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

Observational Ovarian Cancer Differentiating Diagnosis

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Fragmentomics.
Who it may be relevant to
Registry conditions: Ovarian Cancer, Differentiating, Diagnosis. Basic parameters: from 18 years · Female.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Center list to be confirmed — check the primary protocol.
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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

Overview

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.

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.

Interventions

  • 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.

Primary outcome measures

  • Copy number variation [Time frame: 3 years follow-up after enrollment or till the end of research]
  • Nucleosome Footprint [Time frame: 3 years follow-up after enrollment or till the end of research]
  • Fragment length [Time frame: 3 years follow-up after enrollment or till the end of research]
  • Motif [Time frame: 3 years follow-up after enrollment or till the end of research]
Secondary outcome measures (2)
  • Construction and validation a risk prediction model [Time frame: 3 years follow-up after enrollment or till the end of research]
  • urinary proteomics [Time frame: 3 years follow-up after enrollment or till the end of research]

Eligibility criteria

Inclusion criteria

  • Age ≥ 18 years old, female;
  • Suspicious or considering mass in the accessory area, requiring surgical treatment and obtaining pathology of ovarian tissue;
  • Having pelvic imaging evaluation results, including ultrasound, MRI, CT, or PET/CT;
  • Serum CA125 and HE4 tests are tested before surgery, and ROMA evaluation results is obtained;
  • Volunteer to participate in this research and sign an informed consent form; (6) Good compliance and regular follow-up.

Exclusion criteria

  • Patients with confirmed ovarian cancer who have undergone surgery and obtained histopathology;
  • Patients who have received chemotherapy or pelvic radiation therapy within 6 months prior to sample collection;
  • Researchers have confirmed patients with recurrent ovarian cancer, or ovarian cancer patients who have received chemotherapy and/or surgical treatment;
  • Contraindications for surgical evaluation and inability to obtain ovarian pathology or surgical pathological information;
  • Samples that do not meet the requirements for collecting and storing assessment reagent samples; Or contaminated or suspected contaminated samples;
  • Samples with missing, incomplete, and untraceable clinical information of corresponding patients;
  • Pregnant and lactating women;
  • Patients who cannot cooperate with examinations, have poor compliance, and cannot follow up regularly.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Study design

Observational model
Case-control

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT05931055 · K4059

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