Computational Prediction and Experimental Validation of Esophageal Cancer Associated Neoantigens

University Medical Center Ho Chi Minh City (UMC)

Status

Not yet enrolling

Conditions

Neoantigen

Esophageal Cancer

Treatments

Genetic: ratio of predicted neoantigens

Study type

Observational

Funder types

Other

Identifiers

NCT05498168

61/GCN-HDDD

Details and patient eligibility

About

This study is to develop computational pipelines and experimental validation assays for improving the identification of neoantigens from patients with esophageal cancer.

Full 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.

Enrollment

50 estimated patients

Sex

All

Ages

15 to 90 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria