Classifying cancer of unknown primary using DNA methylation data
PaCIFiC-CUP：Pan-Cancer Integrated Fingerprinting Classifier for Identifying the Origin of Cancer of Unknown Primary: A Multi-Center Prospective Cohort Study
This study is trying to see if a new computer model can help doctors figure out what type of cancer someone has when they don't know where it started, by looking at patterns in DNA from cancer samples.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 120 (estimated) |
| Ages | 18 Years to 80 Years |
| Sex | All |
| Sponsor | Sun Yat-sen University Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Trial ID | NCT06140992 on ClinicalTrials.gov |
What this trial studies
This observational study aims to develop a machine learning model called PaCIFiC-CUP that utilizes DNA methylation data from public databases to classify various types of cancer, particularly those with an unknown primary site. By analyzing the DNA methylation patterns of cancer specimens, the study seeks to improve the accuracy of cancer diagnoses and guide precision treatment strategies. The research will involve patient specimens obtained from the Sun Yat-sen University Cancer Center and affiliated centers, with a focus on integrating pan-cancer data for a comprehensive classification approach.
Who should consider this trial
Good fit: Ideal candidates for this study are patients diagnosed with a primary site unknown tumor who have provided consent for their specimens to be used in research.
Not a fit: Patients who are pregnant or lactating, or those whose tumors do not meet the specified criteria, may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could significantly enhance the diagnostic accuracy for patients with unknown primary tumors, leading to more effective and personalized treatment options.
How similar studies have performed: Other studies utilizing machine learning and DNA methylation data have shown promise in cancer classification, suggesting that this approach may yield beneficial results.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. The patient specimens were obtained from the Sun Yat-sen University Cancer Center and affiliated cooperating centers, with written consent from the patients authorizing the use of the specimens for research purposes. 2. Following standard assessments (medical history, physical examination, complete blood count, biochemistry, computed tomography scans of the neck, chest, abdomen, and pelvis, targeted evaluations of all symptomatic areas, pathology, and immunohistochemistry), the diagnosis was determined as a primary site unknown tumor (including adenocarcinoma, squamous cell carcinoma, undifferentiated carcinoma, neuroendocrine carcinoma, sarcoma, etc). 3. The diagnosis was confirmed at the participating institution and the patient had received systemic therapy. 4. Complete clinical, pathological, and follow-up data for the patients can be obtained. 5. ECOG performance status score: 0-2 points. Exclusion Criteria: 1. Pregnant or lactating female patients. 2. Tumor tissue sample size is too small (tumor tissue accounts for \<70% in the biopsy or slice tissue). 3. Organ transplant or history of non-autologous (allogeneic) bone marrow or stem cell transplantation. 4. History of previous tumors, with the current condition being a recurrent tumor. 5. Hematological malignancies (excluding lymphoma). 6. Other diseases that may severely impact patient survival, such as severe cardiovascular or cerebrovascular diseases, sepsis, severe trauma or burns, etc.
Where this trial is running
Guangzhou, Guangdong
- Sun Yat-sen university cancer center — Guangzhou, Guangdong, China (Recruiting)
Study contacts
- Study coordinator: Yiyang Zhang
- Email: zhangyy@sysucc.org.cn
- Phone: +8615652797092
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.