The Construction of a Predictive Model for Gastric Cancer Immunotherapy Response Based on Tumor-Infiltrating Lymphocytes (TILs) and Histone H3K4me3 in the Tumor Microenvironment

Recruiting now

Conditions studied: Gastric Cancer, Immunotherapy

In brief

Gastric cancer is one of the cancers with a high mortality rate globally, and its treatment outcomes urgently need to be improved. The emergence of immunotherapy has broken through the bottleneck of chemotherapy for gastric cancer. However, the therapeutic efficacy of immunotherapy varies significantly among patients and still needs to be enhanced. Extensive research has demonstrated that the efficacy of immunotherapy for gastric cancer is significantly influenced by the tumor microenvironment (TME) and epigenetic modifications. The dynamic changes in tumor-infiltrating lymphocytes (TILs) and histone H3K4me3 may reshape the TME, thereby affecting the efficacy of immunotherapy. Based on these findings, this study proposes the scientific hypothesis that the density and spatial distribution of TILs in the TME, as well as the level of H3K4me3 modification, may serve as key biomarkers for predicting the response of gastric cancer patients to immunotherapy. This project aims to delve into the potential mechanisms by which TILs and H3K4me3 enhance the efficacy of immune checkpoint inhibitors (ICIs) and to construct a predictive model for the response to immunotherapy in gastric cancer based on TILs and H3K4me3. The establishment of this model will help identify the patient population most likely to benefit from immunotherapy, facilitate personalized treatment, provide new ideas and approaches for the treatment of gastric cancer, and advance the field of gastric cancer immunotherapy.

Key facts

Study ID
NCT07069842
Run by
Changzhi People's Hospital Affiliated to Changzhi Medical College
People needed
170
Starts
2025-01-01
Expected to finish
2026-12-31
Last updated by the study team
2025-07-17

Who can join

Age: 18 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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