NCT05498168

Computational Prediction and Experimental Validation of Esophageal Cancer Associated Neoantigens

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 50 (estimated)
• Sponsor: University Medical Center Ho Chi Minh City (UMC) · Academic / Other
• Sex: All
• Age: 15 Years – 90 Years
• Healthy volunteers: Accepted

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.

Conditions

• Esophageal Cancer
• Neoantigen

Interventions

Type	Name	Description
GENETIC	ratio of predicted neoantigens	10 ml of whole blood is collected from each patient prior surgery Fresh tumor tissue samples (\~ 1cm3 ) are collected during surgery

Timeline

• Start date: 2022-09-01
• Primary completion: 2023-12-31
• Completion: 2023-12-31
• First posted: 2022-08-11
• Last updated: 2022-08-11

Locations

1 site across 1 country: Vietnam