EV-Associated miRNAs from Peritoneal Lavage are a Source of Biomarkers in Endometrial Cancer.
ascitic fluid
biomarkers
endometrial cancer
exosomes
extracellular vesicles
liquid biopsy
miRNAs
microRNAs
peritoneal lavage
uterine cancer
Journal
Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829
Informations de publication
Date de publication:
18 Jun 2019
18 Jun 2019
Historique:
received:
29
04
2019
revised:
13
06
2019
accepted:
14
06
2019
entrez:
21
6
2019
pubmed:
21
6
2019
medline:
21
6
2019
Statut:
epublish
Résumé
Endometrial cancer (EC) is the sixth most common cancer in women worldwide and is responsible for more than 89,000 deaths every year. Mortality is associated with presence of poor prognostic factors at diagnosis, i.e., diagnosis at an advanced stage, with a high grade and/or an aggressive histology. Development of novel approaches that would permit us to improve the clinical management of EC patients is an unmet need. In this study, we investigate a novel approach to identify highly sensitive and specific biomarkers of EC using extracellular vesicles (EVs) isolated from the peritoneal lavage of EC patients. EVs of peritoneal lavages of 25 EC patients were isolated and their miRNA content was compared with miRNAs of EVs isolated from the ascitic fluid of 25 control patients. Expression of the EV-associated miRNAs was measured using the Taqman OpenArray technology that allowed us to detect 371 miRNAs. The analysis showed that 114 miRNAs were significantly dysregulated in EC patients, among which eight miRNAs, miRNA-383-5p, miRNA-10b-5p, miRNA-34c-3p, miRNA-449b-5p, miRNA-34c-5p, miRNA-200b-3p, miRNA-2110, and miRNA-34b-3p, demonstrated a classification performance at area under the receiver operating characteristic curve (AUC) values above 0.9. This finding opens an avenue for the use of EV-associated miRNAs of peritoneal lavages as an untapped source of biomarkers for EC.
Identifiants
pubmed: 31216648
pii: cancers11060839
doi: 10.3390/cancers11060839
pmc: PMC6628347
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Generalitat de Catalunya
ID : SLT002/16/00274
Organisme : Generalitat de Catalunya
ID : 2017SGR1661
Organisme : Generalitat de Catalunya
ID : 2017SGR1368
Organisme : CIBERONC
ID : CB16/12/00328
Organisme : CIBERONC
ID : CB16/12/00231
Organisme : Instituto de Salud Carlos III
ID : PIE15/00029
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