Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules

Relevance of mutation-derived neoantigens and non-classical antigens for anticancer therapies

Efficacy of cancer immunotherapies relies on correct recognition of tumor antigens by lymphocytes, eliciting thus functional responses capable of eliminating tumor cells. Therefore, important efforts have been carried out in antigen identification, with the aim of understanding mechanisms of response to immunotherapy and to design safer and more efficient strategies. In addition to classical tumor-associated antigens identified during the last decades, implementation of next-generation sequencing methodologies is enabling the identification of neoantigens (neoAgs) arising from mutations, leading to the development of new neoAg-directed therapies. Moreover, there are numerous non-classical tumor antigens originated from other sources and identified by new methodologies. Here, we review the relevance of neoAgs in different immunotherapies and the results obtained by applying neoAg-based strategies. In addition, the different types of non-classical tumor antigens and the best approaches for their identification are described. This will help to increase the spectrum of targetable molecules useful in cancer immunotherapies.

Identification and relative abundance of naturally presented and cross-reactive influenza A virus MHC class I-restricted T cell epitopes

Cytotoxic T lymphocytes are key for controlling viral infection. Unravelling CD8+ T cell-mediated immunity to distinct influenza virus strains and subtypes across prominent HLA types is relevant for combating seasonal infections and emerging new variants. Using an immunopeptidomics approach, naturally presented influenza A virus-derived ligands restricted to HLA-A*24:02, HLA-A*68:01, HLA-B*07:02, and HLA-B*51:01 molecules were identified. Functional characterization revealed multifunctional memory CD8+ T cell responses for nine out of sixteen peptides. Peptide presentation kinetics was optimal around 12 h post infection and presentation of immunodominant epitopes shortly after infection was not always persistent. Assessment of immunogenic epitopes revealed that they are highly conserved across the major zoonotic reservoirs and may contain a single substitution in the vicinity of the anchor residues. These findings demonstrate how the identified epitopes promote T cell pools, possibly cross-protective in individuals and can be potential targets for vaccination.

Energy landscapes of peptide-MHC binding

Molecules of the Major Histocompatibility Complex (MHC) present short protein fragments on the cell surface, an important step in T cell immune recognition. MHC-I molecules process peptides from intracellular proteins; MHC-II molecules act in antigen-presenting cells and present peptides derived from extracellular proteins. Here we show that the sequence-dependent energy landscapes of MHC-peptide binding encode class-specific nonlinearities (epistasis). MHC-I has a smooth landscape with global epistasis; the binding energy is a simple deformation of an underlying linear trait. This form of epistasis enhances the discrimination between strong-binding peptides. In contrast, MHC-II has a rugged landscape with idiosyncratic epistasis: binding depends on detailed amino acid combinations at multiple positions of the peptide sequence. The form of epistasis affects the learning of energy landscapes from training data. For MHC-I, a low-complexity problem, we derive a simple matrix model of binding energies that outperforms current models trained by machine learning. For MHC-II, higher complexity prevents learning by simple regression methods. Epistasis also affects the energy and fitness effects of mutations in antigen-derived peptides (epitopes). In MHC-I, large-effect mutations occur predominantly in anchor positions of strong-binding epitopes. In MHC-II, large effects depend on the background epitope sequence but are broadly distributed over the epitope, generating a bigger target for escape mutations due to loss of presentation. Together, our analysis shows how an energy landscape of protein-protein binding constrains the target of escape mutations from T cell immunity, linking the complexity of the molecular interactions to the dynamics of adaptive immune response.

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.

Innovations Toward Immunopeptidomics

Over the past 30 years, immunopeptidomics has grown alongside improvements in mass spectrometry technology, genomics, transcriptomics, T cell receptor sequencing, and immunological assays to identify and characterize the targets of activated T cells. Together, multiple research groups with expertise in immunology, biochemistry, chemistry, and peptide mass spectrometry have come together to enable the isolation and sequence identification of endogenous major histocompatibility complex (MHC)-bound peptides. The idea to apply highly sensitive mass spectrometry techniques to study the landscape of peptide antigens presented by cell surface MHCs was innovative and continues to be successfully used and improved upon to deepen our understanding of how peptide antigens are processed and presented to T cells. Multiple research groups were involved in this bringing immunopeptidomics to the forefront of translational research, and we will highlight the contributions of one of the earliest developers, Professor Donald F. Hunt, and his research group at the University of Virginia. The Hunt laboratory applied cutting edge mass spectroscopy-based immunopeptidomics to study cancer, autoimmunity, transplant rejection, and infectious diseases. Across these diverse research areas, the Hunt laboratory and collaborators would characterize previously unknown MHC peptide-binding motifs and identify immunologically active antigens using ultra sensitive mass spectrometry techniques. Amazingly, many of the MHC-bound peptide antigens discovered in collaborations with the Hunt laboratory were sequenced by mass spectrometry before the completion of the human genome using manual de novo sequencing. In this perspective article, we will chronicle the work of the Hunt laboratory and their many collaborators that would be a major part of the foundation for mass spectrometry-based immunopeptidomics and its application to immunology research.

Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program's strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.

CRISPR-Cas9 screening reveals a distinct class of MHC-I binders with precise HLA-peptide recognition

Human leukocyte antigen (HLA) class-I molecules present fragments of the cellular proteome to the T cell receptor (TCR) of cytotoxic T cells to control infectious diseases and cancer. The large number of combinations of HLA class-I allotypes and peptides allows for highly specific and dedicated low-affinity interactions to a diverse array of TCRs and natural killer (NK) cell receptors. Whether the divergent HLA class-I peptide complex is exclusive for interactions with these proteins is unknown. Using genome-wide CRISPR-Cas9 activation and knockout screens, we identified peptide-specific HLA-C∗07 combinations that can interact with the surface molecules CD55 and heparan sulfate. These interactions closely resemble the HLA class-I interaction with the TCR regarding both the affinity range and the specificity of the peptide and HLA allele. These findings indicate that various proteins can specifically bind HLA class-I peptide complexes due to their polymorphic nature, which suggests there are more interactions like the ones we describe here.

Principles of peptide selection by the transporter associated with antigen processing

Our ability to fight pathogens relies on major histocompatibility complex class I (MHC-I) molecules presenting diverse antigens on the surface of diseased cells. The transporter associated with antigen processing (TAP) transports nearly the entire repertoire of antigenic peptides into the endoplasmic reticulum for MHC-I loading. How TAP transports peptides specific for MHC-I is unclear. In this study, we used cryo-EM to determine a series of structures of human TAP, both in the absence and presence of peptides with various sequences and lengths. The structures revealed that peptides of eight or nine residues in length bind in a similarly extended conformation, despite having little sequence overlap. We also identified two peptide-anchoring pockets on either side of the transmembrane cavity, each engaging one end of a peptide with primarily main chain atoms. Occupation of both pockets results in a global conformational change in TAP, bringing the two halves of the transporter closer together to prime it for isomerization and ATP hydrolysis. Shorter peptides are able to bind to each pocket separately but are not long enough to bridge the cavity to bind to both simultaneously. Mutations that disrupt hydrogen bonds with the N and C termini of peptides almost abolish MHC-I surface expression. Our findings reveal that TAP functions as a molecular caliper that selects peptides according to length rather than sequence, providing antigen diversity for MHC-I presentation.

