Urine protein markers to predict and monitor response to pre-surgery therapy in colorectal cancer.
Predicting and Evaluating the Efficacy of Neoadjuvant Therapy in Colorectal Cancer Based on 4D Deep Urinary Proteomics Technology
This project will test whether urine proteins can predict and track how people with locally advanced colorectal cancer respond to neoadjuvant (pre-surgery) therapy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 400 (estimated) |
| Ages | 18 Years to 75 Years |
| Sex | All |
| Sponsor | Cancer Institute and Hospital, Chinese Academy of Medical Sciences Academic / other |
| Drugs / interventions | immunotherapy |
| Locations | 1 site (Beijing, Chaoyang District) |
| Trial ID | NCT06904677 on ClinicalTrials.gov |
What this trial studies
This is an observational project in which patients with locally advanced colorectal cancer provide urine samples before and after neoadjuvant therapy. Samples will be analyzed using optimized 4D deep urinary proteomics and machine learning to identify proteins associated with treatment response. Key candidate proteins will be validated using targeted proteomics and immunological methods. Selected tumor tissues will be used to create patient-derived organoids to explore the biological roles of the identified proteins in therapy sensitivity.
Who should consider this trial
Good fit: Adults aged 18–75 with pathologically confirmed locally advanced colorectal cancer (cT3-4 and/or N+) who are planned for neoadjuvant therapy followed by surgery, have no distant metastases, and can provide urine samples and informed consent.
Not a fit: Patients with distant metastases, prior anti-tumor therapy, other active malignancies, significant renal or urinary disease, urinary tract infection, or recent medications that affect protein metabolism are unlikely to benefit from this urine-based predictor.
Why it matters
Potential benefit: If successful, this could let doctors use a noninvasive urine test to predict who is likely to benefit from neoadjuvant therapy and to monitor response during treatment.
How similar studies have performed: Previous pilot work using 4D urinary proteomics by the investigators showed promising differences between responders and non-responders, but urine-based prediction of neoadjuvant response remains experimental and not yet validated in large multicenter trials.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Aged 18-75 years; 2. Pathologically confirmed diagnosis of locally advanced colorectal cancer (cT3-4 and/or N+); 3. Planned to undergo neoadjuvant therapy followed by surgical resection; 4. No evidence of distant metastasis (M0) confirmed by imaging (CT and/or PET-CT); 5. Clinically assessed as being able to tolerate and complete the full course of neoadjuvant treatment; 6. No prior anti-tumor therapy (e.g., targeted therapy, immunotherapy) before the initiation of treatment; 7. Willing and able to provide urine samples as required; 8. Written informed consent obtained. Exclusion Criteria: 1. History of or concurrent diagnosis with other malignancies; 2. Presence of severe hepatic, renal, cardiovascular, or metabolic diseases that may affect urinary protein metabolism; 3. Recent use of medications known to affect protein metabolism (e.g., glucocorticoids, high-dose antibiotics); 4. Urinary tract infection or other diseases known to cause abnormal urinary protein levels (e.g., nephrotic syndrome); 5. Any other condition deemed unsuitable for enrollment by the investigators.
Where this trial is running
Beijing, Chaoyang District
- Cancer Hospital Chinese Academy of Medical Sciences — Beijing, Chaoyang District, China (Recruiting)
Study contacts
- Study coordinator: Qian Liu, M.D.
- Email: fcwpumch@163.com
- Phone: +8613601008906
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.