Major Histocompatibility Complex Presentation Research Articles

RLpMIEC: High-Affinity Peptide Generation Targeting Major Histocompatibility Complex-I Guided and Interpreted by Interaction Spectrum-Navigated Reinforcement Learning.

Major histocompatibility complex (MHC) plays a vital role in presenting epitopes (short peptides from pathogenic proteins) to T-cell receptors (TCRs) to trigger the subsequent immune responses. Vaccine design targeting MHC generally aims to find epitopes with a high binding affinity for MHC presentation. Nevertheless, to find novel epitopes usually requires high-throughput screening of bulk peptide database, which is time-consuming, labor-intensive, more unaffordable, and very expensive. Excitingly, the past several years have witnessed the great success of artificial intelligence (AI) in various fields, such as natural language processing (NLP, e.g., GPT-4), protein structure prediction and engineering (e.g., AlphaFold2), and so on. Therefore, herein, we propose a deep reinforcement-learning (RL)-based generative algorithm, RLpMIEC, to quantitatively design peptide targeting MHC-I systems. Specifically, RLpMIEC combines the energetic spectrum (namely, the molecular interaction energy component, MIEC) based on the peptide-MHC interaction and the sequence information to generate peptides with strong binding affinity and precise MIEC spectra to accelerate the discovery of candidate peptide vaccines. RLpMIEC performs well in all the generative capability evaluations and can generate peptides with strong binding affinities and precise MIECs and, moreover, with high interpretability, demonstrating its powerful capability in participation for accelerating peptide-based vaccine development.

Precision Neoantigen Discovery Using Large-Scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

Major histocompatibility complex (MHC)–bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass spectrometry–based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past 2 decades. However, improvement in the accuracy of prediction algorithms is needed for clinical applications like the development of personalized cancer vaccines, the discovery of biomarkers for response to immunotherapies, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic Human Leukocyte Antigen (HLA) Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA allele to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.17-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

Subcellular location of source proteins improves prediction of neoantigens for immunotherapy.

Antigen presentation via the major histocompatibility complex (MHC) is essential for anti-tumor immunity. However, the rules that determine which tumor-derived peptides will be immunogenic are still incompletely understood. Here, we investigated whether constraints on peptide accessibility to the MHC due to protein subcellular location are associated with peptide immunogenicity potential. Analyzing over 380,000 peptides from studies of MHC presentation and peptide immunogenicity, we find clear spatial biases in both eluted and immunogenic peptides. We find that including parent protein location improves the prediction of peptide immunogenicity in multiple datasets. In human immunotherapy cohorts, the location was associated with a neoantigen vaccination response, and immune checkpoint blockade responders generally had a higher burden of neopeptides from accessible locations. We conclude that protein subcellular location adds important information for optimizing cancer immunotherapies.

Phosphosite-dependent presentation of dual phosphorylated peptides by MHC class I molecules

SummaryPhosphopeptides presented by major histocompatibility complex (MHC) class I have been regarded as a pivotal type of cancer neoantigens that are recognized by T cells. The structural basis of single-phosphorylated peptide presentation has been well studied. Diphosphorylation with one interval between two sites is one of the prevalent forms of multisite-phosphorylated peptides. Herein, we determined the molecular basis of presentation of two P4/P6 double pS-containing peptides by HLA-B27 and compared them with unmodified and single-phosphorylated peptide complexes. These data clarified not only the HLA allele-specific presentation of phosphopeptides by MHC class I molecules but also the cooperativity of peptide conformation within P4 and P6 phosphorylation sites. The phosphorylation of P6 site can influence the binding mode of P4 phosphorylated site to HLA-B27. And we found the diphospho-dependent attenuated effect of peptide binding affinity. This study provides insights into the MHC presentation features of diphosphopeptides, which is different from monophosphopeptides.

An Integrated Genomic, Proteomic, and Immunopeptidomic Approach to Discover Treatment-Induced Neoantigens.

