Dataset Information

Differentially expressed genes in HEECs of eutopic endometrium of patients with endometriosis compared with control

ABSTRACT: The pathogenesis of endometriosis may result from aberrant angiogenesis that occurs in eutopic endometrium with retrograde menstruation. The difference in gene expression profile between human endometrial endothelial cells (HEECs) from eutopic endometria of patients with and without endometriosis would be determinant that affects the occurrence of endometriosis. To explore this kind of difference, we performed in vitro culture and identified their endothelial origin, as well as observed growth features of HEECs from the two different origins. Finally we identified the difference in gene expression profile when combined suppression subtractive hybridization(SSH) with genechip and confirmed the results by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The HEECs derived from endometriosis exhibited potent survival ability in vitro compared to that from non-endometriosis. We found that gremlin and fibronectin genes were up-regulated in HEECs derived from eutopic endometrium of patients with endometriosis when compared with that from patients without endometriosis. Our study implies that enhanced angiogenic capacity of eutopic HEECs may be an independent determinant in endometriotic aberrant angiogenesis in addition to the interaction of exfoliated endometrium and peritoneal environment elements such as activated macrophages and soluble cytokines. Keywords: human endometrial endothelial cells (HEECs),endometriosis,differentially expressed genes

ORGANISM(S): Homo sapiens

PROVIDER: GSE7846 | GEO | 2007/10/31

SECONDARY ACCESSION(S): PRJNA99977

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Endometriosis is associated with aberrant gene expression in the eutopic endometrium of women with disease. To determine if the development of endometriotic lesions directly impacts eutopic endometrial gene expression, we sequentially analyzed the eutopic endometrium across the time course of disease progression in a baboon model of induced disease. Endometriosis was induced in baboons by intraperitoneal inoculation of autologous menstrual endometrium. Eutopic endometria were collected at 9-11 days postovulation) in five time points: 1, 3, 6-7, 10-12, and 15-16 months after disease induction and compared with tissue from disease-free baboons. We used microarrays to identify differentially expressed genes between time points. Sequential analysis of the same animals during disease progression demonstrated an early disease insult and a transitory dominance of an estrogenic phenotype. However, as the disease progressed, a progesterone-resistant phenotype became evident. Endometriosis was experimentally induced in Papio anubis female baboons (n = 4) by intraperitoneal inoculation with menstrual endometrium on two consecutive menstrual cycles. Baboons with spontaneous endometriosis (n = 2) were also included in this study with an unknown duration of disease. Control endometrium was similarly harvested from animals (n = 4) with no previous surgeries and with no visible disease. The progression of disease was monitored in each animal by consecutive laparoscopies and video recording at 1 (n = 2), 3 (n = 4), 6-7 (n = 4), 10-12, (n = 4), and 15-16 (n = 3) months after inoculation during a window of 9-11 days postovulation. Eutopic endometrial tissues were harvested and were snap frozen in liquid nitrogen for RNA extraction. Additionally, menstrual endometrium was harvested on Days 1-2 of menses using a Unimar Pipelle (Cooper Surgical Inc., Shelton, CT) immediately prior to laparoscopy. Blood samples were collected daily from days 7 through 16 postmenstruation of menstrual cycles.

Dataset Information

Differentially expressed genes in HEECs of eutopic endometrium of patients with endometriosis compared with control

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets