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RecruitingNCT07892755Updated Oct 23, 2026

Liquid Biopsy-Based Early Screening for Endometrial Cancer in Regional Chinese Populations

An observational study in Endometrial Cancer and Atypical Endometrial Hyperplasia, sponsored by Guizhou Provincial People's Hospital. Recruiting at 1 site in China. Open to female participants aged Up to 18 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-10-23.

Sponsored by Guizhou Provincial People's Hospital · Observational

From the registry’s dates

  • Started Aug 2026; still recruiting 2 months later.
Updated Oct 23, 2026Newly registeredGo to Updates ↓
Study type
Observational
Model
Case-control
Time perspective
Prospective
Enrollment
512
Ages
Up to 18 Years
Sex
Female
01

Study summary

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.

Read the detailed 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.

02

Conditions studied

  • Endometrial Cancer
  • Atypical Endometrial Hyperplasia

Keywords

  • Liquid Biopsy
  • Cell-Free DNA
  • Whole Genome Sequencing
  • Fragmentomics
03

In context

Endometrial Neoplasms

1,347 studies on the registry are indexed under Endometrial Neoplasms; 452 are open to participants now.

This study's planned enrollment of 512 is above the median of 200 across 328 observational studies indexed under Endometrial Neoplasms.

Browse Endometrial Neoplasms studies →

Lead sponsor

Guizhou Provincial People's Hospital is the lead sponsor of 8 studies on the registry; 4 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
Up to 18 Years
Sexes eligible
Female
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

he study includes three cohorts: 216 patients with stage I-IV endometrial cancer, 80 patients with atypical endometrial hyperplasia, and 216 age-matched healthy female controls. All participants are recruited from regional Chinese populations.

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

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

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.

05

Study design

Observational model
Case-control
Time perspective
Prospective
Enrollment
512 participants (estimated)
Patient registry
No

Groups and cohorts

  • Cohort A: Endometrial Cancer

    Patients with histologically and/or cytologically confirmed stage I-IV endometrial cancer. Baseline plasma samples and complete clinical and pathological information will be collected.

  • Cohort B: Atypical Endometrial Hyperplasia

    Patients with atypical endometrial hyperplasia. Baseline plasma samples and complete clinical and pathological information will be collected.

  • Cohort C: Healthy Control

    Healthy female subjects confirmed by systematic examination to have no tumors or suspicious nodules. Age-matched with Cohorts A and B. Baseline plasma samples will be collected.

06

What researchers measure

Primary outcomes

  1. Diagnostic performance (sensitivity and specificity) of the cfDNA fragmentomics model for early screening of endometrial cancer

    Evaluate the accuracy and specificity of a multi-omics cfDNA-based model (incorporating fragmentomics and copy number variation features) in predicting the risk of endometrial cancer.

    Time frame: At baseline (time of blood collection)

Secondary outcomes

  1. Ability of the cfDNA model to differentiate between benign and malignant endometrial lesions

    Evaluate the performance of the cfDNA-based model in distinguishing atypical endometrial hyperplasia (precancerous/benign) from endometrial cancer (malignant).

    Time frame: At baseline (time of blood collection)

07

Study locations

1 of 1 sites recruiting
  • Guizhou Provincial People's Hospital
    Guiyang, Guizhou 550002, China
    Recruiting
08

References and documents

Publications

  • Cristiano S, Leal A, Phallen J, Fiksel J, Adleff V, Bruhm DC, Jensen SO, Medina JE, Hruban C, White JR, Palsgrove DN, Niknafs N, Anagnostou V, Forde P, Naidoo J, Marrone K, Brahmer J, Woodward BD, Husain H, van Rooijen KL, Orntoft MW, Madsen AH, van de Velde CJH, Verheij M, Cats A, Punt CJA, Vink GR, van Grieken NCT, Koopman M, Fijneman RJA, Johansen JS, Nielsen HJ, Meijer GA, Andersen CL, Scharpf RB, Velculescu VE. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature. 2019 Jun;570(7761):385-389. doi: 10.1038/s41586-019-1272-6. Epub 2019 May 29. PubMed 31142840 ↗
  • Liu J, Hu D, Lin Y, Chen X, Yang R, Li L, Zhan Y, Bao H, Zang L, Zhu M, Zhu F, Yan J, Zhu D, Zhang H, Xu B, Xu Q. Early detection of uterine corpus endometrial carcinoma utilizing plasma cfDNA fragmentomics. BMC Med. 2024 Jul 29;22(1):310. doi: 10.1186/s12916-024-03531-8. PubMed 39075419 ↗
  • Rao Q, Zhou H, Weng W, He Y, Li N, He P, Tang W, He M, Zhu X, Zhu D, Bao H, Wu X, Wang H, Lin Z, Zhang B. Early detection, clinicopathological subtyping, and prognosis prediction for endometrial cancer patients using fragmentomics liquid biopsy assay. ESMO Open. 2025 Oct;10(10):105770. doi: 10.1016/j.esmoop.2025.105770. Epub 2025 Sep 24. PubMed 40992272 ↗

Individual participant data

Plan to share: No

09

Updates

1 registry update since Sep 25, 2026
Registered
First appeared on the registry. No changes since
Oct 23, 2026
Show all 1 update
  1. Oct 23, 2026
    First appeared on the registry

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07892755
Lead sponsor
Guizhou Provincial People's Hospital
Collaborators
Nanjing Geneseeq Technology Inc.
Responsible party
Sponsor
First posted
Oct 23, 2026
Start date
Aug 10, 2026
Primary completion
Aug 9, 2027 (estimated)
Completion
Dec 2027 (estimated)
Last update
Oct 23, 2026

Study contacts

Yong Li, MD
Contact
liyong7229771@163.com
+8613628566285
Yong Li, MD
principal investigator · Guizhou Provincial People's Hospital

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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