All nucleated mammalian cells express major histocompatibility complex (MHC) proteins that present peptides on cell surfaces for immune surveillance. These MHC-presented peptides (pMHC) are necessary for directing T-cell responses against cells harboring non-self antigens derived from pathogens or from somatic mutations. Alterations in tumor-specific antigen repertoires — particularly novel MHC presentation of mutation-bearing peptides (neoantigens) — can be potent targets of anti-tumor immune responses. Here we employed an integrated genomic and proteomic antigen discovery strategy aimed at measuring how interferon gamma (IFN-γ) alters antigen presentation, using a human lymphoma cell line, GRANTA-519. IFN-γ treatment resulted in 126 differentially expressed proteins (2% of all quantified proteins), which included components of antigen presentation machinery and interferon signaling pathways, and MHC molecules themselves. In addition, several proteasome subunits were found to be modulated, consistent with previous reports of immunoproteasome induction by IFN-γ exposure. This finding suggests that a modest proteomic response to IFN-γ could create larger alteration to cells’ antigen/epitope repertoires. Accordingly, MHC immunoprecipitation followed by mass spectrometric analysis of eluted peptide repertoires revealed exclusive signatures of IFN-γ induction, with 951 unique peptides reproducibly presented by MHC-I and 582 presented by MHC-II. Furthermore, an additional set of pMHCs including several candidate neoantigens, distinguished control and the IFN-γ samples by their altered relative abundances. Accordingly, we developed a classification system to distinguish peptides which are differentially presented due to altered expression from novel peptides resulting from changes in antigen processing. Taken together, these data demonstrate that IFN-γ can re-shape antigen repertoires by identity and by abundance. Extending this approach to models with greater clinical relevance could help develop strategies by which immunopeptide repertoires are intentionally reshaped to improve endogenous or vaccine-induced anti-tumor immune responses and potentially anti-viral immune responses.

MHC Class I Loss in Triple-negative Breast Cancer: A Potential Barrier to PD-1/PD-L1 Checkpoint Inhibitors.

Suppression of the immune system is intimately linked to the development and progression of malignancy, and immune modulating treatment options have shown promise in a variety of tumor types, including some triple-negative breast cancers (TNBC). The most dramatic therapeutic success has been seen with immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) and its ligand, PD-L1. Difficulty remains, however, in appropriate patient selection for treatment, as many PD-L1-positive cancers fail to show durable responses to PD-1/PD-L1 inhibition. Checkpoint inhibitor targeting of the adaptive immune response relies on the presence of major histocompatibility complex (MHC) class I molecules on the tumor cell surface for tumor antigen presentation. MHC class I loss has been previously described in breast cancer and represents a putative mechanism of immunotherapeutic resistance in this tumor type. One hundred seventeen invasive primary breast carcinomas with a range of histologic subtypes were evaluated on tissue microarrays containing formalin-fixed paraffin-embedded tissue. Loss of MHC class I expression was common among breast cancers, with greater than half of cases demonstrating either subclonal or diffuse loss. Fifty-nine percent of TNBC demonstrated loss of MHC class I, including 46% of those meeting the Food and Drug Administration-approved threshold of 1% for tumor-associated immune cell PD-L1 expression. MHC class I loss was particularly common in the apocrine subtype of TNBC (78%). MHC class I's employment as a predictive biomarker should be considered, as its loss may represent a barrier to successful enhancement of the antitumor adaptive immune response by PD-1/PD-L1 inhibition.

Precision Neoantigen Discovery Using Large-scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass-spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past two decades. However, improvement in the sensitivity and specificity of prediction algorithms is needed for clinical applications such as the development of personalized cancer vaccines, the discovery of biomarkers for response to checkpoint blockade, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic HLA Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA alleles to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC-binding pocket diversity in the training data and extend allelic coverage in under profiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.15-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

MHC Restriction: Where Are We Now?

MHC Restriction: Where Are We Now?

PTuneos: prioritizing tumor neoantigens from next-generation sequencing data

BackgroundCancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface in complex with major histocompatibility complex (MHC) class I proteins for recognition by cytotoxic T cells. Accurate and rapid identification of neoantigens play a pivotal role in cancer immunotherapy. Although several in silico tools for neoantigen prediction have been presented, limitations of these tools exist.ResultsWe developed pTuneos, a computational pipeline for prioritizing tumor neoantigens from next-generation sequencing data. We tested the performance of pTuneos on the melanoma cancer vaccine cohort data and tumor-infiltrating lymphocyte (TIL)-recognized neopeptide data. pTuneos is able to predict the MHC presentation and T cell recognition ability of the candidate neoantigens, and the actual immunogenicity of single-nucleotide variant (SNV)-based neopeptides considering their natural processing and presentation, surpassing the existing tools with a comprehensive and quantitative benchmark of their neoantigen prioritization performance and running time. pTuneos was further tested on The Cancer Genome Atlas (TCGA) cohort data as well as the melanoma and non-small cell lung cancer (NSCLC) cohort data undergoing checkpoint blockade immunotherapy. The overall neoantigen immunogenicity score proposed by pTuneos is demonstrated to be a powerful and pan-cancer marker for survival prediction compared to traditional well-established biomarkers.ConclusionsIn summary, pTuneos provides the state-of-the-art one-stop and user-friendly solution for prioritizing SNV-based candidate neoepitopes, which could help to advance research on next-generation cancer immunotherapies and personalized cancer vaccines. pTuneos is available at https://github.com/bm2-lab/pTuneos, with a Docker version for quick deployment at https://cloud.docker.com/u/bm2lab/repository/docker/bm2lab/ptuneos.

Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

Despite improved methods for MHC affinity prediction, the vast majority of computationally predicted tumor neoantigens are not immunogenic experimentally, indicating that high-quality neoantigens are beyond current algorithms to discern. To enrich for neoantigens with the greatest likelihood of immunogenicity, we developed an analytic method to parse neoantigen quality through rational biological criteria across five clinical datasets for 318 cancer patients. We explored four quality metrics, including analysis of dissimilarity to the non-mutated proteome that was predictive of peptide immunogenicity. In patient tumors, neoantigens with high dissimilarity were unique, enriched for hydrophobic sequences, and correlated with survival after PD-1 checkpoint therapy in patients with non-small cell lung cancer independent of predicted MHC affinity. We incorporated our neoantigen quality analysis methodology into an open-source tool, antigen.garnish, to predict immunogenic peptides from bulk computationally predicted neoantigens for which the immunogenic "hit rate" is currently low.

Human Colorectal Carcinoma Infiltrating B Lymphocytes Are Active Secretors of the Immunoglobulin Isotypes A, G, and M.

Despite the importance of tumor infiltrating B cells (TiBc) in immunological circuits, their functional role is scarcely investigated. Here, we analyzed immunoglobulin (Ig) secretion of the subtypes IgA, IgG, and IgM of TiBc from freshly resected primary and secondary colorectal carcinomas (CRC) by FluoroSpot (n = 30 CRC) directly ex vivo. High, intermediate, and low secretion was observed in 33%, 37%, and 30% of the tumors for IgA; in 10%, 27%, and 63% for IgG; and in 21%, 36%, and 50% for IgM, respectively. These ex vivo data validate our previous findings: Most TiBc present in the CRC microenvironment are functional since they produce and actively secrete Ig (IgA > IgG > IgM). Of note, the presence of major histocompatibility complex (MHC) class II expressing cells in the tumor micromilieu only correlated with IgG secretion (p = 0.0004). Supporting recent findings in several other tumor entities, TiBc in CRC thus likely can contribute to tumor control in a dual role of sole antigen-presentation and additionally anti-tumoral Ig-production.

The presentation of neuroendocrine self-peptides in the thymus: an essential event for individual life and vertebrate survival.

Confirming Burnet's early hypothesis, elimination of self‐reactive T cells in the thymus was demonstrated in the late 1980s, and an important question immediately arose about the nature of the self‐peptides expressed in the thymus. Many genes encoding neuroendocrine‐related and tissue‐restricted antigens (TRAs) are transcribed in thymic epithelial cells (TECs). They are then processed for presentation by proteins of the major histocompatibility complex (MHC) expressed by TECs and thymic dendritic cells. MHC presentation of self‐peptides in the thymus programs self‐tolerance by two complementary mechanisms: (1) negative selection of self‐reactive “forbidden” T cell clones starting already in fetal life, and (2) generation of self‐specific thymic regulatory T lymphocytes (tTreg cells), mainly after birth. Many studies, including the discovery of the transcription factors autoimmune regulator (AIRE) and fasciculation and elongation protein zeta family zinc finger (FEZF2), have shown that a defect in thymus central self‐tolerance is the earliest event promoting autoimmunity. AIRE and FEZF2 control the level of transcription of many neuroendocrine self‐peptides and TRAs in the thymic epithelium. Furthermore, AIRE and FEZF2 mutations are associated with the development of autoimmunity in peripheral organs. The discovery of the intrathymic presentation of self‐peptides has revolutionized our knowledge of immunology and is opening novel avenues for prevention/treatment of autoimmunity.

Autophagy proteins influence endocytosis for MHC restricted antigen presentation.

T cells of the adaptive immune system monitor protein degradation products via their presentation on major histocompatibility complex (MHC) molecules to recognize infected cells. Both macroautophagy and endocytosis target intra- and extracellular constituents, respectively, for lysosomal degradation. This results in antigen processing for MHC presentation and influences the trafficking of MHC molecules. This review will discuss recent evidence that the molecular machinery of macroautophagy regulates also endocytosis at the level of phagosome maturation and cell membrane internalization. These non-canonical functions of this machinery affect both MHC class I and II restricted antigen presentation to CD8+ and CD4+ T cells, respectively, and should be harnessed to improve immune responses against infectious diseases and cancer.

