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Plasma ctDNA Detection in Diagnosis of Epithelial Ovarian Cancer.

NCT ID: NCT03155451

Last Updated: 2017-10-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

43 participants

Study Classification

OBSERVATIONAL

Study Start Date

2017-08-14

Study Completion Date

2017-10-18

Brief Summary

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Epithelial ovarian cancer constitutes one of the most common gynecological malignancies.Because the ovaries lie in the deep pelvic cavity,most ovarian cancer patients are asymptomatic, rendering the majority often diagnosed at an advanced stage.ctDNA in cancer patients often bears similar genetic and epigenetic features to the related tumor DNA.This study aims to detect plasma ctDNA in Diagnosis of Epithelial Ovarian Cancer.

Detailed Description

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Epithelial ovarian cancer constitutes one of the most common gynecological malignancies, with an incidence rate of 3-12/100 000 woman per year. Because the ovaries lie in the deep pelvic cavity,most ovarian cancer patients are asymptomatic, rendering the majority often diagnosed at an advanced stage. Liquid biopsy, which is meant to detect cancers by sequencing the DNA in a few drops of a person's blood. It may detect cancers early, even before symptoms arise, when there is just a few cells in the blood circulation.

ctDNA in cancer patients often bears similar genetic and epigenetic features to the related tumor DNA. There is evidence that some of the ctDNA originates from tumor tissue. This, and the fact that ctDNA can easily be isolated from the circulation and other body fluids of patients, makes it a promising candidate as a non-invasive biomarker of cancer.

This study aims to detect plasma ctDNA in Diagnosis of Epithelial Ovarian Cancer.

Conditions

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Epithelial Ovarian Cancer

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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Epithelial ovarian cancer

patients receive the ctDNA methylation markers screening

methylation markers screening

Intervention Type DIAGNOSTIC_TEST

ctDNA extraction from plasma samples;bisulfite-treated DNA;DNA methylation levels by deep sequencing-Sequencing; data analysis

Interventions

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methylation markers screening

ctDNA extraction from plasma samples;bisulfite-treated DNA;DNA methylation levels by deep sequencing-Sequencing; data analysis

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* people aged 18years to 80years;
* Diagnosis of ovarian cancer is confirmed by two Pathologists independently;
* Pregnancy tests are negative.

Exclusion Criteria

* With other type of malignancies;
* someone who refuse to participate the study.
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes

Sponsors

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RenJi Hospital

OTHER

Sponsor Role lead

Responsible Party

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Wang Yu

M.D.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Yu Wang, M.D.

Role: PRINCIPAL_INVESTIGATOR

Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University

Locations

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Renji Hospital, School of Medicine, Shanghai Jiao Tong University

Shanghai, Shanghai Municipality, China

Site Status

Countries

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China

References

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Wen L, Li J, Guo H, Liu X, Zheng S, Zhang D, Zhu W, Qu J, Guo L, Du D, Jin X, Zhang Y, Gao Y, Shen J, Ge H, Tang F, Huang Y, Peng J. Genome-scale detection of hypermethylated CpG islands in circulating cell-free DNA of hepatocellular carcinoma patients. Cell Res. 2015 Nov;25(11):1250-64. doi: 10.1038/cr.2015.126. Epub 2015 Oct 30.

Reference Type BACKGROUND
PMID: 26516143 (View on PubMed)

Nick AM, Coleman RL, Ramirez PT, Sood AK. A framework for a personalized surgical approach to ovarian cancer. Nat Rev Clin Oncol. 2015 Apr;12(4):239-45. doi: 10.1038/nrclinonc.2015.26. Epub 2015 Feb 24.

Reference Type BACKGROUND
PMID: 25707631 (View on PubMed)

Other Identifiers

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[2017]012

Identifier Type: -

Identifier Source: org_study_id