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Extracellular vesicle-derived long non-coding RNA as circulating biomarkers for endometriosis

Could extracellular vesicle-derived long non-coding RNA (lncRNA) serve as promising circulating biomarkers for endometriosis? To obtain novel diagnostic markers, 85 patients with endometriosis were enrolled as the endometriosis group and 86 unaffected participants as the control group. RNA sequencin...

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Published in:Reproductive biomedicine online 2022-05, Vol.44 (5), p.923-933
Main Authors: Shan, Shan, Yang, Yeping, Jiang, Jilan, Yang, Bingxin, Yang, Yisai, Sun, Feng, Zhang, Junyu, Lin, Yu, Xu, Hong
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container_title Reproductive biomedicine online
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Zhang, Junyu
Lin, Yu
Xu, Hong
description Could extracellular vesicle-derived long non-coding RNA (lncRNA) serve as promising circulating biomarkers for endometriosis? To obtain novel diagnostic markers, 85 patients with endometriosis were enrolled as the endometriosis group and 86 unaffected participants as the control group. RNA sequencing was performed to identify extracellular vesicle-derived lncRNA that were differentially expressed between women with endometriosis (n = 5) and unaffected participants (n = 6). Messenger RNA and lncRNA sequences of the plasma extracellular vesicles were analysed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. lncRNA expression levels were further validated using quantitative reverse transcriptase polymerase chain reaction. Moreover, receiver operating characteristic curve analysis was performed to determine the diagnostic value of candidate lncRNA. Clinical features were correlated to the expression levels of candidate lncRNA. It was found that 210 lncRNA were significantly dysregulated; among these, expression of LINC01569, RP3-399L15.2, FAM138B and CH507-513H4.6 was significantly decreased, whereas expression of RP11-326N17.2, KLHL7-AS1 and MIR548XHG was increased, in the plasma of patients with endometriosis. Combined expression level of RP3-399L15.2 and CH507-513H4.6 was used to distinguish patients with endometriosis from control participants; the results revealed a sensitivity of 80.00% and specificity of 85.45% at the cut-off point, and an area under the ROC curve of 0.9045. The findings demonstrated the potential of these two lncRNA as diagnostic biomarkers for endometriosis. Moreover, CH507-513H4.6 alone may be useful in detecting early-stage endometriosis lesions. The combination of RP3-399L15.2 and CH507-513H4.6 may be a potential candidate for endometriosis biomarkers.
doi_str_mv 10.1016/j.rbmo.2021.11.019
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To obtain novel diagnostic markers, 85 patients with endometriosis were enrolled as the endometriosis group and 86 unaffected participants as the control group. RNA sequencing was performed to identify extracellular vesicle-derived lncRNA that were differentially expressed between women with endometriosis (n = 5) and unaffected participants (n = 6). Messenger RNA and lncRNA sequences of the plasma extracellular vesicles were analysed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. lncRNA expression levels were further validated using quantitative reverse transcriptase polymerase chain reaction. Moreover, receiver operating characteristic curve analysis was performed to determine the diagnostic value of candidate lncRNA. Clinical features were correlated to the expression levels of candidate lncRNA. It was found that 210 lncRNA were significantly dysregulated; among these, expression of LINC01569, RP3-399L15.2, FAM138B and CH507-513H4.6 was significantly decreased, whereas expression of RP11-326N17.2, KLHL7-AS1 and MIR548XHG was increased, in the plasma of patients with endometriosis. Combined expression level of RP3-399L15.2 and CH507-513H4.6 was used to distinguish patients with endometriosis from control participants; the results revealed a sensitivity of 80.00% and specificity of 85.45% at the cut-off point, and an area under the ROC curve of 0.9045. The findings demonstrated the potential of these two lncRNA as diagnostic biomarkers for endometriosis. Moreover, CH507-513H4.6 alone may be useful in detecting early-stage endometriosis lesions. The combination of RP3-399L15.2 and CH507-513H4.6 may be a potential candidate for endometriosis biomarkers.</description><identifier>ISSN: 1472-6483</identifier><identifier>EISSN: 1472-6491</identifier><identifier>DOI: 10.1016/j.rbmo.2021.11.019</identifier><identifier>PMID: 35341703</identifier><language>eng</language><publisher>Netherlands: Elsevier Ltd</publisher><subject>Biomarker ; Biomarkers ; Diagnosis ; Endometriosis ; Endometriosis - diagnosis ; Endometriosis - genetics ; Endometriosis - metabolism ; Extracellular vesicles ; Extracellular Vesicles - metabolism ; Female ; Humans ; lncRNA ; RNA sequencing ; RNA, Long Noncoding - metabolism ; ROC Curve ; Sequence Analysis, RNA</subject><ispartof>Reproductive biomedicine online, 2022-05, Vol.44 (5), p.923-933</ispartof><rights>2021 The Author(s)</rights><rights>Copyright © 2021 The Author(s). Published by Elsevier Ltd.. 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It was found that 210 lncRNA were significantly dysregulated; among these, expression of LINC01569, RP3-399L15.2, FAM138B and CH507-513H4.6 was significantly decreased, whereas expression of RP11-326N17.2, KLHL7-AS1 and MIR548XHG was increased, in the plasma of patients with endometriosis. Combined expression level of RP3-399L15.2 and CH507-513H4.6 was used to distinguish patients with endometriosis from control participants; the results revealed a sensitivity of 80.00% and specificity of 85.45% at the cut-off point, and an area under the ROC curve of 0.9045. The findings demonstrated the potential of these two lncRNA as diagnostic biomarkers for endometriosis. Moreover, CH507-513H4.6 alone may be useful in detecting early-stage endometriosis lesions. 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subjects Biomarker
Biomarkers
Diagnosis
Endometriosis
Endometriosis - diagnosis
Endometriosis - genetics
Endometriosis - metabolism
Extracellular vesicles
Extracellular Vesicles - metabolism
Female
Humans
lncRNA
RNA sequencing
RNA, Long Noncoding - metabolism
ROC Curve
Sequence Analysis, RNA
title Extracellular vesicle-derived long non-coding RNA as circulating biomarkers for endometriosis
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