An observational study in Colorectal Cancer (CRC), Neoadjuvant Therapy and Proteomics, sponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences. Recruiting at 1 site in China. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2025-11-28.
Sponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences · Observational
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.
Neoadjuvant therapy is one of the main treatment strategies for patients with locally advanced colorectal cancer (LACC). However, the response to neoadjuvant therapy varies greatly among individuals, presenting a significant clinical challenge in accurately predicting therapeutic efficacy before treatment and dynamically assessing response during therapy. Commonly used clinical methods-such as imaging techniques, tissue biomarkers, and liquid biomarkers-often suffer from low sensitivity and specificity.
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.
5,600 studies on the registry are indexed under Colorectal Neoplasms; 1,459 are open to participants now.
This study's planned enrollment of 400 is above the median of 250 across 1,226 observational studies indexed under Colorectal Neoplasms.
Browse Colorectal Neoplasms studies →Cancer Institute and Hospital, Chinese Academy of Medical Sciences is the lead sponsor of 374 studies on the registry; 271 are open to participants now.
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This study will enroll patients aged 18 to 75 years with a pathologically confirmed diagnosis of locally advanced colorectal cancer (LACC), defined as clinical stage cT3-4 and/or N+ without distant metastasis (M0) as determined by imaging (CT and/or PET-CT). Eligible participants must be treatment-naïve, with no prior exposure to anti-tumor therapies such as chemotherapy, targeted therapy, or immunotherapy. All patients must be clinically assessed as suitable candidates for neoadjuvant therapy followed by surgical resection and must be able to tolerate and complete the prescribed treatment regimen. In addition, participants must be willing and able to provide urine samples before and after neoadjuvant therapy and must sign written informed consent prior to enrollment.
Patients will be excluded if they have a history of or concurrent diagnosis of other malignancies; suffer from serious hepatic, renal, cardiovascular, or metabolic conditions that may interfere with urinary protein metab
Exclusion Criteria:
Diagnosed with rectal cancer and receiving neoadjuvant chemoradiotherapy.
Diagnosed with colorectal cancer and receiving neoadjuvant chemoradiotherapy.
Diagnosed with colorectal cancer and receiving neoadjuvant immunochemotherapy.
Tumor regression grade
Tumor regression after neoadjuvant therapy (based on pathological analysis of the resected specimen)
Time frame: through study completion, an average of 3 months
Plan to share: No — Individual participant data (IPD) will not be shared due to concerns regarding patient privacy and confidentiality, as well as institutional regulations on data sharing.
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Cancer Institute and Hospital, Chinese Academy of Medical Sciences