Human Leukocyte Antigen-Allelic Variations May Influence the Age at Cancer Diagnosis in Lynch Syndrome

Lynch syndrome (LS) is an inherited cancer predisposition disorder associated with an elevated risk of developing various solid cancers, but mostly colorectal cancer (CRC). Despite having the same germline pathogenic variant (PV) in one of the mis-match repair genes or the EPCAM gene, Lynch syndrome variant heterozygotes (LSVH) exhibit a remarkable phenotypic variability in the risk of developing cancer. The role of human leukocyte antigen (HLA) in modifying cancer development risk prompted our hypothesis into whether HLA variations act as potential genetic modifiers influencing the age at cancer diagnosis in LSVH. To investigate this, we studied a unique cohort of 426 LSVH carrying the same germline PV in the hMLH1 gene (MLH1:c.1528C > T) in South Africa. We intuitively selected 100 LSVH with the greatest diversity in age at cancer diagnosis (N = 80) and the oldest cancer unaffected LSVH (N = 20) for a high-throughput HLA genotyping of 11 HLA class I and class II loci using the shotgun next-generation sequencing (NGS) technique on the Illumina MiSeq platform. Statistical analyses employed Kaplan-Meier survival analyses with log-rank tests, and Cox proportional hazards using binned HLA data to minimize type I error. Significant associations were observed between young age at cancer diagnosis and HLA-DPB1*04:02 (mean age: 37 y (25-50); hazard ratio (HR) = 3.37; corrected p-value (q) = 0.043) as well as HLA-DPB1 binned alleles (including HLA-DPB1*09:01, HLA-DPB1*10:01, HLA-DPB1*106:01, HLA-DPB1*18:01, HLA-DPB1*20:01, HLA-DPB1*26:01, HLA-DPB1*28:01, HLA-DPB1*296:01, and HLA-DPB1*55:01) (mean age: 37 y (17-63); HR = 2.30, q = 0.045). The involvement of HLA-DPB1 alleles in the age at cancer diagnosis may highlight the potential role of HLA class II in the immune response against cancer development in LSVH. When validated in a larger cohort, these high-risk HLA-DPB1 alleles could be factored into cancer risk prediction models for personalized cancer screening in LSVH.

In silico design of high-affinity antigenic peptides for HLA-B44

Cancer cell-killing by CD8+ T cells demands effective tumor antigen presentation by human leukocyte antigen class I (HLA-I) molecules. Screening and designing highly immunogenic neoantigens require quantitative computations to reliably predict HLA-peptide binding affinities. Here, with all-atom molecular dynamics (MD) simulations and free energy perturbation (FEP) methods, we design a collection of antigenic peptide candidates through in silico mutagenesis studies on immunogenic neoantigens, yielding enhanced binding affinities to HLA-B*44:02. In-depth structural dissection shows that introducing positively charged residues such as arginine to position 6 or lysine to position 7 of the candidates triggers conformational shifts in both peptides and the antigen-binding groove of the HLA, following the "induced-fit" mechanism. Enhancement in binding affinities compared to the wild-type was found in three out of five mutated candidates. The HLA pocket, capable of accommodating positively charged residues in positions from 5 to 7, is designated as the "dynamic pocket". Taken together, we showcase an effective structure-based binding affinity optimization framework for antigenic peptides of HLA-B*44:02 and underscore the importance of dynamic nature of the antigen-binding groove in concert with the anchoring motifs. This work provides structural insights for rational design of favorable HLA-peptide bindings and future developments in neoantigen-based therapeutics.

Characterizing and forecasting neoantigens-resulting from MUC mutations in COAD

BACKGROUND

The treatment for colon adenocarcinoma (COAD) faces challenges in terms of immunotherapy effectiveness due to multiple factors. Because of the high tumor specificity and immunogenicity, neoantigen has been considered a pivotal target for cancer immunotherapy. Therefore, this study aims to identify and predict the potential tumor antigens of MUC somatic mutations (MUCmut) in COAD.

METHODS

Three databases of TCGA, TIMER2.0, and cBioPortal were used for a detailed evaluation of the association between MUCmut and multi-factors like tumor mutation burden (TMB), microsatellite instability (MSI), prognosis, and the tumor microenvironment within the context of total 2242 COAD patients. Next, TSNAdb and the differential agretopicity index (DAI) were utilized to predict high-confidence neopeptides for MUCmut based on 531 COAD patients' genomic information. DAI was calculated by subtraction of its predicted HLA binding affinity of the MUCmut peptide from the corresponding wild-type peptide.

RESULTS

The top six mutation frequencies (14 to 2.9%) were from MUC16, MUC17, MUC5B, MUC2, MUC4 and MUC6. COAD patients with MUC16 and MUC4 mutations had longer DFS and PFS. However, patients with MUC13 and MUC20 mutations had shorter OS. Patients with the mutation of MUC16, MUC5B, MUC2, MUC4, and MUC6 exhibited higher TMB and MSI. Moreover, these mutations from the MUC family were associated with the infiltration of diverse lymphocyte cells and the expression of immune checkpoint genes. Through TSNAdb 1.0/NetMHCpan v2.8, 452 single nucleotide variants (SNVs) of MUCmut peptides were identified. Moreover, through TSNAdb2.0/NetMHCpan v4.0, 57 SNVs, 1 Q-frame shift (TS), and 157 short insertions/deletions (INDELs) of MUCmut were identified. Finally, 10 high-confidence neopeptides of MUCmut were predicted by DAI.

CONCLUSIONS

Together, our findings establish the immunogenicity and therapeutic potential of mutant MUC family-derived neoantigens. Through combining the tools of TSNAdb and DAI, a group of novel MUCmut neoantigens were identified as potential targets for immunotherapy.

Multiple environmental antigens may trigger autoimmunity in psoriasis through T-cell receptor polyspecificity

Introduction

Psoriasis is a T-cell mediated autoimmune skin disease. HLA-C*06:02 is the main psoriasis-specific risk gene. Using a Vα3S1/Vβ13S1 T-cell receptor (TCR) from a lesional psoriatic CD8+ T-cell clone we had discovered that, as an underlying pathomechanism, HLA-C*06:02 mediates an autoimmune response against melanocytes in psoriasis, and we had identified an epitope from ADAMTS-like protein 5 (ADAMTSL5) as a melanocyte autoantigen. The conditions activating the psoriatic autoimmune response in genetically predisposed individuals throughout life remain incompletely understood. Here, we aimed to identify environmental antigens that might trigger autoimmunity in psoriasis because of TCR polyspecificity.

Methods

We screened databases with the peptide recognition motif of the Vα3S1/Vβ13S1 TCR for environmental proteins containing peptides activating this TCR. We investigated the immunogenicity of these peptides for psoriasis patients and healthy controls by lymphocyte stimulation experiments and peptide-loaded HLA-C*06:02 tetramers.

Results

We identified peptides from wheat, Saccharomyces cerevisiae, microbiota, tobacco, and pathogens that activated both the Vα3S1/Vβ13S1 TCR and CD8+ T cells from psoriasis patients. Using fluorescent HLA-C*06:02 tetramers loaded with ADAMTSL5 or wheat peptides, we find that the same CD8+ T cells may recognize both autoantigen and environmental antigens. A wheat-free diet could alleviate psoriasis in several patients.

Discussion

Our results show that due to TCR polyspecificity, several environmental antigens corresponding to previously suspected psoriasis risk conditions converge in the reactivity of a pathogenic psoriatic TCR and might thus be able to stimulate the psoriatic autoimmune response against melanocytes. Avoiding the corresponding environmental risk factors could contribute to the management of psoriasis.

