A Cohort Study of Hereditary Ovarian Cancer Risk Prediction Models and Pathogenesis Exploration

NCT ID: NCT06564428

Last Updated: 2025-06-18

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 1000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-01-01
• Study Completion Date: 2026-12-31

Brief Summary

The aim of this project is to establish a bidirectional multicenter cohort of hereditary ovarian cancer and to describe the clinicopathologic features of hereditary ovarian cancer patients in our country. The risk prediction model of ovarian cancer for Chinese was established by following-up analysis of clinical and pathological information, genetic test results and detailed family history, to predict the risk of cancer in first-degree relatives of carriers of pathogenic/suspected pathogenic mutations, and to guide the intervention management of high-risk population of cancer.

The study will identify novel tumor-causing mutations/predisposing genes by gene sequencing in a special family with hereditary tumor.

Detailed Description

About 10%-20% of ovarian cancers have familial aggregation, suggesting that it may be hereditary ovarian cancer. Exploring a genetic ovarian cancer risk prediction model suitable for Chinese people will help quantify the risk of cancer in high risk groups and guide preventive interventions. The clinicopathology, gene mutation and family history of hereditary ovarian cancer need to be deeply analyzed, and the relevant research is still in the initial stage in China. At the same time, in a small number of ovarian cancer families with obvious familial aggregation, genetic testing failed to detect known pathogenic/possible pathogenic mutations in the germ line, suggesting that there may be a new pathogenic mechanism that needs further study.

Based on the above clinical issues, this project intends to establish a prospective multicenter cohort of hereditary ovarian cancer. To describe the clinicopathological and genetic mutation characteristics of hereditary ovarian cancer patients in China, and guide the individualized diagnosis and treatment of patients. Through follow-up analysis of clinicopathological information, gene mutation characteristics, detailed family history and other factors, a suitable ovarian cancer risk prediction model was established and preliminarily verified to guide the intervention management of high-risk groups. Special genetic ovarian cancer families or early-onset ovarian cancer cases were collected, and new tumor-causing mutations/susceptibility genes were explored through gene sequencing analysis, and functional verification and preliminary mechanism studies were conducted.

Relying on the National Clinical Research Center for Obstetrics and Gynecology, the research team has been engaged in the clinical diagnosis, treatment and scientific research of gynecological malignant tumors for a long time. In China, the gynecological tumor genetic consultation clinic was established earlier, and there are mature platforms for diagnosis, treatment and genetic blocking of hereditary ovarian cancer. Our research group has initially established a genetic ovarian cancer cohort in our hospital, which has included more than 1000 cases of patients with epithelial ovarian cancer and their families who have received surgical treatment in our hospital since 2016. In September 2022, it led the establishment of a multi-center gynecological tumor genetic diagnosis and treatment platform, with 11 sub-centers across the country working together to focus on the diagnosis, treatment and research of hereditary gynecological tumors.

The development of this project will establish the ovarian cancer risk prediction model suitable for Chinese people for the first time, and guide the prevention and intervention of high-risk groups. Through special genetic ovarian cancer family mining, to explore the new pathogenic mechanism of ovarian cancer, to guide the early diagnosis of hereditary ovarian cancer; At the same time, it will promote the individualized and accurate diagnosis and treatment of hereditary ovarian cancer patients.

Conditions

Ovarian Neoplasms

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Mutation carriers

Patients presented to our hospital with a definite pathological diagnosis of epithelial ovarian cancer, who carry suspective gene mutations or have family history of cancer.

Suspective gene mutations and family history

Intervention Type: GENETIC

To observe if the patients with suspective gene mutations or family history take higher risk of suffering from ovarian cancer.

Control group

Patients presented to our hospital with a definite pathological diagnosis of epithelial ovarian cancer, who don't carry any suspective gene mutations and have no family history of any type of cancer.

No interventions assigned to this group

Interventions

Suspective gene mutations and family history

To observe if the patients with suspective gene mutations or family history take higher risk of suffering from ovarian cancer.

Intervention Type: GENETIC

Eligibility Criteria

Inclusion Criteria

• Epithelial ovarian cancer
• ≥18 years
• The pathological diagnosis was clear
• The genetic test showed germ line pathogenic/suspected pathogenic mutations (for mutation interpretation, refer to the American ACMG Classification Standards and Guidelines for Genetic Variation)

Exclusion Criteria

• Non-epithelial ovarian cancer was confirmed by pathology
• No genetic test has been performed

• Minimum Eligible Age: 18 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

Peking University Third Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Hongyan Guo, Doctor

Role: PRINCIPAL_INVESTIGATOR

Peking University Third Hospital

Locations

Peking University Third Hospital

Beijing, Beijing Municipality, China

Site Status: RECRUITING

Countries

China

Central Contacts

Yuan Li, Doctor

Role: CONTACT

yuanli@bimu.edu.cn

18610689868

Facility Contacts

Yuan Li, Doctor

Role: primary

yuanli@bimu.edu.cn

18610689868

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Document Type: Study Protocol, Statistical Analysis Plan, and Informed Consent Form

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Identifier Source: org_study_id