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A Multi-omics Breast Cancer Distant Metastasis Prediction Model Empowered by Artificial Intelligence and Its Clinical Translation Research

Status: Recruiting
Location: See location...
Study Type: Observational
SUMMARY

Breast cancer is one of the most common malignancies in women worldwide, and distant metastasis is the main cause of poor prognosis and death. This project aims to construct a precision prediction system based on multi-omics (digital pathology, immunohistochemistry, proteomics, gene sequencing) and artificial intelligence to predict distant and organ-specific metastasis (bone, lung, liver, brain) in breast cancer, analyze its mechanisms, and provide new solutions for precision medicine.

Eligibility
Participation Requirements
Sex: Female
Healthy Volunteers: f
View:

• Female patients pathologically diagnosed with breast cancer at our hospital or participating centers between January 1, 2000, and December 30, 2028.

• Must meet one of the following: 1) Initially diagnosed with breast cancer at our hospital, has developed distant metastasis (liver, bone, lung, or brain), and has a biopsy or surgical specimen from the metastatic site stored at our hospital, with complete clinical information available. 2) Primary tumor specimen is not at our hospital, but a biopsy or surgical specimen from a distant metastatic site (liver, bone, lung, brain) is stored at our hospital.

Locations
Other Locations
China
The Second Affiliated Hospital, Zhejiang University School of Medicine
RECRUITING
Hangzhou
Contact Information
Primary
Fengbo Huang, MD
keyanlunli_zheer@163.com
0571-87783914
Time Frame
Start Date: 2025-12-01
Estimated Completion Date: 2028-12-30
Participants
Target number of participants: 2000
Treatments
Group 1
Metastatic Risk Stratification (High/Medium/Low Risk)
Group 2
Organ-Specific Metastasis (Bone/Lung/Liver/Brain)
Group 3
Non-Metastatic Control Group
Related Therapeutic Areas
Sponsors
Leads: Second Affiliated Hospital, School of Medicine, Zhejiang University

This content was sourced from clinicaltrials.gov