Computational Prediction and Experimental Validation of Esophageal Cancer Associated Neoantigens
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Esophageal Cancer
- Sponsor
- University Medical Center Ho Chi Minh City (UMC)
- Enrollment
- 50
- Locations
- 1
- Primary Endpoint
- The neoantigen landscape of patients with esophageal cancer
- Last Updated
- 3 years ago
Overview
Brief Summary
This study is to develop computational pipelines and experimental validation assays for improving the identification of neoantigens from patients with esophageal cancer.
Detailed Description
Esophageal cancer (EC) is the common malignant tumor with poor survival. The long-term surival rate of patients with advanced EC stages has not been improved with multidisciplinary treatments including surgery and chemotherapy and radiation. Recently, immunotherapy approaches using checkpoint inhibitors (CPI), cancer vaccine, and adoptive T cell therapy have improved survival outcomes of EC patients. The clinical outcomes are associated with expression levels as well as the immunogenicity of neoantigens which arise from soma mutations. Therefore, the identification of immunogenic neoantigens is essential for achieving effective therapies. Recent data published by the Tumor Neoantigen Selection Alliance (TESLA) show that the majority (98%) of predicted neoantigens are lack of immunogenicity and ineffective in activating antitumor immune responses. In our study, we aim to develop a pipeline with both computational prediction tools and experimental validation assays to enhance the accuracy of neoantigen identification.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Male or Female patients aged 18 years and older
- •Diagnosed with advanced esophageal cancer
- •Treatment-Naive
- •Not known for other concomitant cancers
- •Provide written informed consent
Exclusion Criteria
- •Insufficient tumor tissues (less than 1 cm3 )
- •Unable to sign informed consent
- •Underwent treatment
Outcomes
Primary Outcomes
The neoantigen landscape of patients with esophageal cancer
Time Frame: 3 months from the begining of study
The analysis of tumor DNA and RNA sequencing data will provide the mutational distribution of patients with esophageal cancer, which could give rise to neoantigens. Of those, neoantigens derived from hotspot mutations in Vietnamese esophageal cancer patients will be identified.
The ratio of predicted neoantigens being presented by HLA-I
Time Frame: 6 months from the begining of study
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.
The ratio of predicted neoantigens being immunogenic
Time Frame: 12 months from the begining of study
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.