Investigating Associations between HLA-DR Genotype, H. pylori Infection, and Anti-CagA IgA Seropositivity in a Turkish Gastritis Cohort

Helicobacter pylori (H. pylori) is associated with gastric inflammation and mucosal antibodies against its cytotoxin-associated gene A (CagA) are protective. Vaccine-elicited immunity against H. pylori requires MHC class II expression, indicating that CD4+ T cells are protective. We hypothesized that the HLA-DR genotypes in human populations include protective alleles that more effectively bind immunogenic CagA peptide fragments and susceptible alleles with an impaired capacity to present CagA peptides. We recruited patients (n = 170) admitted for gastroendoscopy procedures and performed high-resolution HLA-DRB1 typing. Serum anti-CagA IgA levels were analyzed by ELISA (23.2% positive) and H. pylori classified as positive or negative in gastric mucosal tissue slides (72.9% positive). Pearson Chi-square analysis revealed that H. pylori infection was significantly increased in DRB1*11:04-positive individuals (p = 0.027). Anti-CagA IgA was significantly decreased in DRB1*11:04 positive individuals (p = 0.041). In contrast, anti-CagA IgA was significantly increased in DRB1*03:01 positive individuals (p = 0.030). For these HLA-DRB1 alleles of interest, we utilized two in silico prediction methods to compare their capacity to present CagA peptides. Both methods predicted increased numbers of peptides for DRB1*03:01 than DRB1*11:04. In addition, both alleles preferred distinctively different CagA 15mer peptide sequences for high affinity binding. These observations suggest that DRB1*11:04 is a susceptible genotype with impaired CagA immunity, whereas DRB1*03:01 is a protective genotype that promotes enhanced CagA immunity.

The relationship between Listeria infections and host immune responses: Listeriolysin O as a potential target

Listeria monocytogenes (Lm), a foodborne bacterium, can infect people and has a high fatality rate in immunocompromised individuals. Listeriolysin O (LLO), the primary virulence factor of Lm, is critical in regulating the pathogenicity of Lm. This review concludes that LLO may either directly or indirectly activate a number of host cell viral pathophysiology processes, such as apoptosis, pyroptosis, autophagy, necrosis and necroptosis. We describe the invasion of host cells by Lm and the subsequent removal of Lm by CD8 T cells and CD4 T cells upon receipt of the LLO epitopes from major histocompatibility complex class I (MHC-I) and major histocompatibility complex class II (MHC-II). The development of several LLO-based vaccines that make use of the pore-forming capabilities of LLO and the immune response of the host cells is then described. Finally, we conclude by outlining the several natural substances that have been shown to alter the three-dimensional conformation of LLO by binding to particular amino acid residues of LLO, which reduces LLO pathogenicity and may be a possible pharmacological treatment for Lm.

An Overview of Peptides and Peptide Pools for Antigen-Specific Stimulation in T-Cell Assays

The analysis of antigen-specific T-cell responses has become routine in many laboratories. Functional T-cell assays like enzyme-linked-immuno-spot (ELISPOT), which depend on antigen-specific stimulation, increasingly use peptides to represent the antigen of interest. Besides single peptides, mixtures of peptides (peptide pools) are very frequently applied. Such peptide pools may, for example, represent entire proteins (with overlapping peptides covering a protein sequence) or include noncontiguous peptides such as a collection of T-cell-stimulating peptides. The optimum specification of single peptides or peptide pools for T-cell stimulation assays will depend on the purpose of the test, the target T-cell population, the availability of sample, requirements regarding reproducibility, and, last but not least, the available budget, to mention only the most important factors. Because of the way peptides are produced, they will always contain certain amounts of impurities such as peptides with deletions or truncated peptides, and there may be additional by-products of peptide synthesis. Optimized synthesis protocols as well as purification help reduce impurities that might otherwise cause false-positive assay results. However, specific requirements with respect to purity will vary depending on the purpose of an assay. Finally, storage conditions significantly affect the shelf life of peptides, which is relevant especially for longitudinal studies. The present book chapter addresses all of these aspects in detail. It should provide the researcher with all necessary background knowledge for making the right decisions when it comes to choosing, using, and storing peptides for ELISPOT and other T-cell stimulation assays.

In Silico Tools for Predicting Novel Epitopes

Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.

FAK suppresses antigen processing and presentation to promote immune evasion in pancreatic cancer

OBJECTIVE

Immunotherapy for the treatment of pancreatic ductal adenocarcinoma (PDAC) has shown limited efficacy. Poor CD8 T-cell infiltration, low neoantigen load and a highly immunosuppressive tumour microenvironment contribute to this lack of response. Here, we aimed to further investigate the immunoregulatory function of focal adhesion kinase (FAK) in PDAC, with specific emphasis on regulation of the type-II interferon response that is critical in promoting T-cell tumour recognition and effective immunosurveillance.

DESIGN

We combined CRISPR, proteogenomics and transcriptomics with mechanistic experiments using a KrasG12Dp53R172H mouse model of pancreatic cancer and validated findings using proteomic analysis of human patient-derived PDAC cell lines and analysis of publicly available human PDAC transcriptomics datasets.

RESULTS

Loss of PDAC cell-intrinsic FAK signalling promotes expression of the immunoproteasome and Major Histocompatibility Complex class-I (MHC-I), resulting in increased antigen diversity and antigen presentation by FAK-/- PDAC cells. Regulation of the immunoproteasome by FAK is a critical determinant of this response, optimising the physicochemical properties of the peptide repertoire for high affinity binding to MHC-I. Expression of these pathways can be further amplified in a STAT1-dependent manner via co-depletion of FAK and STAT3, resulting in extensive infiltration of tumour-reactive CD8 T-cells and further restraint of tumour growth. FAK-dependent regulation of antigen processing and presentation is conserved between mouse and human PDAC, but is lost in cells/tumours with an extreme squamous phenotype.

CONCLUSION

Therapies aimed at FAK degradation may unlock additional therapeutic benefit for the treatment of PDAC through increasing antigen diversity and promoting antigen presentation.

Regulation of DNA damage-induced HLA class I presentation

Immune checkpoint inhibitors (ICI) are cancer therapies that restore anti-tumor immunity; however, only a small percentage of patients have been completely cured by ICI alone. Multiple approaches in combination with other modalities have been used to improve the efficacy of ICI therapy. Among conventional cancer treatments, radiotherapy or DNA damage-based chemotherapy is a promising candidate as a partner of ICI because DNA damage signaling potentially stimulates immune activities turning the tumor's immune environment into hot tumors. Programmed death-ligand 1 (PD-L1) and human leukocyte antigen class I (HLA-I), which are immune ligands, regulate the balance of anti-tumor immunity in the tumor microenvironment. PD-L1 functions as a brake to suppress cytotoxic T cell activity, whereas HLA-I is an immune accelerator that promotes the downstream of the T cell signaling. Accumulating evidence has demonstrated that DNA damage enhances the presentation of HLA-I on the surface of damaged cells. However, it is unclear how signal transduction in DNA-damaged cells upregulates the presentation of HLA-I with antigens. Our recent study uncovered the mechanism underlying DNA damage-induced HLA-I presentation, which requires polypeptide synthesis through a pioneer round of translation. In this review, we summarize the latest overview of how DNA damage stimulates antigen production presented by HLA-I.

Thioamide Analogues of MHC I Antigen Peptides

Short, synthetic peptides that are displayed by major histocompatibility complex I (MHC I) can stimulate CD8 T cells in vivo to destroy virus-infected or cancer cells. The development of such peptides as vaccines that provide protective immunity, however, is limited by rapid proteolytic degradation. Introduction of unnatural amino acid residues can suppress MHC I antigen proteolysis, but the modified peptides typically display lower affinity for MHC I and/or diminished ability to activate CD8 T cells relative to native antigen. Here, we report a new strategy for modifying MHC I antigens to enhance resistance to proteolysis while preserving MHC I affinity and T cell activation properties. This approach, replacing backbone amide groups with thioamides, was evaluated in two well-characterized antigens presented by HLA-A2, a common human MHC I. For each antigen, singly modified thioamide analogues retained affinity for HLA-A2 and activated T cells specific for the native antigen, as measured via interferon-γ secretion. In each system, we identified a highly potent triply substituted thioamide antigen ("thio-antigen") that displayed substantial resistance to proteolytic cleavage. Collectively, our results suggest that thio-antigens may represent a general and readily accessible source of potent vaccine candidates that resist degradation.

Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design.

Immunogenicity risk assessment of synthetic peptide drugs and their impurities

Peptide drugs play an important part in medicine owing to their many therapeutic applications. Of the 80 peptide drugs approved for use in humans, at least five are now off-patent and are consequently being developed as generic alternatives to the originator products. To accelerate access to generic products, the FDA has proposed new regulatory pathways that do not require direct comparisons of generics to originators in clinical trials. The 'Abbreviated New Drug Application' (ANDA) pathway recommends that sponsors provide information on any new impurities in the generic drug, compared with the originator product, because the impurities can have potential to elicit unwanted immune responses owing to the introduction of T-cell epitopes. This review describes how peptide drug impurities can elicit unexpected immunogenicity and describes a framework for performing immunogenicity risk assessment of all types of bioactive peptide products. Although this report primarily focuses on generic peptides and their impurities, the approach might also be of interest for developers of novel peptide drugs who are preparing their products for an initial regulatory review.

Brain Hydrophobic Peptides Antagonists of Neurotoxic Amyloid β Peptide Monomers/Oligomers-Protein Interactions

Amyloid β (Aβ) oligomers have been linked to Alzheimer's disease (AD) pathogenesis and are the main neurotoxic forms of Aβ. This review focuses on the following: (i) the Aβ(1-42):calmodulin interface as a model for the design of antagonist Aβ peptides and its limitations; (ii) proteolytic degradation as the major source of highly hydrophobic peptides in brain cells; and (iii) brain peptides that have been experimentally demonstrated to bind to Aβ monomers or oligomers, Aβ fibrils, or Aβ plaques. It is highlighted that the hydrophobic amino acid residues of the COOH-terminal segment of Aβ(1-42) play a key role in its interaction with intracellular protein partners linked to its neurotoxicity. The major source of highly hydrophobic endogenous peptides of 8-10 amino acids in neurons is the proteasome activity. Many canonical antigen peptides bound to the major histocompatibility complex class 1 are of this type. These highly hydrophobic peptides bind to Aβ and are likely to be efficient antagonists of the binding of Aβ monomers/oligomers concentrations in the nanomolar range with intracellular proteins. Also, their complexation with Aβ will protect them against endopeptidases, suggesting a putative chaperon-like physiological function for Aβ that has been overlooked until now. Remarkably, the hydrophobic amino acid residues of Aβ responsible for the binding of several neuropeptides partially overlap with those playing a key role in its interaction with intracellular protein partners that mediates its neurotoxicity. Therefore, these latter neuropeptides are also potential candidates to antagonize Aβ peptides binding to target proteins. In conclusion, the analysis performed in this review points out that hydrophobic endogenous brain neuropeptides could be valuable biomarkers to evaluate the risk of the onset of sporadic AD, as well as for the prognosis of AD.

Peptide-based vaccine for cancer therapies

Different strategies based on peptides are available for cancer treatment, in particular to counter-act the progression of tumor growth and disease relapse. In the last decade, in the context of therapeutic strategies against cancer, peptide-based vaccines have been evaluated in different tumor models. The peptides selected for cancer vaccine development can be classified in two main type: tumor-associated antigens (TAAs) and tumor-specific antigens (TSAs), which are captured, internalized, processed and presented by antigen-presenting cells (APCs) to cell-mediated immunity. Peptides loaded onto MHC class I are recognized by a specific TCR of CD8+ T cells, which are activated to exert their cytotoxic activity against tumor cells presenting the same peptide-MHC-I complex. This process is defined as active immunotherapy as the host's immune system is either de novo activated or restimulated to mount an effective, tumor-specific immune reaction that may ultimately lead to tu-mor regression. However, while the preclinical data have frequently shown encouraging results, therapeutic cancer vaccines clinical trials, including those based on peptides have not provided satisfactory data to date. The limited efficacy of peptide-based cancer vaccines is the consequence of several factors, including the identification of specific target tumor antigens, the limited immunogenicity of peptides and the highly immunosuppressive tumor microenvironment (TME). An effective cancer vaccine can be developed only by addressing all such different aspects. The present review describes the state of the art for each of such factors.

Immunoprecipitation methods impact the peptide repertoire in immunopeptidomics

Introduction

Mass spectrometry-based immunopeptidomics is the only unbiased method to identify naturally presented HLA ligands, which is an indispensable prerequisite for characterizing novel tumor antigens for immunotherapeutic approaches. In recent years, improvements based on devices and methodology have been made to optimize sensitivity and throughput in immunopeptidomics. However, developments in ligand isolation, mass spectrometric analysis, and subsequent data processing can have a marked impact on the quality and quantity of immunopeptidomics data.

Methods

In this work, we compared the immunopeptidome composition in terms of peptide yields, spectra quality, hydrophobicity, retention time, and immunogenicity of two established immunoprecipitation methods (column-based and 96-well-based) using cell lines as well as primary solid and hematological tumor samples.

Results

Although, we identified comparable overall peptide yields, large proportions of method-exclusive peptides were detected with significantly higher hydrophobicity for the column-based method with potential implications for the identification of immunogenic tumor antigens. We showed that column preparation does not lose hydrophilic peptides in the hydrophilic washing step. In contrast, an additional 50% acetonitrile elution could partially regain lost hydrophobic peptides during 96-well preparation, suggesting a reduction of the bias towards the column-based method but not completely equalizing it.

Discussion

Together, this work showed how different immunoprecipitation methods and their adaptions can impact the peptide repertoire of immunopeptidomic analysis and therefore the identification of potential tumor-associated antigens.

The good and the bad of T cell cross-reactivity: challenges and opportunities for novel therapeutics in autoimmunity and cancer

T cells are main actors of the immune system with an essential role in protection against pathogens and cancer. The molecular key event involved in this absolutely central task is the interaction of membrane-bound specific T cell receptors with peptide-MHC complexes which initiates T cell priming, activation and recall, and thus controls a range of downstream functions. While textbooks teach us that the repertoire of mature T cells is highly diverse, it is clear that this diversity cannot possibly cover all potential foreign peptides that might be encountered during life. TCR cross-reactivity, i.e. the ability of a single TCR to recognise different peptides, offers the best solution to this biological challenge. Reports have shown that indeed, TCR cross-reactivity is surprisingly high. Hence, the T cell dilemma is the following: be as specific as possible to target foreign danger and spare self, while being able to react to a large spectrum of body-threatening situations. This has major consequences for both autoimmune diseases and cancer, and significant implications for the development of T cell-based therapies. In this review, we will present essential experimental evidence of T cell cross-reactivity, implications for two opposite immune conditions, i.e. autoimmunity vs cancer, and how this can be differently exploited for immunotherapy approaches. Finally, we will discuss the tools available for predicting cross-reactivity and how improvements in this field might boost translational approaches.

Get into the groove! The influence of TAPBPR on cargo selection

Since the discovery of Transporter associated with antigen processing-binding protein-related (TAPBPR) over two decades ago, extensive studies have explored its function in the context of the major histocompatibility complex class-I (MHC-I) antigen processing and presentation pathway. As a chaperone and peptide editor, TAPBPR was recently revealed to have overlapping structural features when resolved with peptide-receptive MHC-I molecules compared with the two newly solved tapasin:MHC-I structures. Despite this, the two chaperones seem to have a unique criteria for loading high-affinity peptides on MHC-I molecules. Yet, the mechanism of action of how TAPBPR creates its distinct filter in cargo selection for peptide-receptive MHC-I molecules continues to be a subject of debate.

Is HLA type a possible cancer risk modifier in Lynch syndrome?

