grant number: 19/22021-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2020
• End date: February 28, 2021
• Field of knowledge: Health Sciences - Medicine - Maternal and Child Health
• Principal Investigator: Juliana Meola Lovato
• Grantee: Ana Clara Lagazzi Cressoni
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Endometriosis is a disease of complex and multifactorial etiopathogenesis. One of the most studied theories to explain its origin is that of retrograde menstrual flow that spreads "viable endometrial cells" to the peritoneal cavity. Recently, a complementary hypothesis has been raised that endometrial mesenchymal stem cells (eMSC) could participate in the development of endometriosis. Moreover, it is known that for the establishment and development of the disease occurs deregulation of gene expression, which can be mediated at different levels, among them, there is the participation of microRNAs, which act at the post-transcriptional level. This unpublished study seeks to investigate the gene expression profiles of the major genes involved in microRNA biosynthesis in eMSCs isolated from the menstrual flow of women with and without endometriosis. Objective: To evaluate whether the expression of DROSHA, DGCR8, XPO5, DICER and AGO1-4 genes is differentially expressed in endometriosis. Study Design: Cross-sectional comparison between eMSCs isolated from the menstrual flow of women with and without endometriosis. Methods: Menstrual flow eMSC from women with (n = 10) and without endometriosis (n = 10) were previously isolated and characterized by the group (PROCESS FAPESP: 2013 / 22431-3) and are stored in a biorepository (Process HCRP 15227 /2012). expression (RQ) will be quantified by RT-qPCR using the 2-delta delta Ct method. Then the values will be transformed [(log10RQ) +10] and the statistical analysis will be unpaired parametric T test. (AU)