Identifying neoepitopes that elicit an adaptive immune response is a major bottleneck to
developing personalized cancer vaccines. Experimental validation of candidate …

Background Immunotherapy is an emerging approach in cancer treatment that activates the
host immune system to destroy cancer cells expressing unique peptide signatures …

Computational prediction of binding between neoantigen peptides and major
histocompatibility complex (MHC) proteins can be used to predict patient response to cancer …

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II
molecules would be valuable for vaccine development and cancer immunotherapies …

Current tumor neoantigen calling algorithms primarily rely on epitope/major
histocompatibility complex (MHC) binding affinity predictions to rank and select for potential …

Motivation Increasingly comprehensive characterization of cancer-associated genetic
alterations has paved the way for the development of highly specific therapeutic vaccines …

Neoantigens play important roles in cancer immunotherapy. Current methods used for
neoantigen prediction focus on the binding between human leukocyte antigens (HLAs) and …

Epitopes that arise from a somatic mutation, also called neoepitopes, are now known to play
a key role in cancer immunology and immunotherapy. Recent advances in high-throughput …

The accurate selection of neoantigens that bind to class I human leukocyte antigen (HLA)
and are recognized by autologous T cells is a crucial step in many cancer immunotherapy …

The field of cancer neoantigen investigation has developed swiftly in the past decade.
Predicting novel and true neoantigens derived from large multi-omics data became difficult …