Lynch syndrome (LS) is the most common inherited cancer syndrome. It is inherited via a monoallelic germline variant in one of the DNA mismatch repair (MMR) genes. LS carriers have a broad 30% to 80% risk of developing various malignancies, and more precise, individual risk estimations would be of high clinical value, allowing tailored cancer prevention and surveillance. Due to MMR deficiency, LS cancers are characterized by the accumulation of frameshift mutations leading to highly immunogenic frameshift peptides (FSPs). Thus, immune surveillance is proposed to inhibit the outgrowth of MMR-deficient cell clones. Recent studies have shown that immunoediting during the evolution of MMR-deficient cancers leads to a counter-selection of highly immunogenic antigens. The immunogenicity of FSPs is dependent on the antigen presentation. One crucial factor determining antigen presentation is the HLA genotype. Hence, a LS carrier's HLA genotype plays an important role in the presentation of FSP antigens to the immune system, and may influence the likelihood of progression from precancerous lesions to cancer. To address the challenge of clarifying this possibility including diverse populations with different HLA types, we have established the INDICATE initiative (Individual cancer risk by HLA type, http://indicate-lynch.org/), an international network aiming at a systematic evaluation of the HLA genotype as a possible cancer risk modifier in LS. Here we summarize the current knowledge on the role of HLA type in cancer risk and outline future research directions to delineate possible association in the scenario of LS with genetically defined risk population and highly immunogenic tumors.

Determinants of tumor immune evasion: the role of T cell exposed motif frequency and mutant amino acid exposure

Few neoepitopes detected in tumor biopsies are immunogenic. Tumor-specific T cell responses require both the presentation of an epitope that differs from wildtype and the presence of T cells with neoepitope-cognate receptors. We show that mutations detected in tumor biopsies result in an increased frequency of rare amino acid combinations compared to the human proteome and gastrointestinal microorganisms. Mutations in a large data set of oncogene and tumor suppressor gene products were compared to wildtype, and to the count of corresponding amino acid motifs in the human proteome and gastrointestinal microbiome. Mutant amino acids in T cell exposed positions of potential neoepitopes consistently generated amino acid motifs that are less common in both proteome reference datasets. Approximately 10% of the mutant amino acid motifs are absent from the human proteome. Motif frequency does not change when mutants were positioned in the MHC anchor positions hidden from T cell receptors. Analysis of neoepitopes in GBM and LUSC cases showed less common T cell exposed motifs, and HLA binding preferentially placing mutant amino acids in an anchor position for both MHC I and MHC II. Cross-presentation of mutant exposed neoepitopes by MHC I and MHC II was particularly uncommon. Review of a tumor mutation dataset known to generate T cell responses showed immunogenic epitopes were those with mutant amino acids exposed to the T cell receptor and with exposed pentamer motifs present in the human and microbiome reference databases. The study illustrates a previously unrecognized mechanism of tumor immune evasion, as rare T cell exposed motifs produced by mutation are less likely to have cognate T cells in the T cell repertoire. The complex interactions of HLA genotype, binding positions, and mutation specific changes in T cell exposed motif underscore the necessity of evaluating potential neoepitopes in each individual patient.

The biogenesis of the immunopeptidome

The immunopeptidome is the repertoire of peptides bound and presented by the MHC class I, class II, and non-classical molecules. The peptides are produced by the degradation of most cellular proteins, and in some cases, peptides are produced from extracellular proteins taken up by the cells. This review attempts to first describe some of its known and well-accepted concepts, and next, raise some questions about a few of the established dogmas in this field: The production of novel peptides by splicing is questioned, suggesting here that spliced peptides are extremely rare, if existent at all. The degree of the contribution to the immunopeptidome by degradation of cellular protein by the proteasome is doubted, therefore this review attempts to explain why it is likely that this contribution to the immunopeptidome is possibly overstated. The contribution of defective ribosome products (DRiPs) and non-canonical peptides to the immunopeptidome is noted and methods are suggested to quantify them. In addition, the common misconception that the MHC class II peptidome is mostly derived from extracellular proteins is noted, and corrected. It is stressed that the confirmation of sequence assignments of non-canonical and spliced peptides should rely on targeted mass spectrometry using spiking-in of heavy isotope-labeled peptides. Finally, the new methodologies and modern instrumentation currently available for high throughput kinetics and quantitative immunopeptidomics are described. These advanced methods open up new possibilities for utilizing the big data generated and taking a fresh look at the established dogmas and reevaluating them critically.

The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

Comprehensive Analysis of Epstein-Barr Virus LMP2A-Specific CD8+ and CD4+ T Cell Responses Restricted to Each HLA Class I and II Allotype Within an Individual

Latent membrane protein 2A (LMP2A), a latent Ag commonly expressed in Epstein-Barr virus (EBV)-infected host cells, is a target for adoptive T cell therapy in EBV-associated malignancies. To define whether individual human leukocyte antigen (HLA) allotypes are used preferentially in EBV-specific T lymphocyte responses, LMP2A-specific CD8+ and CD4+ T cell responses in 50 healthy donors were analyzed by ELISPOT assay using artificial Ag-presenting cells expressing a single allotype. CD8+ T cell responses were significantly higher than CD4+ T cell responses. CD8+ T cell responses were ranked from highest to lowest in the order HLA-A, HLA-B, and HLA-C loci, and CD4+ T cell responses were ranked in the order HLA-DR, HLA-DP, and HLA-DQ loci. Among the 32 HLA class I and 56 HLA class II allotypes, 6 HLA-A, 7 HLA-B, 5 HLA-C, 10 HLA-DR, 2 HLA-DQ, and 2 HLA-DP allotypes showed T cell responses higher than 50 spot-forming cells (SFCs)/5×105 CD8+ or CD4+ T cells. Twenty-nine donors (58%) showed a high T cell response to at least one allotype of HLA class I or class II, and 4 donors (8%) had a high response to both HLA class I and class II allotypes. Interestingly, we observed an inverse correlation between the proportion of LMP2A-specific T cell responses and the frequency of HLA class I and II allotypes. These data demonstrate the allele dominance of LMP2A-specific T cell responses among HLA allotypes and their intra-individual dominance in response to only a few allotypes in an individual, which may provide useful information for genetic, pathogenic, and immunotherapeutic approaches to EBV-associated diseases.

Diversity of HLA-A2-Restricted and Immunodominant Epitope Repertoire of Human T-Lymphotropic Virus Type 1 (HTLV-1) Tax Protein: Novel Insights among N-Terminal, Central and C-Terminal Regions

The present study sought to search for the immunodominance related to the N-terminal, Central and C-terminal regions of HTLV-1 Tax using novel, cutting-edge peptide microarray analysis. In addition, in silico predictions were performed to verify the presence of nine amino acid peptides present along Tax restricted to the human leukocyte antigen (HLA)-A2.02*01 haplotype, as well as to verify the ability to induce pro-inflammatory and regulatory cytokines, such as IFN-γ and IL-4, respectively. Our results indicated abundant dose-dependent reactivity for HLA-A*02:01 in all regions (N-terminal, Central and C-terminal), but with specific hotspots. Furthermore, the results of fold-change over the Tax11–19 reactivity obtained at lower concentrations of HLA-A*02:01 reveal that peptides from the three regions contain sequences that react 100 times more than Tax11–19. On the other hand, Tax11–19 has similar or superior HLA-A*02:01 reactivity at higher concentrations of this haplotype. The in silico analysis showed a higher frequency of IFN-γ-inducing peptides in the N-terminal portion, while the C-terminal portion showed a higher frequency of IL-4 inducers. Taken together, these results shed light on the search for new Tax immunodominant epitopes, in addition to the canonic Tax11–19, for the rational design of immunomodulatory strategies for HTLV-1 chronic diseases.

