Actively Recruiting

Age: 18Years - 75Years
All Genders
NCT06904677

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

Led by Cancer Institute and Hospital, Chinese Academy of Medical Sciences · Updated on 2025-11-28

400

Participants Needed

1

Research Sites

208 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

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.

CONDITIONS

Official Title

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

Who Can Participate

Age: 18Years - 75Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • 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 able to tolerate and complete full neoadjuvant treatment
  • No prior anti-tumor therapy before treatment start
  • Willing and able to provide urine samples as required
  • Written informed consent obtained
Not Eligible

You will not qualify if you...

  • History of or current other malignancies
  • Severe hepatic, renal, cardiovascular, or metabolic diseases affecting urinary protein metabolism
  • Recent use of medications affecting protein metabolism (e.g., glucocorticoids, high-dose antibiotics)
  • Urinary tract infection or diseases causing abnormal urinary protein levels (e.g., nephrotic syndrome)
  • Any other condition unsuitable for enrollment as decided by investigators

AI-Screening

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Trial Site Locations

Total: 1 location

1

Cancer Hospital Chinese Academy of Medical Sciences

Beijing, Chaoyang District, China, 100021

Actively Recruiting

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Research Team

Q

Qian Liu, M.D.

CONTACT

M

Mingguang Zhang, M.D.

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

3

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