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UnknownNCT05721963

Study on the Accuracy of Proteomics in Evaluating Lymph Node Metastasis Status in Cholangiocarcinoma Patients

Clinical Study on the Accuracy of Proteomics in Evaluating Lymph Node Metastasis Status and Comparation With Pathological Examination in Cholangiocarcinoma Patients

Status
Unknown
Phase
Study type
Observational
Enrollment
30 (estimated)
Sponsor
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University · Academic / Other
Sex
All
Age
18 Years – 75 Years
Healthy volunteers
Not accepted

Summary

This is a single-center, prospective, observational and exploratory clinical study. The object of this study is to evaluate the accuracy of proteomics approaches on resected lymph node samples in evaluating lymph node metastasis status in cholangiocarcinoma patients.

Detailed description

The current gold standard for the diagnosis of lymph node metastasis is pathological examination of surgically resected lymph node specimens. However, lymph node metastases are different from the primary lesions, and the distribution of tumor cells is heterogeneous and more dispersed. Therefore, a single thin pathological section is difficult to obtain complete information, which may be misdiagnosed due to the failure to examine on the section containing tumor cells or the presence of micro-metastases. The application of proteomics can obtain the overall information of the samples, including the remodeling of the microenvironment by the tumor metastases and the acclimation even before the metastasis, resulting in significant changes in the protein expression profiles of the lymph nodes, which are difficult to be completely presented in conventional pathological sections. This study aims to evaluate the accuracy of proteomics approaches on resected lymph node samples in evaluating lymph node metastasis status in cholangiocarcinoma patients, assisting in guiding precision medicine and making therapeutic decisions. Positive controls of lymph node metastases and negative controls of normal lymph nodes were previously profiled using proteomic approaches. Machine-learning clustering method will be used to classify the newly examined lymph nodes.

Conditions

Interventions

TypeNameDescription
DIAGNOSTIC_TESTNo interventions.No interventions.

Timeline

Start date
2023-02-01
Primary completion
2024-12-31
Completion
2024-12-31
First posted
2023-02-10
Last updated
2023-02-10

Locations

1 site across 1 country: China

Source: ClinicalTrials.gov record NCT05721963. Inclusion in this directory is not an endorsement.