Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and
control tumor growth. However, it remains difficult to predict the antigens that will be …

The immune epitope database analysis resource (IEDB-AR: http://tools. iedb. org) is a
collection of tools for prediction and analysis of molecular targets of T-and B-cell immune …

Identification of neoantigens is a critical step in predicting response to checkpoint blockade
therapy and design of personalized cancer vaccines. This is a cross-disciplinary challenge …

Neoantigens are newly formed peptides created from somatic mutations that are capable of
inducing tumor-specific T cell recognition. Recently, researchers and clinicians have …

Human leukocyte antigen class I (HLA-I) molecules are encoded by major histocompatibility
complex (MHC) class I loci in humans. The binding and interaction between HLA-I …

Definitive experimental evidence from mouse cancer models and strong correlative clinical
data gave rise to the Cancer Immunoediting concept that explains the dual host-protective …

Computational prediction of T cell epitope candidates is currently being used in several
applications including vaccine discovery studies, development of diagnostics, and removal …

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

High-grade meningiomas frequently recur and are associated with high rates of morbidity
and mortality. To determine the factors that promote the development and evolution of these …

A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …