Multi-omics Based Prediction of Treatment Response to Immunotherapy Combined with Chemotherapy in Advanced Gastric/Gastroesophageal Junction Cancer.

NCT ID: NCT06642857

Last Updated: 2024-10-15

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

RECRUITING

Total Enrollment

150 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-03-25

Study Completion Date

2026-02-01

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Advanced Gastric Carcinoma Advanced Gastroesophageal Junction Adenocarcinoma

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Patients with advanced gastric cancer

Advanced gastric cancer patients receiving chemotherapy combined with immunotherapy

Peripheral blood, tougue coating, saliva, and feces

Intervention Type OTHER

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.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

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.

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

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.

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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Xiangdong Cheng

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Xiangdong Cheng

Professor

Responsibility Role SPONSOR_INVESTIGATOR

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)

Hangzhou, Zhejiang, China

Site Status RECRUITING

Countries

Review the countries where the study has at least one active or historical site.

China

Central Contacts

Reach out to these primary contacts for questions about participation or study logistics.

Xiangdong Cheng Cheng, PhD

Role: CONTACT

+0086-0571-88128041

Facility Contacts

Find local site contact details for specific facilities participating in the trial.

Xiangdong Cheng Xiangdong Cheng, PhD

Role: primary

+0086-0571-88128041

Nannan Zhang Nannan Zhang, PhD

Role: backup

18920166859

References

Explore related publications, articles, or registry entries linked to this study.

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. Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study. EClinicalMedicine. 2023 Feb 6;57:101834. doi: 10.1016/j.eclinm.2023.101834. eCollection 2023 Mar.

Reference Type BACKGROUND
PMID: 36825238 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 34840700 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 36633525 (View on PubMed)

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

IRB-2024-175

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.

Changhai Multimodal Esophageal Cancer Cohort
NCT06410677 ACTIVE_NOT_RECRUITING