Overview
Endometrial cancer is one of the most common gynecological malignancies, and its incidence is rising. Currently, there is a lack of highly effective and non-invasive screening methods. Liquid biopsy, which analyzes cell-free DNA (cfDNA) in the blood, has emerged as a promising approach for early cancer detection. This observational study aims to develop and evaluate a non-invasive blood test to screen for early-stage endometrial cancer and to distinguish between benign and malignant endometrial lesions.
This study plans to enroll 512 female participants, divided into three groups: 216 patients with stage I-IV endometrial cancer, 80 patients with atypical endometrial hyperplasia (a precancerous condition), and 216 healthy controls. We will collect peripheral blood samples from all participants and perform low-pass whole-genome sequencing (WGS) on the extracted plasma cfDNA. By analyzing specific DNA features (such as DNA fragment patterns, end motifs, and copy number variations) and using artificial intelligence (machine learning), we will build a predictive model. This study hopes to establish a more effective, non-invasive early screening strategy to improve the clinical diagnosis of endometrial cancer in the Chinese population.
Description
Background and Objective:
Current clinical screening methods for endometrial cancer, such as transvaginal ultrasound and endometrial biopsy, have limitations including invasiveness and subjectivity. Recent advances in plasma DNA fragmentomics have shown great potential in oncology. This study aims to systematically evaluate the accuracy and specificity of a multi-omics cfDNA model based on whole-genome sequencing (WGS) for the risk prediction of endometrial cancer, and to assess its ability to differentiate between benign and malignant endometrial lesions.
Study Design and Participants:
This is an observational, case-control study. A total of 512 female subjects will be prospectively enrolled and divided into three cohorts:
Cohort A: 216 patients with histologically confirmed stage I-IV endometrial cancer.
Cohort B: 80 patients with atypical endometrial hyperplasia.
Cohort C: 216 age-matched healthy controls with no evidence of tumors.
Sample Collection and Sequencing:
Peripheral blood samples (8-10 mL) will be collected from all participants using EDTA tubes prior to any anti-tumor treatment. Plasma will be separated within 2 hours of collection. Cell-free DNA (cfDNA) will be extracted from the plasma, and low-pass whole-genome sequencing (WGS) will be performed using the MGI high-throughput sequencing platform. Strict quality control will be applied throughout the sample processing and sequencing stages.
Bioinformatics and Modeling:
High-quality sequencing data will be analyzed to extract comprehensive multi-dimensional cfDNA features, including:
Genomic copy number variations (CNV).
cfDNA fragment size ratios (short/long).
cfDNA fragment size distribution.
cfDNA fragment end motifs.
cfDNA fragment breakpoint motifs.
Using artificial intelligence and machine learning algorithms (such as generalized linear models, deep learning, random forest, and extreme gradient boosting), a multi-omics predictive model will be constructed and validated. The ultimate goal is to establish a highly sensitive, specific, and cost-effective non-invasive early screening model for endometrial cancer in regional Chinese populations.
Eligibility
Inclusion Criteria:
- Female, aged \> 18 years.
Participants fully understand the study requirements and sign the written informed consent.
Cohort A (Endometrial Cancer): Patients with histologically and/or cytologically confirmed stage I-IV endometrial cancer; comprehensive clinical and pathological information is available.
Cohort B (Atypical Hyperplasia): Patients diagnosed with atypical endometrial hyperplasia; comprehensive clinical and pathological information is available.
Cohort C (Healthy Control): Healthy female subjects with no tumors or suspicious nodules confirmed by systematic examination.
Exclusion Criteria:
- Pregnant women.
Current diagnosis of tumors other than endometrial cancer or a history of previous tumors.
Received any form of tumor treatment prior to blood draw, including surgery, radiotherapy/chemotherapy, endocrine therapy, targeted therapy, or immunotherapy.
Current febrile illness, or acute/inflammatory disease requiring internal medical treatment within 14 days prior to blood draw.
Organ transplant recipients or previous recipients of allogeneic bone marrow or stem cell transplants.
Poor health status or unsuitable for blood draw.
Any other clinically significant disease or condition that, in the investigator's opinion, may affect protocol compliance, affect the subject's ability to sign informed consent, or make the subject unsuitable for this clinical study.
