Immunoinformatics and epitope prediction in the age of genomic medicine

Abstract

Immunoinformatics involves the application of computational methods to immunological problems. Prediction of B- and T-cell epitopes has long been the focus of immunoinformatics, given the potential translational implications, and many tools have been developed. With the advent of next-generation sequencing (NGS) methods, an unprecedented wealth of information has become available that requires more-advanced immunoinformatics tools. Based on information from whole-genome sequencing, exome sequencing and RNA sequencing, it is possible to characterize with high accuracy an individual's human leukocyte antigen (HLA) allotype (i.e., the individual set of HLA alleles of the patient), as well as changes arising in the HLA ligandome (the collection of peptides presented by the HLA) owing to genomic variation. This has allowed new opportunities for translational applications of epitope prediction, such as epitope-based design of prophylactic and therapeutic vaccines, and personalized cancer immunotherapies. Here, we review a wide range of immunoinformatics tools, with a focus on B- and T-cell epitope prediction. We also highlight fundamental differences in the underlying algorithms and discuss the various metrics employed to assess prediction quality, comparing their strengths and weaknesses. Finally, we discuss the new challenges and opportunities presented by high-throughput data-sets for the field of epitope prediction.

Fig. 1

Generating predictions from data. a Evaluation of the predictor using cross-validation: first the data-set is split into k-folds (k = 5). Next, five predictors are trained on four folds and validated on the one left out. Evaluation can be, for example, a receiver operating characteristic (ROC) curve analysis. Finally, an average ROC curve is generated. b Training of the final predictor: after evaluation, the final predictor is trained on the complete data-set

Fig. 2

Antigen processing pathways. Top: HLA class I pathway — the endogenous antigen is cleaved by the proteasome into peptides. These peptides are transported into the endoplasmic reticulum (ER) by the TAP and become bound to HLA class I. The HLA–ligand complex is transported in a vesicle to the cell surface and can be recognized by the TCR on CD8⁺ T cells. Bottom: HLA class II pathway — the exogenous antigen is taken up into the cell, digested into peptides and bound to HLA class II in an endosome. The HLA–ligand complex is transported in a vesicle to the cell surface and can be recognized by the TCR on CD4⁺ T cells. HLA human leukocyte antigen, TAP transporter associated with antigen processing, TCR T-cell receptor