Prediction of Drug Response in Gastric Cancer Based on 3D Bioprinting

Recruiting

• Conditions: STOMACH NEOPLASM

• Registration Number: NCT06792149
• Lead Sponsor: Peking Union Medical College Hospital

Brief Summary

The therapeutic regimens for adjuvant and neoadjuvant chemotherapy in gastric cancer (GC) predominantly hinge on clinical experience. Consequently, there is an imperative need for preclinical models to facilitate the guidance of individualized medicine. The investigators plan to establish three-dimensional (3D) bioprinted GC models derived from surgically resected tumor tissues of GC patients. These in vitro 3D models will be subjected to treatment with the identical chemotherapy drugs administered to the corresponding patients from whom the models are sourced. The sensitivity of the chemotherapy drugs will be assayed within the in vitro models, and the actual response to chemotherapy in patients will be meticulously evaluated. This observational study aims to substantiate the potential utility of 3D bioprinted tumor models in prognosticating the response to chemotherapy in GC.

Detailed Description

Not available

Study Timeline

• Study Start: 2023-10-01
• Status Verified: 2024-06
• Study First Submitted: 2025-01-19
• Study First Submitted QC: 2025-01-19
• Last Update Submitted: 2025-01-19
• Study First Posted: 2025-01-24
• Last Update Posted: 2025-01-24
• Primary Completion: 2025-10-31
• Study Completion: 2025-12-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 60

Inclusion Criteria

• More than 18 years old
• Patients previously diagnosed with gastric cancer or confirmed by pathology as having gastric cancer postoperatively.
• Patients who have undergone preoperative imaging examinations, including plain and contrast-enhanced CT scans of the chest, abdomen, and pelvis, as well as gastric MRI for tumor staging, and who are planned for preoperative (neo)adjuvant therapy after multidisciplinary team (MDT) discussion; patients with advanced gastric cancer who are confirmed by postoperative pathology to require (neo)adjuvant therapy.
• The patient or their family members are able to comprehend the research protocol and are willing to participate in this study, providing written informed consent.

Exclusion Criteria

• History of other malignancies or serious medical conditions
• Inability to provide independent informed consent

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Correlation of Drug Sensitivity in In Vitro Tumor Models with Clinical Response in Patients	From enrollment to end within 2 weeks	1. Response of 3D tumor models to chemotherapy drugs identical to those administered to corresponding patients: Researchers will establish and culture 3D printed gastric cancer models and treat them with the same chemotherapy drugs used for the corresponding patients. Following treatment, the viability of the 3D tumor models will be observed, and the IC50 of each drug will be calculated. The correlation between the sensitivity of the 3D models and the patients' responses will be analyzed.; 2. Response of Gastric Cancer Patients to Neoadjuvant Chemotherapy: For patients who undergo neoadjuvant chemotherapy prior to surgery, the response to such treatment will be assessed based on clinical imaging results, the Mandard-TRG criteria, and the RECIST score.

Secondary Outcome Measures

Name	Time	Method
Response of Gastric Cancer Patients to Adjuvant Chemotherapy	Up to 2 years	The response to adjuvant chemotherapy will be assessed based on disease-free survival (DFS) or Overall Survival (OS). Regular follow-ups will be conducted. DFS is defined as the interval between the date of surgery and the date of the last follow-up or the date of recurrence/progression.Overall survival (OS) is delineated as the temporal span from the date of surgery to the date of death or the date of the last follow-up, whichever occurs first.

Trial Locations

Locations (1)

Peking Union Medical College Hospital; 🇨🇳 Beijing, Beijing, China