Wei-Ping Hu1, Sun Kuie Tay, Yi Zhao. 1. Department of Obstetrics and Gynecology, Singapore General Hospital, Outram Road, Singapore 169608.
Abstract
CONTEXT: The etiology and molecular pathogenesis of endometriosis, a prevalent estrogen-dependent gynecologic disease, are poorly understood. OBJECTIVE: The objective of the study was to identify the differentially expressed genes between autologous ectopic and eutopic endometrium. DESIGN: Subtractive hybridization was used for a genome-wide search for differentially expressed genes between autologous ectopic and eutopic endometrium. Real-time RT-PCR was used for gene expression profiling in the paired tissue samples taken from multiple subjects. PATIENTS: The paired pelvic endometriosis and uterine endometrium tissue biopsies were procured from 15 patients undergoing laparoscopy or hysterectomy for endometriosis. RESULTS: Seventy-eight candidate genes were identified from the subtractive cDNA libraries. Seventy-six of these genes were investigated in approximately 8000 real-time PCR for their differential expression in 30 paired tissue biopsies from 15 patients affected by endometriosis. Cluster analysis on gene expression revealed highly consistent profiles in two groups of genes, despite the clinical heterogeneity of the 15 cases. Thirty-four genes specific to early disease point to their potential roles in establishment and evolution of endometriosis. Most interestingly, 14 genes were consistently dysregulated in the paired samples from the majority of the patients. Of these, there were two uncharacterized transcripts and two novel genes, and 10 were matched to known genes: IGFBP5, PIM2, RPL41, PSAP, FBLN1, SIPL, DLX5, HSD11B2, SET, and RHOE. CONCLUSIONS: Dysregulation of 14 genes was found to be overtly associated with endometriosis. Some of these genes, known to participate in estrogen activities and antiapoptosis, may play a role in the pathogenesis of endometriosis and may represent potential diagnostic markers or therapeutic targets for endometriosis.
CONTEXT: The etiology and molecular pathogenesis of endometriosis, a prevalent estrogen-dependent gynecologic disease, are poorly understood. OBJECTIVE: The objective of the study was to identify the differentially expressed genes between autologous ectopic and eutopic endometrium. DESIGN: Subtractive hybridization was used for a genome-wide search for differentially expressed genes between autologous ectopic and eutopic endometrium. Real-time RT-PCR was used for gene expression profiling in the paired tissue samples taken from multiple subjects. PATIENTS: The paired pelvic endometriosis and uterine endometrium tissue biopsies were procured from 15 patients undergoing laparoscopy or hysterectomy for endometriosis. RESULTS: Seventy-eight candidate genes were identified from the subtractive cDNA libraries. Seventy-six of these genes were investigated in approximately 8000 real-time PCR for their differential expression in 30 paired tissue biopsies from 15 patients affected by endometriosis. Cluster analysis on gene expression revealed highly consistent profiles in two groups of genes, despite the clinical heterogeneity of the 15 cases. Thirty-four genes specific to early disease point to their potential roles in establishment and evolution of endometriosis. Most interestingly, 14 genes were consistently dysregulated in the paired samples from the majority of the patients. Of these, there were two uncharacterized transcripts and two novel genes, and 10 were matched to known genes: IGFBP5, PIM2, RPL41, PSAP, FBLN1, SIPL, DLX5, HSD11B2, SET, and RHOE. CONCLUSIONS: Dysregulation of 14 genes was found to be overtly associated with endometriosis. Some of these genes, known to participate in estrogen activities and antiapoptosis, may play a role in the pathogenesis of endometriosis and may represent potential diagnostic markers or therapeutic targets for endometriosis.
Authors: Hien Tt Luong; Jodie N Painter; Konstantin Shakhbazov; Brett Chapman; Anjali K Henders; Joseph E Powell; Dale R Nyholt; Grant W Montgomery Journal: Int J Mol Epidemiol Genet Date: 2013-11-28
Authors: Alysson Zanatta; André M Rocha; Filomena M Carvalho; Ricardo M A Pereira; Hugh S Taylor; Eduardo L A Motta; Edmund C Baracat; Paulo C Serafini Journal: J Assist Reprod Genet Date: 2010-09-07 Impact factor: 3.412
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