Classifying pulmonary nodules using whole-genome methylation sequencing

Development a Pulmonary Nodules Diagnosis Classification Model for Benign/Malignant of Bronchoscopic Biopsy Specimens Based on High-throughput Whole-genome Methylation Sequencing(GM-seq)

This study is testing a new way to tell if lung nodules are cancerous or not by using advanced DNA analysis to help patients with nodules found on chest scans get a more accurate diagnosis without needing invasive procedures.

Quick facts

• Study type: Observational
• Enrollment: 120 (estimated)
• Ages: 20 Years to 75 Years
• Sex: All
• Sponsor: Geneplus-Beijing Co. Ltd. (industry)
• Locations: 2 sites (Beijing, Beijing and 1 other locations)
• Trial ID: NCT05415670 on ClinicalTrials.gov

What this trial studies

This observational study aims to improve the classification of benign and malignant pulmonary nodules through high-throughput whole-genome methylation sequencing (GM-seq). By utilizing liquid biopsy technology and machine learning, the study seeks to enhance early lung cancer diagnosis, particularly in patients with solitary nodules detected via chest CT. The research focuses on patients who are candidates for surgical resection and aims to gather clinical data to support the findings. The goal is to provide a more accurate and less invasive diagnostic method compared to traditional pathological techniques.

Who should consider this trial

Good fit: Ideal candidates are males and females aged 20-75 with solitary pulmonary nodules of 1-3 cm in diameter suspected to be malignant and eligible for surgical resection.

Not a fit: Patients with metastatic tumors, unresectable advanced lung cancer, or those unwilling to undergo invasive examinations may not benefit from this study.

Why it matters

Potential benefit: If successful, this approach could lead to earlier and more accurate diagnoses of lung cancer, improving patient outcomes.

How similar studies have performed: While liquid biopsy technology has shown promise in early cancer screening, the specific application of whole-genome methylation sequencing for pulmonary nodule classification is relatively novel.

Eligibility criteria

Inclusion Criteria:

1. Male or female, 20-75 year-old with pulmonary nodules 1-3cm in diameter confirmed by chest CT;
2. The nodules are single or multiple, suspected to be malignant, and have the indication of surgical resection;
3. Patient accept imaging evaluation without advanced lung tumors and metastases;
4. The location of the nodule in the lung is within the reach of lung biopsy under bronchoscope;
5. provide the collected clinical data needed by the research;
6. Patients have the ability to follow the planned schedule and actively cooperate to return to the hospital for regular clinical visits.

Exclusion criteria:

1. Unwilling to accept the invasive examination and treatment of this study;
2. Contraindication of tracheoscopy;
3. Consider that the pulmonary nodules are metastatic tumors or unresectable advanced lung cancer;
4. Those who cannot tolerate resection of pulmonary nodules;
5. Accompanied by other malignant tumors;
6. In the judgment of the researcher, the patient also suffers from other serious diseases that may affect the accuracy of the test;
7. Those who cannot accept the use of contrast-enhanced magnetic resonance imaging (MRI) or contrast-enhanced computed tomography (CT);
8. Any other illness, social / psychological problems, etc. are judged by the researcher to be unsuitable for participating in this study.

Where this trial is running

Beijing, Beijing and 1 other locations

• Emergency general hospital — Beijing, Beijing, China (RECRUITING)
• Beijing hospital — Beijing, Beijing, China (RECRUITING)

Study contacts

• Study coordinator: Wei Zhou, Doctor

Conditions: Pulmonary Nodule, Solitary, Whole-genome Methylation Sequencing, ctDNA, Machine learning