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Predicting Treatment Response to Immunotherapy Combined with Chemotherapy in Advanced Gastric/gastroesophageal Junction Cancer Based on the Multi-omics Information During Tumor Evolution.
In this project, based on the information of advanced gastric/gastroesophageal junction cancer in evolution under immunotherapy combined with chemotherapy treatment, we will integrate multi-omics dynamic data to identify essential features that correlate to therapeutic effects of immunotherapy therapy, screen potential molecular markers/dominant microbiota for predicting the efficacy of immunotherapy and establish a multimodal predictive model for patients that benefit from immunotherapy. Our project could provide evidence to predict response to immunotherapy for patients with advanced gastric/gastroesophageal junction cancer and potentially optimize the clinical decision-making about therapy for advanced gastric/gastroesophageal junction cancer.
Main objective: to extract and identify multi omics information tags related to the efficacy of immunotherapy for advanced gastric / gastroesophageal junction cancer Secondary objective: to construct and validate the efficacy prediction model of chemotherapy combined with immunotherapy for gastric cancer, in order to optimize the scheme decision of advanced gastric cancer treatment Exploratory purpose: to screen potential molecular markers / dominant flora for predicting the efficacy of immunotherapy in patients with advanced gastric / gastroesophageal junction cancer
Age
18 - 75 years
Sex
ALL
Healthy Volunteers
No
Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)
Hangzhou, Zhejiang, China
Start Date
March 25, 2024
Primary Completion Date
February 1, 2026
Completion Date
February 1, 2026
Last Updated
October 15, 2024
150
ESTIMATED participants
Peripheral blood, tougue coating, saliva, and feces
OTHER
Lead Sponsor
Xiangdong Cheng
NCT04550494
NCT04704661
Data Source & Attribution
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