Introduction

Researchers from TESLA established a model of tumor epitope immunogenicity by using multiple independent pipelines to predict neoantigens in common tumor samples. This model integrates peptide characteristics related to tumor neoantigen presentation and recognition, and can filter out 98% of non-immunogenic peptides. Here, we collected the key parameters controlling tumor immunogenicity in the model and integrated powerful predictive tools in “Antigenic Peptide Prediction”to facilitate neoantigen screening.