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

Ovarian Cancer Clinical Trial

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

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05931055
• Other study ID #: K4059
• Status: Not yet recruiting
• Start date: January 1, 2024
• Est. completion date: January 1, 2032

Study information

• Verified date: June 2023
• Source: Peking Union Medical College Hospital
• Contact: Lei Li, doctor
• Phone: +86 13911988831
• Email: lileigh[@]163.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 1000
• Est. completion date: January 1, 2032
• Est. primary completion date: January 1, 2029
• Gender: Female
• Age group: 18 Years and older

Eligibility

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.

Related Conditions & MeSH terms

• Carcinoma, Ovarian Epithelial
• Diagnosis
• Disease
• Ovarian Cancer
• Ovarian Neoplasms

Intervention

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.

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Peking Union Medical College Hospital

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Copy number variation	Exploring the characteristics of cfDNA copy number variation in patients with epithelial ovarian cancer	3 years follow-up after enrollment or till the end of research
Primary	Nucleosome Footprint	Exploring the characteristics of cfDNA nucleosome Footprint in patients with epithelial ovarian cancer	3 years follow-up after enrollment or till the end of research
Primary	Fragment length	Exploring the characteristics of cfDNA fragment length in patients with epithelial ovarian cancer	3 years follow-up after enrollment or till the end of research
Primary	Motif	Exploring the characteristics of cfDNA motif in patients with epithelial ovarian cancer	3 years follow-up after enrollment or till the end of research
Secondary	Construction and validation a risk prediction model	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.	3 years follow-up after enrollment or till the end of research
Secondary	urinary proteomics	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.	3 years follow-up after enrollment or till the end of research