AI-powered multi-omics model to predict breast cancer distant and organ-specific metastasis
Official title: A Multi-omics Breast Cancer Distant Metastasis Prediction Model Empowered by Artificial Intelligence and Its Clinical Translation Research
Run by Second Affiliated Hospital, Zhejiang University, School of Medicine · NCT07252986 · Data updated 2026-11-12
This project will test whether combining tumor images, protein data, and gene sequencing with artificial intelligence can predict if and where breast cancer will spread for women who have stored metastatic tissue samples at the hospital.
Quick facts
| Study type | Observational |
|---|---|
| Sex | Women only |
| Enrollment | 2000 (estimated) |
| Sponsor | Second Affiliated Hospital, Zhejiang University, School of Medicine Academic / other |
| Locations | 1 site (Hangzhou, Zhejiang) |
| Status | Recruiting |
| Started | December 1, 2025 |
| Main results expected | December 30, 2028 |
| Study ends | December 30, 2028 |
| Registry record updated | March 3, 2026 |
| Trial ID | NCT07252986 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Women with pathologically confirmed breast cancer who have a biopsy or surgical specimen from a distant metastatic site stored at the Second Affiliated Hospital, Zhejiang University (or participating centers) from 2000 to 2028 are ideal candidates.
✕Probably not a fit
Patients without stored metastatic tissue specimens at the study sites, with incomplete clinical records, or with a concurrent metastatic cancer from another primary are unlikely to benefit from this project.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational project will build a precision prediction system by integrating digital pathology images, immunohistochemistry, proteomics, and gene sequencing with artificial intelligence. Researchers will use clinical data and tissue specimens from female breast cancer patients treated at the lead hospital or participating centers between 2000 and 2028, focusing on cases with biopsy or surgical samples from distant metastatic sites. The model aims to predict overall distant metastasis and organ-specific spread to bone, lung, liver, and brain while analyzing molecular patterns to clarify underlying mechanisms. There are no experimental treatments; the work is retrospective and prospective observational data analysis to develop and validate predictive algorithms.
Why it matters
Potential benefit: If successful, the model could help clinicians monitor high-risk patients more closely and tailor surveillance or treatment to prevent or detect metastasis earlier.
How similar studies have gone: Previous AI and genomics efforts have shown promise for predicting breast cancer outcomes, but comprehensive multi-omics models that combine digital pathology, proteomics, and sequencing for organ-specific metastasis prediction remain relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Female patients pathologically diagnosed with breast cancer at our hospital or participating centers between January 1, 2000, and December 30, 2028. 2. 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. Exclusion Criteria: 1. Concomitant metastatic malignancy from another primary cancer. 2. Incomplete clinical information.
Where it's running
-
The Second Affiliated Hospital, Zhejiang University School of Medicine
Hangzhou, Zhejiang, China Recruiting
Study contacts
- Study coordinator: Fengbo Huang, MD
- Email: keyanlunli_zheer@163.com
- Phone: 0571-87783914
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.