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We have established a machine learning model based on effective TIIC signature which could select GC patients who may benefit from immunotherapy.
The current study aims to enroll 300 GC patients as a validation cohort to vertify the accuracy of TIIC signature in predicting immunotherapy efficacy
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Immunotherapy Group |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| TIIC signature | Device | Collect tumor tissue of 300 gastric cancer patients at treatment baseline, samples will be transferred to central lab to detect the density and spatial proximity of certain immune cells infiltrated in tumor by multi complex immunohistochemistry, and evaluate patients' TIIC signature.Tumor response evaluation will be performed after two cycles of therapy by CT/MRI based on RECIST.Clinical data, including tumor stage,metastaticorgan ,regimen, objective response, progression free survival, overall survival, etc, will be collected according to study protocol. |
| Measure | Description | Time Frame |
|---|---|---|
| TIIC signature | Density and spatial proximity of 4 kinds of immune cells involved in TIIC signature infiltrate in tumor at treatment baseline will be recorded. | Treatment baseline |
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Inclusion Criteria:
Exclusion Criteria:
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All patients in this study were enrolled by the Department of gastrointestinal oncology, Peking University Cancer Hospital & Institute for conventional therapy or clinical trials
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yang Chen, MD | Contact | 010-88196090 | yang_chen@bjcancer.org |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Peking University Cancer Hospital | Recruiting | Beijing | China |
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