Exploring the Application of 3D Bioprinting for Personalized Treatment in Pancreatic Ductal Adenocarcinoma

Peking Union Medical College Hospital30 enrolled

Overview

The goal of this observational study is to test the application value of 3D bioprinting technology in personalized treatment of pancreatic cancer. The main questions it aims to answer are: * Can 3D bioprinting technology be successfully applied to establish preclinical models of pancreatic cancer? * Can 3D bioprinted preclinical models of pancreatic cancer be applied to personalized treatment of pancreatic cancer? Participants will have tumor tissue collected to extract primary tumor cells for the establishment of in vitro preclinical models, which will be used for drug sensitivity testing.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Pancreatic Ductal Adenocarcinoma

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * More than 18 years old * Diagnosed as colorectal cancer with or without liver metastases before * Pathologically proven colorectal cancer after surgery Exclusion Criteria: * History of other malignancies or serious medical conditions * Inability to provide independent informed consent

Locations (2)

China-Japan Friendship Hospital

Beijing, Beijing Municipality, China

Outcomes

Primary Outcomes

Correlation of Drug Sensitivity in In Vitro Tumor Models with Clinical Response in Patients

1. Evaluation of the efficacy of neoadjuvant therapy in clinical response using the internationally recognized Response Evaluation Criteria in Solid Tumors (RECIST) 1.1: Stable Disease (SD) and Partial Response (PR) are considered indicators of chemotherapy sensitivity (good response), while Progressive Disease (PD) is considered indicative of chemotherapy resistance (poor response). 2. Drug sensitivity testing results were assessed using standardized IC50 values. The standardized IC50 values were treated as the testing variables, while the clinical response to chemotherapy was designated as the state variable. The ROC curves for both variables were analyzed, and the area under the curve (AUC) was calculated to assess their correlation. To analyze the correlation between the drug testing results and clinical prognosis, linear regression analysis was performed to evaluate the correlation between standardized IC50 values and patients' progression-free survival (PFS) values.

Time frame: From enrollment to end within 2 weeks

Secondary Outcomes

Progression-free survival time (PFS)

The time from the start of postoperative adjuvant therapy to recurrence or death.

Time frame: Up to 2 years.