Role of MHC class I pathways in Mycobacterium tuberculosis antigen presentation

MHC class I antigen processing is an underappreciated area of nonviral host–pathogen interactions, bridging both immunology and cell biology, where the pathogen’s natural life cycle involves little presence in the cytoplasm. The effective response to MHC-I foreign antigen presentation is not only cell death but also phenotypic changes in other cells and stimulation of the memory cells ready for the next antigen reoccurrence. This review looks at the MHC-I antigen processing pathway and potential alternative sources of the antigens, focusing on Mycobacterium tuberculosis (Mtb) as an intracellular pathogen that co-evolved with humans and developed an array of decoy strategies to survive in a hostile environment by manipulating host immunity to its own advantage. As that happens via the selective antigen presentation process, reinforcement of the effective antigen recognition on MHC-I molecules may stimulate subsets of effector cells that act earlier and more locally. Vaccines against tuberculosis (TB) could potentially eliminate this disease, yet their development has been slow, and success is limited in the context of this global disease’s spread. This review’s conclusions set out potential directions for MHC-I-focused approaches for the next generation of vaccines.

Analysis of the different subpeptidomes presented by the HLA class I molecules of the B7 supertype

MHC-I molecules of the HLA-B7 supertype preferentially bind peptides with proline at position 2. HLA-B*51:01 and B*51:08 present two predominant subpeptidomes, one with Pro2 and hydrophobic residues at P1, and another with Ala2 and Asp enriched at position 1. Here, we present a meta-analysis of the peptidomes presented by molecules of the B7 supertype to investigate the presence of subpeptidomes across different allotypes. Several allotypes presented subpeptidomes differing in the presence of Pro or another residue at P2. The Ala2 subpeptidomes preferred Asp1 except in HLA-B*54:01, where ligands with Ala2 contained Glu1. Sequence alignment and the analysis of crystal structures allowed us to propose positions 45 and 67 of the MHC heavy chain as relevant for the presence of subpeptidomes. Deciphering the principles behind the presence of subpeptidomes could improve our understanding of antigen presentation in other MHC-I molecules. Running title: HLA-B7 supertype subpeptidomes.

The impact of immunopeptidomics: From basic research to clinical implementation

The immunopeptidome is the set of peptides presented by the major histocompatibility complex (MHC) molecules, in humans also known as the human leukocyte antigen (HLA), on the surface of cells that mediate T-cell immunosurveillance. The immunopeptidome is a sampling of the cellular proteome and hence it contains information about the health state of cells. The peptide repertoire is influenced by intra- and extra-cellular perturbations - such as in the case of drug exposure, infection, or oncogenic transformation. Immunopeptidomics is the bioanalytical method by which the presented peptides are extracted from biological samples and analyzed by high-performance liquid chromatography coupled to tandem mass spectrometry (MS), resulting in a deep qualitative and quantitative snapshot of the immunopeptidome. In this review, we discuss published immunopeptidomics studies from recent years, grouped into three main domains: i) basic, ii) pre-clinical and iii) clinical research and applications. We review selected fundamental immunopeptidomics studies on the antigen processing and presentation machinery, on HLA restriction and studies that advanced our understanding of various diseases, and how exploration of the antigenic landscape allowed immune targeting at the pre-clinical stage, paving the way to pioneering exploratory clinical trials where immunopeptidomics is directly implemented in the conception of innovative treatments for cancer patients.

Antigen discovery for the development of cancer immunotherapy

Central to successful cancer immunotherapy is effective T cell antitumor immunity. Multiple targeted immunotherapies engineered to invigorate T cell-driven antitumor immunity rely on identifying the repertoire of T cell antigens expressed on the tumor cell surface. Mass spectrometry-based survey of such antigens ("immunopeptidomics") combined with other omics platforms and computational algorithms has been instrumental in identifying and quantifying tumor-derived T cell antigens. In this review, we discuss the types of tumor antigens that have emerged for targeted cancer immunotherapy and the immunopeptidomics methods that are central in MHC peptide identification and quantification. We provide an overview of the strength and limitations of mass spectrometry-driven approaches and how they have been integrated with other technologies to discover targetable T cell antigens for cancer immunotherapy. We highlight some of the emerging cancer immunotherapies that successfully capitalized on immunopeptidomics, their challenges, and mass spectrometry-based strategies that can support their development.

Contemplating immunopeptidomes to better predict them

The identification of T-cell epitopes is key for a complete molecular understanding of immune recognition mechanisms in infectious diseases, autoimmunity and cancer. T-cell epitopes further provide targets for personalized vaccines and T-cell therapy, with several therapeutic applications in cancer immunotherapy and elsewhere. T-cell epitopes consist of short peptides displayed on Major Histocompatibility Complex (MHC) molecules. The recent advances in mass spectrometry (MS) based technologies to profile the ensemble of peptides displayed on MHC molecules - the so-called immunopeptidome - had a major impact on our understanding of antigen presentation and MHC ligands. On the one hand, these techniques enabled researchers to directly identify hundreds of thousands of peptides presented on MHC molecules, including some that elicited T-cell recognition. On the other hand, the data collected in these experiments revealed fundamental properties of antigen presentation pathways and significantly improved our ability to predict naturally presented MHC ligands and T-cell epitopes across the wide spectrum of MHC alleles found in human and other organisms. Here we review recent computational developments to analyze experimentally determined immunopeptidomes and harness these data to improve our understanding of antigen presentation and MHC binding specificities, as well as our ability to predict MHC ligands. We further discuss the strengths and limitations of the latest approaches to move beyond predictions of antigen presentation and tackle the challenges of predicting TCR recognition and immunogenicity.

Viral T-cell epitopes - Identification, characterization and clinical application

T-cell immunity, mediated by CD4⁺ and CD8⁺ T cells, represents a cornerstone in the control of viral infections. Virus-derived T-cell epitopes are represented by human leukocyte antigen (HLA)-presented viral peptides on the surface of virus-infected cells. They are the prerequisite for the recognition of infected cells by T cells. Knowledge of viral T-cell epitopes provides on the one hand a diagnostic tool to decipher protective T-cell immune responses in the human population and on the other hand various prophylactic and therapeutic options including vaccination approaches and the transfer of virus-specific T cells. Such approaches have already been proven to be effective against various viral infections, particularly in immunocompromised patients lacking sufficient humoral, antibody-based immune response. This review provides an overview on the state of the art as well as current studies regarding the identification and characterization of viral T-cell epitopes and approaches of clinical application. In the first chapter in silico prediction tools and direct, mass spectrometry-based identification of viral T-cell epitopes is compared. The second chapter provides an overview of commonly used assays for further characterization of T-cell responses and phenotypes. The final chapter presents an overview of clinical application of viral T-cell epitopes with a focus on human immunodeficiency virus (HIV), human cytomegalovirus (HCMV) and severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), being representatives of relevant viruses.

Functional studies of HLA and its role in SARS-CoV-2: Stimulating T cell response and vaccine development

In the biological immune process, the major histocompatibility complex (MHC) plays an indispensable role in the expression of HLA molecules in the human body when viral infection activates the T-cell response to remove the virus. Since the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 2019, how to address and prevent SARS-CoV-2 has become a common problem facing all mankind. The T-cell immune response activated by MHC peptides is a way to construct a defense line and reduce the transmission and harm of the virus. Presentation of SARS-CoV-2 antigen is associated with different types of HLA phenotypes, and different HLA phenotypes induce different immune responses. The prediction of SARS-CoV-2 mutation information and the design of vaccines based on HLAs can effectively activate autoimmunity and cope with virus mutations, which can provide some references for the prevention and treatment of SARS-CoV-2.

