Swati Suryawanshi 1 , Anda M Vlad , Hui-Min Lin , Gina Mantia-Smaldone , Robin Laskey , Minjae Lee , Yan Lin , Nicole Donnellan , Marcia Klein-Patel , Ted Lee , Suketu Mansuria , Esther Elishaev , Raluca Budiu , Robert P Edwards , Xin Huang Show Affiliations »
Abstract
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PURPOSE: Endometriosis, a largely benign, chronic inflammatory disease, is an independent risk factor for endometrioid and clear cell epithelial ovarian tumors. We aimed to identify plasma miRNAs that can be used to differentiate patients with endometriosis and ovarian cancer from healthy individuals . EXPERIMENTAL DESIGN: We conducted a two-stage exploratory study to investigate the use of plasma miRNA profiling to differentiate between patients with endometriosis, patients with endometriosis-associated ovarian cancer (EAOC), and healthy individuals . In the first stage, using global profiling of more than 1,000 miRNAs via reverse transcriptase quantitative PCR (RT-qPCR ) in a 20-patient initial screening cohort, we identified 23 candidate miRNAs, which are differentially expressed between healthy controls (n = 6), patients with endometriosis (n = 7), and patients with EAOC (n = 7) based on the fold changes. In the second stage, the 23 miRNAs were further tested in an expanded cohort (n = 88) of healthy individuals (n = 20), endometriosis (n = 33), EAOC (n = 14), and serous ovarian cancer cases (SOC; n = 21, included as controls ). RESULTS: We identified three distinct miRNA signatures with reliable differential expression between healthy individuals, patients with endometriosis, and patients with EAOC . When profiled against the control SOC category, our results revealed different miRNAs, suggesting that the identified signatures are reflective of disease-specific pathogenic mechanisms. This was further supported by the fact that the majority of miRNAs differentially expressed in human EAOCs were mirrored in a double transgenic mouse EAOC model. CONCLUSION: Our study reports for the first time that distinct plasma miRNA expression patterns may serve as highly specific and sensitive diagnostic biomarkers to discriminate between healthy, endometriosis, and EAOC cases. ©2013 AACR.
RCT Entities: Population
Interventions
Outcomes
PURPOSE: Endometriosis , a largely benign, chronic inflammatory disease , is an independent risk factor for endometrioid and clear cell epithelial ovarian tumors . We aimed to identify plasma miRNAs that can be used to differentiate patients with endometriosis and ovarian cancer from healthy individuals. EXPERIMENTAL DESIGN: We conducted a two-stage exploratory study to investigate the use of plasma miRNA profiling to differentiate between patients with endometriosis , patients with endometriosis-associated ovarian cancer (EAOC), and healthy individuals. In the first stage, using global profiling of more than 1,000 miRNAs via reverse transcriptase quantitative PCR (RT-qPCR) in a 20-patient initial screening cohort, we identified 23 candidate miRNAs, which are differentially expressed between healthy controls (n = 6), patients with endometriosis (n = 7), and patients with EAOC (n = 7) based on the fold changes. In the second stage, the 23 miRNAs were further tested in an expanded cohort (n = 88) of healthy individuals (n = 20), endometriosis (n = 33), EAOC (n = 14), and serous ovarian cancer cases (SOC; n = 21, included as controls). RESULTS: We identified three distinct miRNA signatures with reliable differential expression between healthy individuals, patients with endometriosis , and patients with EAOC. When profiled against the control SOC category, our results revealed different miRNAs, suggesting that the identified signatures are reflective of disease-specific pathogenic mechanisms. This was further supported by the fact that the majority of miRNAs differentially expressed in human EAOCs were mirrored in a double transgenic mouse EAOC model. CONCLUSION: Our study reports for the first time that distinct plasma miRNA expression patterns may serve as highly specific and sensitive diagnostic biomarkers to discriminate between healthy, endometriosis , and EAOC cases. ©2013 AACR.
Entities: Chemical
Disease
Gene
Mutation
Species
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Year: 2013
PMID： 23362326 PMCID： PMC3596045 DOI： 10.1158/1078-0432.CCR-12-2726
Source DB: PubMed Journal: Clin Cancer Res ISSN： 1078-0432 Impact factor: 12.531