Multi-omics Based Prediction of Treatment Response to Immunotherapy Combined with Chemotherapy in Advanced Gastric/Gastroesophageal Junction Cancer.
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Peripheral blood, tougue coating, saliva, and feces.
- Who it may be relevant to
- Registry conditions: Advanced Gastric Carcinoma, Advanced Gastroesophageal Junction Adenocarcinoma. Basic parameters: 18 years — 75 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Predicting Treatment Response to Immunotherapy Combined with Chemotherapy in Advanced Gastric/gastroesophageal Junction Cancer Based on the Multi-omics Information During Tumor Evolution.
Overview
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.
Detailed description
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
Interventions
- Other Peripheral blood, tougue coating, saliva, and feces
Peripheral blood, coating, saliva, and feces on the tongue and clinical data of patients with advanced gastric cancer patients who received chemotherapy combined with immunotherapy will be collected.
Primary outcome measures
- Objective Best Tumor Response [Time frame: 12 months]
- Overall Survival [Time frame: 60 months]
Secondary outcome measures (1)
- Progression-free Survival [Time frame: 36 months]
Eligibility criteria
Inclusion criteria：
- Patients with gastric or gastroesophageal junction adenocarcinoma confirmed by pathology and with advanced or metastatic disease that cannot be resected
- HER2 negative
- Not received any anti-tumor treatment before.
- After evaluation, the treatment plan is chemotherapy combined with immunotherapy.
- Aged 18 to 75 years old, gender is not limited.
- Expected survival time is greater than or equal to 3 months. Exclusion criteria：
- Patients with malignant tumors other than gastric cancer or those with tumors metastasized to the stomach from other sites.
- Patients who have previously received anti-tumor treatments such as surgery, radiotherapy and chemotherapy, targeted therapy or immunotherapy.
- Patients with severe infections.
- Those with a history of mental illness cannot cooperate with the research.
- Patients with severe heart, liver, kidney and other diseases.
- Pregnant or lactating patients.
- HER2 positive.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital — Hangzhou
Publications
- Yuan L, Yang L, Zhang S, Xu Z, Qin J, Shi Y, Yu P, Wang Y, Bao Z, Xia Y, Sun J, He W, Chen T, Chen X, Hu C, Zhang Y, Dong C, Zhao P, Wang Y, Jiang N, Lv B, Xue Y, Jiao B, Gao H, Chai K, Li J, Wang H, Wang X, Guan X, Liu X, Zhao G, Zheng Z, Yan J, Yu H, Chen L, Ye Z, You H, Bao Y, Cheng X, Zhao P, Wang L, Zeng W, Tian Y, Chen M, You Y, Yuan G, Ruan H, Gao X, Xu J, Xu H, Du L, Zhang S, Fu H, Cheng X PMID 36825238
- Li MY, Zhu DJ, Xu W, Lin YJ, Yung KL, Ip AWH. Application of U-Net with Global Convolution Network Module in Computer-Aided Tongue Diagnosis. J Healthc Eng. 2021 Nov 18;2021:5853128. doi: 10.1155/2021/5853128. eCollection 2021. PMID 34840700
- Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023 Jan;73(1):17-48. doi: 10.3322/caac.21763. PMID 36633525
Identifiers
NCT: NCT06642857 · IRB-2024-175