A Comprehensive Review on the Biological, Agricultural and Pharmaceutical Properties of Secondary Metabolites Based-Plant Origin

Natural products are compounds produced by living organisms and can be divided into two main categories: primary (PMs) and secondary metabolites (SMs). Plant PMs are crucial for plant growth and reproduction since they are directly involved in living cell processes, whereas plant SMs are organic substances directly involved in plant defense and resistance. SMs are divided into three main groups: terpenoids, phenolics and nitrogen-containing compounds. The SMs contain a variety of biological capabilities that can be used as flavoring agents, food additives, plant-disease control, strengthen plant defenses against herbivores and, additionally, it can help plant cells to be better adapted to the physiological stress response. The current review is mainly focusing on certain key elements related to the significance, biosynthesis, classification, biochemical characterization and medical/pharmaceutical uses of the major categories of plant SMs. In addition, the usefulness of SMs in controlling plant diseases, boosting plant resistance and as potential natural, safe, eco-friendly substitutes for chemosynthetic pesticides were also reported in this review.

Endo-lysosomal assembly variations among human leukocyte antigen class I (HLA class I) allotypes

The extreme polymorphisms of human leukocyte antigen class I (HLA class I) proteins enable the presentation of diverse peptides to cytotoxic T lymphocytes. The canonical endoplasmic reticulum (ER) HLA class I assembly pathway enables presentation of cytosolic peptides, but effective intracellular surveillance requires multi-compartmental antigen sampling. Endo-lysosomes are generally sites of HLA class II assembly, but human monocytes and monocyte-derived dendritic cells (moDCs) also contain significant reserves of endo-lysosomal HLA class I molecules. We hypothesized variable influences of HLA class I polymorphisms upon outcomes of endo-lysosomal trafficking, as the stabilities and peptide occupancies of cell surface HLA class I molecules are variable. Consistent with this model, when the endo-lysosomal pH of moDCs is disrupted, HLA-B allotypes display varying propensities for reductions in surface expression, with HLA-B*08:01 or HLA-B*35:01 being among the most resistant or sensitive, respectively, among eight tested HLA-B allotypes. Perturbations of moDC endo-lysosomal pH result in accumulation of HLA-B*35:01 in LAMP1+ compartments and increase HLA-B*35:01 peptide receptivity. These findings reveal the intersection of the vacuolar cross-presentation pathway with a constitutive assembly pathway for some HLA-B allotypes. Notably, cross-presentation of epitopes derived from two soluble antigens was also more efficient for B*35:01 compared to B*08:01, even when matched for T cell response sensitivity, and more affected by cathepsin inhibition. Thus, HLA class I polymorphisms dictate the degree of endo-lysosomal assembly, which can supplement ER assembly for constitutive HLA class I expression and increase the efficiency of cross-presentation.

Peptide Vaccines in Melanoma: Chemical Approaches towards Improved Immunotherapeutic Efficacy

Cancer of the skin is by far the most common of all cancers. Although the incidence of melanoma is relatively low among skin cancers, it can account for a high number of skin cancer deaths. Since the start of deeper insight into the mechanisms of melanoma tumorigenesis and their strong interaction with the immune system, the development of new therapeutical strategies has been continuously rising. The high number of melanoma cell mutations provides a diverse set of antigens that the immune system can recognize and use to distinguish tumor cells from normal cells. Peptide-based synthetic anti-tumor vaccines are based on tumor antigens that elicit an immune response due to antigen-presenting cells (APCs). Although targeting APCs with peptide antigens is the most important assumption for vaccine development, peptide antigens alone are poorly immunogenic. The immunogenicity of peptide antigens can be improved not only by synthetic modifications but also by the assistance of adjuvants and/or delivery systems. The current review summarizes the different chemical approaches for the development of effective peptide-based vaccines for the immunotherapeutic treatment of advanced melanoma.

Decoupling peptide binding from T cell receptor recognition with engineered chimeric MHC-I molecules

Major Histocompatibility Complex class I (MHC-I) molecules display self, viral or aberrant epitopic peptides to T cell receptors (TCRs), which employ interactions between complementarity-determining regions with both peptide and MHC-I heavy chain 'framework' residues to recognize specific Human Leucocyte Antigens (HLAs). The highly polymorphic nature of the HLA peptide-binding groove suggests a malleability of interactions within a common structural scaffold. Here, using structural data from peptide:MHC-I and pMHC:TCR structures, we first identify residues important for peptide and/or TCR binding. We then outline a fixed-backbone computational design approach for engineering synthetic molecules that combine peptide binding and TCR recognition surfaces from existing HLA allotypes. X-ray crystallography demonstrates that chimeric molecules bridging divergent HLA alleles can bind selected peptide antigens in a specified backbone conformation. Finally, in vitro tetramer staining and biophysical binding experiments using chimeric pMHC-I molecules presenting established antigens further demonstrate the requirement of TCR recognition on interactions with HLA framework residues, as opposed to interactions with peptide-centric Chimeric Antigen Receptors (CARs). Our results underscore a novel, structure-guided platform for developing synthetic HLA molecules with desired properties as screening probes for peptide-centric interactions with TCRs and other therapeutic modalities.

Prediction and validation of murine MHC class I epitopes of the recombinant virus VSV-GP

Oncolytic viruses are currently tested as a novel platform for cancer therapy. These viruses preferentially replicate in and kill malignant cells. Due to their microbial origin, treatment with oncolytic viruses naturally results in anti-viral responses and general immune activation. Consequently, the oncolytic virus treatment also induces anti-viral T cells. Since these can constitute the dominant activated T cell pool, monitoring of the anti-viral T cell response may aid in better understanding of the immune responses post oncolytic virotherapy. This study aimed to identify the anti-viral T cells raised by VSV-GP virotherapy in C57BL/6J mice, one of the most widely used models for preclinical studies. VSV-GP is a novel oncolytic agent that recently entered a clinical phase I study. To identify the VSV-GP epitopes to which mouse anti-viral T cells react, we used a multilevel adapted bioinformatics viral epitope prediction approach based on the tools netMHCpan, MHCflurry and netMHCstabPan, which are commonly used in neoepitope identification. Predicted viral epitopes were ranked based on consensus binding strength categories, predicted stability, and dissimilarity to the mouse proteome. The top ranked epitopes were selected and included in the peptide candidate matrix in order to use a matrix deconvolution approach. Using ELISpot, we showed which viral epitopes presented on C57BL/6J mouse MHC-I alleles H2-Db and H2-Kb trigger IFN-γ secretion due to T cell activation. Furthermore, we validated these findings using an intracellular cytokine staining. Collectively, identification of the VSV-GP T cell epitopes enables monitoring of the full range of anti-viral T cell responses upon VSV-GP virotherapy in future studies with preclinical mouse models to more comprehensively delineate anti-viral from anti-tumor T cell responses. These findings also support the development of novel VSV-GP variants expressing immunomodulatory transgenes and can improve the assessment of anti-viral immunity in preclinical models.

