Using 4D Urinary Proteomics to Predict and Evaluate Treatment Response in Colorectal Cancer

Summary

The goal of this observational study is to learn how well urinary proteins can predict treatment response in patients with locally advanced colorectal cancer (LACC) undergoing neoadjuvant therapy. The main question it aims to answer is: Can urinary protein markers help predict and evaluate how patients with LACC respond to neoadjuvant therapy? Participants diagnosed with LACC will provide urine samples before and after neoadjuvant therapy. These samples will be analyzed using 4D deep urinary proteomics and machine learning to identify proteins linked to treatment response. Some participants' tumor tissues will also be used to create organoid models for further testing.

Eligibility

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.

Conditions4

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