A Single-arm, Prospective, Multi-center Cohort Study Based on Deep Learning-based cfDNA Fragment Omics to Verify the TuFEst Model for the Staging Diagnosis of Breast Cancer Lesions and Lymph Nodes

NCT07304934 | Not Yet Recruiting DMC

• 1 other identifier: 2025-1028
• Study Type: observational
• Target: 269
• Locations: 0 countries
• Sites: N/A

Brief Summary

Through the research of this project, we expect to achieve the cfDNA fragment omics liquid biopsy technology based on deep learning, verify the accuracy of the TuFEst model in predicting the tumor burden status of breast cancer lesions and lymph nodes in newly diagnosed breast cancer patients and those receiving neoadjuvant therapy, and provide a theoretical basis for large-scale clinical application in the future

Conditions

Breast Cancer

Keywords

breast cancer; cfDNA; TuFEst model

Outcome Measures

Primary Outcomes (1)

• Negative predictive value (NPV) of the TuFEst-based classifier for predicting pathologic node-negative status (pN0)

  Validate the accuracy of the TuFEst model in predicting breast cancer lesion and lymph node tumor burden status among patients with primary breast cancer and those undergoing neoadjuvant therapy.

  up to 2 weeks

Study Arms (2)

1

Breast cancer patients who have undergone radical surgery and have not received neoadjuvant therapy

Other: No Intervention: Observational Cohort

2

Patients with newly diagnosed invasive breast cancer and confirmed axillary lymph node metastasis, who are willing to undergo radical surgery after treatment (Exploratory Analysis Cohort)

Other: No Intervention: Observational Cohort

Interventions

No Intervention: Observational Cohort OTHER

No Intervention: Observational Cohort

1; 2

Eligibility Criteria

• Age: 18 Years - 70 Years
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients who have been treated at the Second Affiliated Hospital of Zhejiang University School of Medicine (Other Centers) from the date of ethical approval until December 31, 2027

You may qualify if:

• Patients aged 18 to 70;
• Direct Surgery Group (Cohort 1) : Radical surgery was performed without neoadjuvant therapy;
• Neoadjuvant therapy group (Cohort 2) : The initial diagnosis was invasive breast cancer with confirmed axillary lymph node metastasis, and the patient was willing to undergo radical surgery at the end of treatment;
• Plasma from patients during treatment can be obtained;
• Be willing to sign the informed consent form. -

You may not qualify if:

• Be pregnant or breastfeeding;
• Patients whose lesions have been resected;
• Suffered from other types of malignant tumors with a clear pathological diagnosis within 5 years prior to enrollment;
• Within the past year of enrollment, the patient had other malignant tumors suspected by imaging, but they were not confirmed by pathology;
• Suspected distant metastatic lesions on imaging, or potential lymph node lesions that cannot be completely cured by surgery;
• Have received any blood product infusion treatment in the past 30 days. -

Sponsors & Collaborators

• Second Affiliated Hospital, School of Medicine, Zhejiang University: lead

Biospecimen

Retention: SAMPLES WITH DNA

Detect tumor-related cfDNA fragments in plasma

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Year
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 19, 2025
• First Posted: December 26, 2025
• Study Start: December 1, 2025
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): December 31, 2027
• Last Updated: December 26, 2025

Record last verified: 2025-10

Data Sharing

• IPD Sharing: Will not share