Predicting and Evaluating the Efficacy of Neoadjuvant Therapy in Colorectal Cancer Based on 4D Deep Urinary Proteomics Technology
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.
• Aged 18-75 years;
• Pathologically confirmed diagnosis of locally advanced colorectal cancer (cT3-4 and/or N+);
• Planned to undergo neoadjuvant therapy followed by surgical resection;
• No evidence of distant metastasis (M0) confirmed by imaging (CT and/or PET-CT);
• Clinically assessed as being able to tolerate and complete the full course of neoadjuvant treatment;
• No prior anti-tumor therapy (e.g., targeted therapy, immunotherapy) before the initiation of treatment;
• Willing and able to provide urine samples as required;
• Written informed consent obtained.