The Effectiveness of Liquid Biopsy in Differential Diagnosis and Early Screening of Epithelial Ovarian Cancer

Sponsor
Peking Union Medical College Hospital (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT05931055
Collaborator
(none)
1,000
96

Study Details

Study Description

Brief Summary

At present, there is a lack of effective screening methods. It is urgent to explore new non-invasive detection methods for early diagnosis of epithelial ovarian cancer and non-invasive differentiation methods for benign and malignant ovarian tumors.

Liquid biopsy technology has great potential for early screening of tumors. The fragmentation patterns of cfDNA fragments in plasma and the uneven coverage of the genome can indirectly reflect the state of gene expression regulation in vivo. Its characteristics mainly include copy number variation (CNV), Nucleosome footprint, fragment length and motif.

The number of proteins in a proteome can sometimes exceed the number of genomes. It includes "structural Proteomics" and "functional Proteomics". At present, research has explored the use of urinary protein biomarkers for early diagnosis of gastric cancer. "Deep Visual Proteomics (DVP)" reveals the mechanism driving tumor evolution and new therapeutic targets for tumors.

Using the currently mature low depth WGS sequencing technology, this study aims to explore its clinical application in the differentiation and early screening of epithelial ovarian cancer, as well as monitoring the course of epithelial ovarian cancer, including the detection of minimal residual lesions (MRD) and monitoring of recurrence (MOR). This study also explores the role of urine proteomics in the differentiation of benign and malignant ovarian tumors, early screening and invasiveness of epithelial ovarian cancer, and monitoring the course of epithelial ovarian cancer.

Condition or Disease Intervention/Treatment Phase
  • Diagnostic Test: Fragmentomics

Detailed Description

At present, there is a lack of effective screening methods. Numerous studies and practices have shown that tumor screening and early diagnosis and treatment can effectively prolong the overall survival period of cancer patients and reduce the economic burden of the disease. The traditional early screening methods for tumors in clinical practice, including imaging screening, endoscopic screening, and tumor marker screening, generally have defects such as strong invasiveness, significant discomfort during the screening process, low accuracy (false negative, false positive), and poor compliance. Therefore, it is urgent to explore new non-invasive detection methods for early diagnosis of epithelial ovarian cancer and non-invasive differentiation methods for benign and malignant ovarian tumors.

Liquid biopsy technology, as a non-invasive new detection technology, has great potential for early screening of tumors. CfDNA is an important marker for liquid biopsy and has been widely used in non-invasive prenatal examinations and cancer liquid biopsy research. The fragmentation patterns of cfDNA fragments in plasma and the uneven coverage of the genome can indirectly reflect the state of gene expression regulation in vivo. Its characteristics mainly include copy number variation (CNV), Nucleosome footprint, fragment length and motif.

Proteome changes with different tissue and even environmental states. During transcription, a gene can be spliced in multiple mRNA forms, and a proteome is not a direct product of a genome. The number of proteins in a proteome can sometimes exceed the number of genomes. It includes "structural Proteomics" and "functional Proteomics". The former is mainly the study of protein expression models, including protein amino acid sequence, analysis and spatial structure analysis, type analysis and quantity determination; The latter mainly focuses on the study of protein functional patterns, including protein function and protein-protein interactions. At present, research has explored the use of urinary protein biomarkers for early diagnosis of gastric cancer. "Deep Visual Proteomics (DVP)" reveals the mechanism driving tumor evolution and new therapeutic targets for tumors.

There is ample evidence to support the diagnostic value of fragment omics research in tumors. Using the currently mature low depth WGS sequencing technology, this study aims to explore its clinical application in the differentiation and early screening of epithelial ovarian cancer, as well as monitoring the course of epithelial ovarian cancer, including the detection of minimal residual lesions (MRD) and monitoring of recurrence (MOR). In addition, there is currently no research on the use of urine proteomics in the differentiation and early screening of ovarian cancer. This study also explores the role of urine proteomics in the differentiation of benign and malignant ovarian tumors, early screening and invasiveness of epithelial ovarian cancer, and monitoring the course of epithelial ovarian cancer.

