Using 4D Urinary Proteomics to Predict and Evaluate Treatment Response in Colorectal Cancer
NCT ID: NCT06904677
Last Updated: 2025-11-28
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
400 participants
OBSERVATIONAL
2025-05-01
2029-05-01
Brief Summary
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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.
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Detailed Description
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In our previous research, we applied 4D deep urinary proteomics to analyze pre-treatment urine samples from patients classified as responders and non-responders to neoadjuvant therapy. The results demonstrated that urinary proteomic profiles reflect differences in the tumor microenvironment associated with treatment response and hold promise for predicting therapeutic efficacy.
Building on this foundation, the current project aims to optimize the 4D deep urinary proteomics workflow and perform comparative analyses of urine samples collected before and after neoadjuvant therapy. Machine learning algorithms will be employed to identify candidate urinary proteins associated with treatment response, and key proteins will be validated using targeted proteomics and immunological techniques. Additionally, patient-derived organoid (PDO) models will be used to explore the biological functions of candidate proteins and elucidate their roles in mediating sensitivity to neoadjuvant therapy.
This study is expected to enable precise stratification of LACC patients and support the implementation of personalized treatment strategies. Furthermore, it may uncover mechanisms of resistance and propose novel therapeutic approaches to improve clinical decision-making and outcomes.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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nCRT group
Diagnosed with rectal cancer and receiving neoadjuvant chemoradiotherapy.
No interventions assigned to this group
chemotherapy group
Diagnosed with colorectal cancer and receiving neoadjuvant chemoradiotherapy.
No interventions assigned to this group
immunochemotherapy group
Diagnosed with colorectal cancer and receiving neoadjuvant immunochemotherapy.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
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
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.
18 Years
75 Years
ALL
No
Sponsors
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Cancer Institute and Hospital, Chinese Academy of Medical Sciences
OTHER
Responsible Party
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QIAN LIU
Chief Physician
Locations
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Cancer Hospital Chinese Academy of Medical Sciences
Beijing, Chaoyang District, China
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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NCC2025C-464
Identifier Type: -
Identifier Source: org_study_id
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