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

NCT06642857 | Recruiting

• 1 other identifier: IRB-2024-175
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Advanced Gastric Carcinoma; Advanced Gastroesophageal Junction Adenocarcinoma

Keywords

Advanced Gastric Carcinoma; Advanced Gastroesophageal Junction Adenocarcinoma; Chemotherapy combined with immunotherapy; efficacy prediction

Outcome Measures

Primary Outcomes (2)

• Objective Best Tumor Response

  Response using Response Evaluation Criteria In Solid Tumors (RECIST) criteria. Complete Response=disappearance of all target lesions; Partial Response=30% decrease in sum of longest diameter of target lesions; Progressive Disease=20% increase in sum of longest diameter of target lesions; Stable Disease=small changes that do not meet above criteria.

  12 months

• Overall Survival

  Overall survival is the duration from diagnosis to death. For patients who are alive, overall survival is censored at the last contact.

  60 months

Secondary Outcomes (1)

• Progression-free Survival

  36 months

Other Outcomes (1)

• Survival rate of 12 month

  12 month from the diagnosis

Study Arms (1)

Patients with advanced gastric cancer

Advanced gastric cancer patients receiving chemotherapy combined with immunotherapy

Other: Peripheral blood, tougue coating, saliva, and feces

Interventions

Peripheral blood, tougue coating, saliva, and feces 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.

Patients with advanced gastric cancer

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with advanced or metastatic gastric or gastroesophageal junction adenocarcinoma

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Xiangdong Cheng: lead

Study Sites (1)

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

Hangzhou, Zhejiang, 310000, China

RECRUITING

Related Publications (3)

• 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.

  PMID: 36825238 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

MeSH Terms

Interventions

Defecation

Intervention Hierarchy (Ancestors)

Digestive System Physiological Phenomena; Digestive System and Oral Physiological Phenomena

Central Study Contacts

Xiangdong Cheng Cheng, PhD

CONTACT

+0086-0571-88128041; Chengxd516@126.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: September 19, 2024
• First Posted: October 15, 2024
• Study Start: March 25, 2024
• Primary Completion: February 1, 2026
• Study Completion: February 1, 2026
• Last Updated: October 15, 2024

Record last verified: 2024-09

Locations

CN (1)