Expression and Regulation of Thymic Stromal Lymphopoietin and Thymic Stromal Lymphopoietin Receptor Heterocomplex in the Innate-Adaptive Immunity of Pediatric Asthma.

Asthma is a chronic inflammatory disease affecting the airway, and it is characterized by a wheezing breathing sound, variable airflow obstruction and the presence of inflammatory cells in the submucosa of the bronchi. Viral infection, pollutants and sensitivity to aeroallergens damage the epithelium from childhood, which causes asthma. The pathogenesis of asthma includes pathways of innate stimulation by environmental microbes and irritant pathogens. Damaged epithelial cells produce thymic stromal lymphopoietin (TSLP) and stimulate myeloid dendritic cell maturation through the thymic stromal lymphopoietin receptor (TSLPR) heterocomplex. TSLP-activated myeloid dendritic cells promote naive CD4+ T cells to differentiate into T helper type 2 (Th2) phenotype CD4+ T cells. Re-exposure to allergens or environmental stimuli causes an adaptive immune response. TSLP-activated dendritic cells expressing the OX40 ligand (OX40L; CD252) trigger naive CD4+ T cells to differentiate into inflammatory Th2 effector cells secreting the cytokines interleukin-4, 5, 9, and 13 (IL-4, IL-5, IL-9 and IL-13), and the dendritic cells (DCs) promote the proliferation of allergen-specific Th2 memory cells. Allergen presentation by Th2 cells through its interaction with their receptors in the presence of major histocompatibility complex (MHC) class II on B cells and through costimulation involving CD40 and CD40L interactions results in immunoglobulin class switching from IgM to IgE. DCs and other blood cell subsets express the TSLPR heterocomplex. The regulatory mechanism of the TSLPR heterocomplex on these different cell subsets remains unclear. The TSLPR heterocomplex is composed of the IL-7Rα chain and TSLPR chain. Moreover, two isoforms of TSLP, short isoform TSLP (sfTSLP) and long isoform TSLP (lfTSLP), have roles in atopic and allergic development. Identifying and clarifying the regulation of TSLPR and IL-7Rα in pediatric asthma are still difficult, because the type of blood cell and the expression for each blood cell in different stages of atopic diseases are poorly understood. We believe that further integrated assessments of the regulation mechanism of the TSLP–TSLPR heterocomplex axis in vitro and in vivo can provide a faster and earlier diagnosis of pediatric asthma and promote the development of more effective preventive strategies at the onset of allergies.

Detection of major histocompatibility complex molecules in processed allogeneic bone blocks for use in alveolar ridge reconstruction

Because processed allogenic bone blocks contain remnants of cells and other organic material, the present study examined the putative presence of major histocompatibility complex (MHC) molecules in protein extracts derived from processed allogeneic bone blocks. Protein content and the immunogenic potential of 3 different processed allografts (Osteograft, DIZG, Berlin, Germany; Caput femoris, DIZG, Berlin, Germany; Human Spongiosa, Charité Tissue Bank, Berlin, Germany) were assessed by protein extraction and analysis of the presence of MHC class 1 and 2 molecules prior to grafting. MHC concentration was measured by using enzyme-linked immunosorbent assay. Protein content in the allograft materials varied between 0.87 and 1.61 µg protein/mg. In the allograft Human Spongiosa, no MHC was detected, whereas in the allogeneic bone blocks Osteograft and Caput femoris MHC 1 (0.04-0.037 ng/mg graft material) and in Osteograft MHC class 2 molecules were detectable. The results of the present study suggest that despite thorough processing, a potential antigenicity of allografts is not eliminated. MHC molecules in allografts may sensitize the immune system.

P.201 - Differential type I and type II interferon signatures in primary inflammatory/dysimmune myopathies

Primary inflammatory/dysimmune myopathies (PIDM) include (i) polymyositis (PM)/inclusion body myositis (IBM), (ii) dermatomyositis (DM), (iii) necrotizing autoimmune myopathy, and (iv) overlap myositis (OM) . Type I α/β interferon signature was proposed as a characteristic feature of DM . Since OM and IBM differ from other PIDM by the presence of major histocompatibility complex (MHC)-2 expression by myofibers, we hypothesized that they are characterized by interferon (IFN)γ-mediated inflammation. To test this hypothesis, we evaluated by qPCR the expression of IFNγ, six IFNγ–induced genes (HLA-DM, -DO, -DP, -DR, CIITA, GBP2), and IFNα-induced gene ISG15 in muscle biopsy samples from patients with IBM (n = 10), DM (n = 10), NAM (n = 10), antisynthetase myositis (ASM, n = 10), and normal muscle (n = 10). Muscle IFNγ expression was found increased x50 in ASM and x80 in IBM compared to control, that of CIITA x4 and x3 (respectively) as well of HLA-DR (x5 and x8) and HLA-DM (x16 and x15). None of these genes were overexpressed in DM and NAM. ISG15 was increased x300 in DM, but not in other conditions. Our results confirmed that DM differed from other PIDM by its elective interferon α/β signature, while ASM and IBM were found associated with IFNγ signature.

Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens.

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells 1–7. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle cell lymphomas using an integrated genomic and proteomic strategy that interrogates tumor antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin (Ig) heavy or light chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-Ig somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC-II. We isolated circulating CD4 T-cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification and exome sequencing is an effective platform to uncover tumor neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

Autophagy proteins in antigen processing for presentation on MHC molecules.

Autophagy describes catabolic pathways that deliver cytoplasmic constituents for lysosomal degradation. Since major histocompatibility complex (MHC) molecules sample protein degradation products and present them to T cells for adaptive immunity, it is maybe not too surprising that autophagy contributes to this protein antigen processing for MHC presentation. However, the recently recognized breath of pathways, by which autophagy contributes to MHC antigen processing, is exciting. Macroautophagy does not only seem to deliver intracellular but facilitates also extracellular antigen processing by lysosomal hydrolysis for MHC class II presentation. Moreover, even MHC class I molecules that usually display proteasomal products are regulated by macroautophagy, probably using a pool of these molecules outside the endoplasmic reticulum, where MHC class I molecules are loaded with peptide during canonical MHC class I antigen processing. This review aims to summarize these recent developments and point out gaps of knowledge, which should be filled by further investigation, in order to harness the different antigen-processing pathways via autophagy for vaccine improvement.

Coevolution of T-cell receptors with MHC and non-MHC ligands.

The structure and amino acid diversity of the T-cell receptor (TCR), similar in nature to that of Fab portions of antibodies, would suggest that these proteins have a nearly infinite capacity to recognize antigen. Yet all currently defined native T cells expressing an α and β chain in their TCR can only sense antigen when presented in the context of a major histocompatibility complex (MHC) molecule. This MHC molecule can be one of many that exist in vertebrates, presenting small peptide fragments, lipid molecules, or small molecule metabolites. Here we review the pattern of TCR recognition of MHC molecules throughout a broad sampling of species and T-cell lineages and also touch upon T cells that do not appear to require MHC presentation for their surveillance function. We review the diversity of MHC molecules and information on the corresponding T-cell lineages identified in divergent species. We also discuss TCRs with structural domains unlike that of conventional TCRs of mouse and human. By presenting this broad view of TCR sequence, structure, domain organization, and function, we seek to explore how this receptor has evolved across time and been selected for alternative antigen-recognition capabilities in divergent lineages.

Epstein-Barr virus-encoded EBNA1 and ZEBRA: targets for therapeutic strategies against EBV-carrying cancers.

The EBV-encoded EBNA1 was first discovered 40 years ago, approximately 10 years after the presence of EBV had been demonstrated in Burkitt's lymphoma cells. It took another 10 years before the functions of EBNA1 in maintaining the viral genome were revealed, and it has since been shown to be an essential viral factor expressed in all EBV-carrying cells. Apart from serving to maintain the viral episome and to control viral replication and gene expression, EBNA1 also harbours a cis-acting mechanism that allows virus-carrying host cells to evade the immune system. This relates to a particular glycine-alanine repeat (GAr) within EBNA1 that has the capacity to suppress antigen presentation to the major histocompatibility complex (MHC) class I pathway. We discuss the role of the GAr sequence at the level of mRNA translation initiation, rather than at the protein level, as at least part of the mechanism to avoid MHC presentation. Interfering with this mechanism has become the focus of the development of immune-based therapies against EBV-carrying cancers, and some lead compounds that affect translation of GAr-carrying mRNAs have been identified. In addition, we describe the EBV-encoded ZEBRA factor and the switch from the latent to the lytic cycle as an alternative virus-specific target for treating EBV-carrying cancers. Understanding the molecular mechanisms of how EBNA1 and ZEBRA interfere with cellular pathways not only opens new therapeutic approaches but continues to reveal new cell-biological insights on the interplay between host and virus. This review is a tale of discoveries relating to how EBNA1 and ZEBRA have emerged as targets for specific cancer therapies against EBV-carrying diseases, and serves as an illustration of how mRNA translation can play roles in future immune-based strategies to target viral disease.