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This study is to develop methods for identification of neoantigens from patients with gastric cancer.
Gastric cancer (GC) is the fourth most common cancer type and one of the leading causes of cancer-related death in Vietnam. Immunotherapy using checkpoint inhibitors (CPI) in combination with certain types of chemotherapy has been clinically shown to offer survival benefits for patients diagnosed with advanced stomach cancer. However, clinical outcomes of CPI are associated with the quantity as well as the quality of neoantigens which arise due to mutations in coding regions of cancer associated genes. Such neoantigens can be presentable by cancer cells to the host adaptive immune system and activate antitumor responses. Hence, the identification of neoantigens would be of significance for immunotherapeutic approaches. Recent data published by the Tumor Neoantigen Selection Alliance (TESLA) indicate that a large proportion (98%) of predicted neoantigens are not immunogenic and ineffective in activating anti-tumor responses. In the present study, we aim to develop a comprehensive pipeline incorporating both computational prediction tools and experimental validation assays to enhance the accuracy of neoantigen identification.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ratio of predicted neoantigens | Diagnostic Test | 10 ml of whole blood is collected from each patient prior surgery Fresh tumor tissue samples (~ 1cm3 ) are collected during surgery |
| Measure | Description | Time Frame |
|---|---|---|
| The neoantigen landscape of patients with gastric cancer | The analysis of tumor DNA and RNA sequencing data will provide the mutational distribution of patients with gastric cancer, which could give rise to neoantigens. Of those, neoantigens derived from hotspot mutations in Vietnamese gastric cancer patients will be identified. | 3 months from the beginning of the study |
| Measure | Description | Time Frame |
|---|---|---|
| The ratio of predicted neoantigens being presented by HLA-I | Computational pipelines will be employed to predict the pairing of neoantigens and HLA molecules. Subsequently, the ratio of those predicted neoantigens will be validated by co-immunoprecipitation with anti-HLA antibodies and mass spectrometry analysis for their binding to corresponding HLA molecules. | 6 months from the beginning of the study |
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Inclusion Criteria:
Exclusion Criteria:
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All the patients who were diagnosed with adavanced gastric cancer and underwent surgical resection
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Long Vo Duy | Contact | +84.918133915 | long.vd@umc.edu.vn |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Medical Center Ho Chi Minh City | Ho Chi Minh City | 700000 | Vietnam |
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| ID | Term |
|---|---|
| D013274 | Stomach Neoplasms |
| ID | Term |
|---|---|
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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| The ratio of predicted neoantigens being immunogenic. | Immunoassays will be employed to identify neoantigens that could activate CD4 and CD8 T cells to kill tumor cells and serve as putative candidates for immunotherapy. | 12 months from the beginning of the study |
| D004066 |
| Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D013272 | Stomach Diseases |