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.
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.
Study Type
OBSERVATIONAL
Enrollment
30
No interventions.
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
Guangzhou, Guangdong, China
RECRUITINGLymph node metastasis status of each examined lymph nodes by pathological tests
The pathological examination results of each resected lymph nodes will be recorded
Time frame: 1 month
Lymph node metastasis status of each lymph nodes evaluated by proteomic approaches
Machine-learning clustering will be applied to classify the lymph node metastasis status of each lymph nodes based on proteomic profiles
Time frame: 2 month
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.