Multi-omics testing to distinguish benign from malignant lung nodules
Official title: Clinical Application Research on Differentiating Benign and Malignant Pulmonary Nodules Based on Multi-omics Detection Technology
Run by The First Affiliated Hospital of Soochow University · NCT07047573 · Data updated 2026-11-12
This project will test whether combining blood single-cell data, flow cytometry, and CT image features can tell if a pulmonary nodule is benign or cancerous in people scheduled for nodule surgery.
Quick facts
| Study type | Observational |
|---|---|
| Sex | All |
| Enrollment | 150 (estimated) |
| Sponsor | The First Affiliated Hospital of Soochow University Academic / other |
| Locations | 1 site (Suzhou, Jiangsu) |
| Status | Recruiting |
| Started | June 1, 2025 |
| Main results expected | June 2026 |
| Study ends | June 2026 |
| Registry record updated | July 2, 2025 |
| Trial ID | NCT07047573 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
People with pulmonary nodules on CT who are scheduled for surgical resection and can provide blood samples and complete clinicopathological data are the intended participants.
✕Probably not a fit
Patients without clear imaging or pathological diagnosis, those with active blood-borne infections, coagulation problems, severe psychiatric illness, or who cannot be followed long-term are unlikely to benefit or be eligible.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study will collect peripheral blood, CT imaging, and clinical data from about 100 patients who undergo surgery for pulmonary nodules and classify them by postoperative pathology into benign or malignant groups. Researchers will perform single-cell sequencing, flow cytometry (including PBMCs incubated with nanoparticle-loaded tumor antigens), and radiomics analyses to identify immune and molecular signatures that differ between groups. The team will build predictive models that combine multi-omics and clinical features to predict nodule nature before surgery and compare their diagnostic sensitivity with traditional tumor markers. The aim is to find specific markers with clinical value and improve preoperative diagnostic accuracy for pulmonary nodules.
Why it matters
Potential benefit: If successful, this approach could improve preoperative identification of malignant nodules, reduce unnecessary surgeries, and enable earlier treatment for people with lung cancer.
How similar studies have gone: Radiomics and blood-based biomarker studies have shown promise separately, but combining single-cell profiling, flow cytometry with antigen-loaded nanoparticles, and imaging in a single predictive model is relatively novel and not yet widely validated.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patient underwent a ct examination * Patient was confirmed to have pulmonary nodules * Patient has been determined to undergo surgical treatment * There are clear pathological results * The clinicopathological data are complete Exclusion Criteria: * Patient has no ct examination results * Refuse surgical treatment * Patient has no clear pathological diagnosis * Patients with hematogenic infectious diseases, such as HIV, hepatitis B or hepatitis C. * Patients with tumor emergencies that require immediate treatment. * Poor vascular conditions. * Abnormal coagulation function or receiving anticoagulant or thrombolytic therapy. * Patients with hematogenic infectious diseases, such as HBV. * Patients with psychiatric disorders or severe mental illnesses. * Patients who have difficulty communicating or are unable to be followed up for a long time
Where it's running
-
Soochow university
Suzhou, Jiangsu, China Recruiting
Study contacts
- Study coordinator: Mi Liu
- Email: mi.liu831116@icoud.com
- Phone: 86-0512-67972216
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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.