Lynch syndrome cancer vaccines: A roadmap for the development of precision immunoprevention strategies

Hereditary cancer syndromes (HCS) account for 5~10% of all cancer diagnosis. Lynch syndrome (LS) is one of the most common HCS, caused by germline mutations in the DNA mismatch repair (MMR) genes. Even with prospective cancer surveillance, LS is associated with up to 50% lifetime risk of colorectal, endometrial, and other cancers. While significant progress has been made in the timely identification of germline pathogenic variant carriers and monitoring and early detection of precancerous lesions, cancer-risk reduction strategies are still centered around endoscopic or surgical removal of neoplastic lesions and susceptible organs. Safe and effective cancer prevention strategies are critically needed to improve the life quality and longevity of LS and other HCS carriers. The era of precision oncology driven by recent technological advances in tumor molecular profiling and a better understanding of genetic risk factors has transformed cancer prevention approaches for at-risk individuals, including LS carriers. MMR deficiency leads to the accumulation of insertion and deletion mutations in microsatellites (MS), which are particularly prone to DNA polymerase slippage during DNA replication. Mutations in coding MS give rise to frameshift peptides (FSP) that are recognized by the immune system as neoantigens. Due to clonal evolution, LS tumors share a set of recurrent and predictable FSP neoantigens in the same and in different LS patients. Cancer vaccines composed of commonly recurring FSP neoantigens selected through prediction algorithms have been clinically evaluated in LS carriers and proven safe and immunogenic. Preclinically analogous FSP vaccines have been shown to elicit FSP-directed immune responses and exert tumor-preventive efficacy in murine models of LS. While the immunopreventive efficacy of "off-the-shelf" vaccines consisting of commonly recurring FSP antigens is currently investigated in LS clinical trials, the feasibility and utility of personalized FSP vaccines with individual HLA-restricted epitopes are being explored for more precise targeting. Here, we discuss recent advances in precision cancer immunoprevention approaches, emerging enabling technologies, research gaps, and implementation barriers toward clinical translation of risk-tailored prevention strategies for LS carriers. We will also discuss the feasibility and practicality of next-generation cancer vaccines that are based on personalized immunogenic epitopes for precision cancer immunoprevention.

Targeting the recurrent Rac1P29S neoepitope in melanoma with heterologous high-affinity T cell receptors

Recurrent neoepitopes are cancer-specific antigens common among groups of patients and therefore ideal targets for adoptive T cell therapy. The neoepitope FSGEYIPTV carries the Rac1P29S amino acid change caused by a c.85C>T missense mutation, which is the third most common hotspot mutation in melanoma. Here, we isolated and characterized TCRs to target this HLA-A*02:01-binding neoepitope by adoptive T cell therapy. Peptide immunization elicited immune responses in transgenic mice expressing a diverse human TCR repertoire restricted to HLA-A*02:01, which enabled isolation of high-affinity TCRs. TCR-transduced T cells induced cytotoxicity against Rac1P29S expressing melanoma cells and we observed regression of Rac1P29S expressing tumors in vivo after adoptive T cell therapy (ATT). Here we found that a TCR raised against a heterologous mutation with higher peptide-MHC affinity (Rac2P29L) more efficiently targeted the common melanoma mutation Rac1P29S. Overall, our study provides evidence for the therapeutic potential of Rac1P29S-specific TCR-transduced T cells and reveal a novel strategy by generating more efficient TCRs by heterologous peptides.

A simple approach for detecting HLA-A*02 alleles in archival formalin-fixed paraffin-embedded tissue samples and an application example for studying cancer immunoediting

The HLA system represents a central component of the antigen presentation machinery. As every patient possesses a defined set of HLA molecules, only certain antigens can be presented on the cell surface. Thus, studying HLA type-dependent antigen presentation can improve the understanding of variation in susceptibility to various diseases, including infectious diseases and cancer. In archival formalin-fixed paraffin-embedded (FFPE) tissue, the HLA type is difficult to analyze because of fragmentation of DNA, hindering the application of commonly used assays that rely on long DNA stretches. Addressing these difficulties, we present a refined approach for characterizing presence or absence of HLA-A*02, the most common HLA-A allele in the Caucasian population, in archival samples. We validated our genotyping strategy in a cohort of 90 samples with HLA status obtained by an NGS-based method. 90% (n = 81) of the samples could be analyzed with the approach. For all of them, the presence or absence of HLA-A*02 alleles was correctly determined with the method, demonstrating 100% sensitivity and specificity (95% CI: 91.40%-100% and 91.19%-100%). Furthermore, we provide an example of application in an independent cohort of 73 FFPE microsatellite-unstable (MSI) colorectal cancer samples. As MSI cancer cells encompass a high number of mutations in coding microsatellites, leading to the generation of highly immunogenic frameshift peptide antigens, they are ideally suited for studying relations between the mutational landscape of tumor cells and interindividual differences in the immune system, including the HLA genotype. Overall, our method can help to promote studying HLA type-dependency during the pathogenesis of a wide range of diseases, making archival and historic tissue samples accessible for identifying HLA-A*02 alleles.

In silico approach to design a multi-epitopic vaccine candidate targeting the non-mutational immunogenic regions in envelope protein and surface glycoprotein of SARS-CoV-2

The novel corona virus (COVID-19) is a causative agent for severe acute respiratory syndrome (SARS-CoV-2) and responsible for the current human pandemic situation which has caused global social and economic commotion. The currently available vaccines use whole viruses whereas there is scope for peptide based vaccines. Thus, the global raise in statistics of this infection at an alarming rate evoked us to determine a novel and effective vaccine candidate against SARS-CoV-2. To find the potential vaccine candidate targets, immunoinformatics approaches were used to analyze the mutations in the envelope protein and surface glycoprotein and determine the conserved region; further specific T-cell epitopes VSLVKPSFY, SLVKPSFYV, RVKNLNSSR, SEETGTLIV, LVKPSFYVY, LTDEMIAQY, YLQPRTFLL, RLFRKSNLK, SPRRARSVA, AEIRASANL, TLLALHRSY, YSRVKNLNS and FELLHAPAT and B-cells epitopes TLAILTALRLCAYCCN and AGTITSGWTFGAGAAL were identified. The 3 D structure of epitope was predicted, refined and validated. The molecular docking analysis of multi-epitope vaccine candidates with TLR receptors, predicted effective binding. Overall, using bioinformatics approach this multi-epitopic target facilitates the proof of concept for SARS-CoV-2 conserved epitopic vaccine design.Communicated by Ramaswamy H. Sarma.

In silico and in vitro arboviral MHC class I-restricted-epitope signatures reveal immunodominance and poor overlapping patterns

INTRODUCTION

The present work sought to identify MHC-I-restricted peptide signatures for arbovirus using in silico and in vitro peptide microarray tools.

METHODS

First, an in-silico analysis of immunogenic epitopes restricted to four of the most prevalent human MHC class-I was performed by identification of MHC affinity score. For that, more than 10,000 peptide sequences from 5 Arbovirus and 8 different viral serotypes, namely Zika (ZIKV), Dengue (DENV serotypes 1-4), Chikungunya (CHIKV), Mayaro (MAYV) and Oropouche (OROV) viruses, in addition to YFV were analyzed. Haplotype HLA-A*02.01 was the dominant human MHC for all arboviruses. Over one thousand HLA-A2 immunogenic peptides were employed to build a comprehensive identity matrix. Intending to assess HLAA*02:01 reactivity of peptides in vitro, a peptide microarray was designed and generated using a dimeric protein containing HLA-A*02:01.

RESULTS

The comprehensive identity matrix allowed the identification of only three overlapping peptides between two or more flavivirus sequences, suggesting poor overlapping of virus-specific immunogenic peptides amongst arborviruses. Global analysis of the fluorescence intensity for peptide-HLA-A*02:01 binding indicated a dose-dependent effect in the array. Considering all assessed arboviruses, the number of DENV-derived peptides with HLA-A*02:01 reactivity was the highest. Furthermore, a lower number of YFV-17DD overlapping peptides presented reactivity when compared to non-overlapping peptides. In addition, the assessment of HLA-A*02:01-reactive peptides across virus polyproteins highlighted non-structural proteins as "hot-spots". Data analysis supported these findings showing the presence of major hydrophobic sites in the final segment of non-structural protein 1 throughout 2a (Ns2a) and in nonstructural proteins 2b (Ns2b), 4a (Ns4a) and 4b (Ns4b).

DISCUSSION

To our knowledge, these results provide the most comprehensive and detailed snapshot of the immunodominant peptide signature for arbovirus with MHC-class I restriction, which may bring insight into the design of future virus-specific vaccines to arboviruses and for vaccination protocols in highly endemic areas.