Study Design

Study Type:
Observational
Anticipated Enrollment :
1000 participants
Observational Model:
Case-Control
Time Perspective:
Prospective
Official Title:
The Effectiveness of Liquid Biopsy in Differential Diagnosis of Benign and Malignant Ovarian Tumors and Early Screening of Epithelial Ovarian Cancer, and the Exploration of Invasive Mechanisms of Epithelial Ovarian Cancer
Anticipated Study Start Date :
Jan 1, 2024
Anticipated Primary Completion Date :
Jan 1, 2029
Anticipated Study Completion Date :
Jan 1, 2032

Arms and Interventions

Arm Intervention/Treatment
ovarian cancer group

patients confirmed with ovarian cancer

Diagnostic Test: Fragmentomics
The fragmentation patterns of cfDNA fragments in plasma and the uneven coverage of the genome can indirectly reflect the state of gene expression regulation in vivo. Its characteristics mainly include copy number variation (CNV), Nucleosome footprint, fragment length and motif. Fragomics relies on WGS (Whole Genome Sequencing), and the target covers the whole Genomics level. Thus, the cfDNA Fragmentomics testing can help differentiation and early diagnosis.

ovarian cyst group

patients confirmed with benign ovarian csyt

Diagnostic Test: Fragmentomics
The fragmentation patterns of cfDNA fragments in plasma and the uneven coverage of the genome can indirectly reflect the state of gene expression regulation in vivo. Its characteristics mainly include copy number variation (CNV), Nucleosome footprint, fragment length and motif. Fragomics relies on WGS (Whole Genome Sequencing), and the target covers the whole Genomics level. Thus, the cfDNA Fragmentomics testing can help differentiation and early diagnosis.

Outcome Measures

Primary Outcome Measures

  1. Copy number variation [3 years follow-up after enrollment or till the end of research]

    Exploring the characteristics of cfDNA copy number variation in patients with epithelial ovarian cancer

  2. Nucleosome Footprint [3 years follow-up after enrollment or till the end of research]

    Exploring the characteristics of cfDNA nucleosome Footprint in patients with epithelial ovarian cancer

  3. Fragment length [3 years follow-up after enrollment or till the end of research]

    Exploring the characteristics of cfDNA fragment length in patients with epithelial ovarian cancer

  4. Motif [3 years follow-up after enrollment or till the end of research]

    Exploring the characteristics of cfDNA motif in patients with epithelial ovarian cancer

Secondary Outcome Measures

  1. Construction and validation a risk prediction model [3 years follow-up after enrollment or till the end of research]

    constructing a risk prediction model based on fragmentomics characteristics and clinical data, for early screening and differential diagnosis of epithelial ovarian cancer, and for monitoring the course of epithelial ovarian cancer patients, including detection of minimal residual lesions (MRD) and monitoring of recurrence (MOR). The fragmentomics characteristics include copy number variation, nucleosome Footprint, fragment length and motif.

  2. urinary proteomics [3 years follow-up after enrollment or till the end of research]

    Exploring the characteristics of urinary proteomics in patients with epithelial ovarian cancer, combined with clinical and pathological data of patients, for early screening and differential diagnosis of epithelial ovarian cancer, and for monitoring the course of epithelial ovarian cancer patients, including detection of minimal residual lesions (MRD) and monitoring of recurrence (MOR). Further exploration of the invasive mechanism of epithelial ovarian cancer using urinary proteomics.

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
Female
Inclusion Criteria:
  1. Age ≥ 18 years old, female;

  2. Suspicious or considering mass in the accessory area, requiring surgical treatment and obtaining pathology of ovarian tissue;

  3. Having pelvic imaging evaluation results, including ultrasound, MRI, CT, or PET/CT;

  4. Serum CA125 and HE4 tests are tested before surgery, and ROMA evaluation results is obtained;

  5. Volunteer to participate in this research and sign an informed consent form; (6) Good compliance and regular follow-up.

Exclusion Criteria:
  1. Patients with confirmed ovarian cancer who have undergone surgery and obtained histopathology;

  2. Patients who have received chemotherapy or pelvic radiation therapy within 6 months prior to sample collection;

  3. Researchers have confirmed patients with recurrent ovarian cancer, or ovarian cancer patients who have received chemotherapy and/or surgical treatment;

  4. Contraindications for surgical evaluation and inability to obtain ovarian pathology or surgical pathological information;

  5. Samples that do not meet the requirements for collecting and storing assessment reagent samples; Or contaminated or suspected contaminated samples;

  6. Samples with missing, incomplete, and untraceable clinical information of corresponding patients;

  7. Pregnant and lactating women;

  8. Patients who cannot cooperate with examinations, have poor compliance, and cannot follow up regularly.

Contacts and Locations

Locations

No locations specified.

Sponsors and Collaborators

  • Peking Union Medical College Hospital

Investigators

  • Principal Investigator: Lei Li, doctor, Peking Union Medical College Hospital

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Peking Union Medical College Hospital
ClinicalTrials.gov Identifier:
NCT05931055
Other Study ID Numbers:
  • K4059
First Posted:
Jul 5, 2023
Last Update Posted:
Jul 5, 2023
Last Verified:
Jun 1, 2023
Individual Participant Data (IPD) Sharing Statement:
Undecided
Plan to Share IPD:
Undecided
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Jul 5, 2023