HLA class I alleles are associated with peptide-binding repertoires of different size, affinity, and immunogenicity

A journey to your self: The vague definition of immune self and its practical implications

The identification of immunogenic peptides has become essential in an increasing number of fields in immunology, ranging from tumor immunotherapy to vaccine development. The nature of the adaptive immune response is shaped by the similarity between foreign and self-protein sequences, a concept extensively applied in numerous studies. Can we precisely define the degree of similarity to self? Furthermore, do we accurately define immune self? In the current work, we aim to unravel the conceptual and mechanistic vagueness hindering the assessment of self-similarity. Accordingly, we demonstrate the remarkably low consistency among commonly employed measures and highlight potential avenues for future research.

STING signalling compensates for low tumour mutation burden to drive anti-tumour immunity

BACKGROUND

While mutation-derived neoantigens are well recognized in generating anti-tumour T cell response, increasing evidences highlight the complex association between tumour mutation burden (TMB) and tumour infiltrating lymphocytes (TILs). The exploration of non-TMB determinants of active immune response could improve the prognosis prediction and provide guidance for current immunotherapy.

METHODS

The transcriptomic and whole exome sequence data in The Cancer Genome Atlas were used to examine the relationship between TMB and exhausted CD8+ T cells (Tex), as an indicator of tumour antigen-specific T cells across nine major cancer types. Computational clustering analysis was performed on 4510 tumours to identify different immune profiles. NanoString gene expression analysis and single cell RNA-seq analysis using fresh human breast cancer were performed for finding validation.

FINDINGS

TMB was found to be poorly correlated with active immune response in various cancer types. Patient clustering analysis revealed a group of tumours with abundant Tex but low TMB. In those tumours, we observed significantly higher expression of the stimulator of interferon genes (STING) signalling. Dendritic cells, particularly those of BATF3+ lineage, were also found to be essential for accumulation of Tex within tumours. Mechanistically, loss of genomic and cellular integrity, marked by decreased DNA damage repair, defective replication stress response, and increased apoptosis were shown to drive STING activation.

INTERPRETATION

These results highlight that TMB alone does not fully predict tumour immune profiles, with STING signalling compensating for low TMB in non-hypermutated tumours to enhance anti-tumour immunity. Translating these results, STING agonists may benefit patients with non-hypermutated tumours. STING activation may serve as an additional biomarker to predict response to immune checkpoint blockades alongside TMB. Our research also unravelled the interplay between genomic instability and STING activation, informing potential combined chemotherapy targeting the axis of genomic integrity and immunotherapy.

FUNDING

City of Hope Christopher Family Endowed Innovation Fund for Alzheimer's Disease and Breast Cancer Research in honor of Vineta Christopher; Breast Cancer Alliance Early Career Investigator Award; National Cancer Institute of the National Institutes of Health under award number R01CA256989 and R01CA240392.

Development and use of machine learning algorithms in vaccine target selection

Computer-aided discovery of vaccine targets has become a cornerstone of rational vaccine design. In this article, I discuss how Machine Learning (ML) can inform and guide key computational steps in rational vaccine design concerned with the identification of B and T cell epitopes and correlates of protection. I provide examples of ML models, as well as types of data and predictions for which they are built. I argue that interpretable ML has the potential to improve the identification of immunogens also as a tool for scientific discovery, by helping elucidate the molecular processes underlying vaccine-induced immune responses. I outline the limitations and challenges in terms of data availability and method development that need to be addressed to bridge the gap between advances in ML predictions and their translational application to vaccine design.

Review - The impact of pharmacogenetics on the outcome of immune checkpoint inhibitors

The development of immune checkpoint inhibitors (ICIs) has a tremendous effect on the treatment options for multiple types of cancer. Nonetheless, there is a large interpatient variability in response, survival, and the development of immune-related adverse events (irAEs). Pharmacogenetics is the general term for germline genetic variations, which may cause the observed interindividual differences in response or toxicity to treatment. These genetic variations can either be single-nucleotide polymorphisms (SNPs) or structural variants, such as gene deletions, amplifications or rearrangements. For ICIs, pharmacogenetic variation in the human leukocyte antigen molecules has also been studied with regard to treatment outcome. This review presents a summary of the literature regarding the pharmacogenetics of ICI treatment, discusses the most important known genetic variations and offers recommendations on the application of pharmacogenetics for ICI treatment.

In silico design of a broad-spectrum multiepitope vaccine against influenza virus

Influenza remains a global health concern due to its potential to cause pandemics as a result of rapidly mutating influenza virus strains. Existing vaccines often struggle to keep up with these rapidly mutating flu viruses. Therefore, the development of a broad-spectrum peptide vaccine that can stimulate an optimal antibody response has emerged as an innovative approach to addressing the influenza threat. In this study, an immunoinformatic approach was employed to rapidly predict immunodominant epitopes from different antigens, aiming to develop an effective multiepitope influenza vaccine (MEV). The immunodominant B-cell linear epitopes of seasonal influenza strains hemagglutinin (HA) and neuraminidase (NA) were predicted using an antibody-peptide microarray, involving a human cohort including vaccinees and infected patients. On the other hand, bioinformatics tools were used to predict immunodominant cytotoxic T-cell (CTL) and helper T-cell (HTL) epitopes. Subsequently, these epitopes were evaluated by various immunoinformatic tools. Epitopes with high antigenicity, high immunogenicity, non-allergenicity, non-toxicity, as well as exemplary conservation were then connected in series with appropriate linkers and adjuvants to construct a broad-spectrum MEV. Moreover, the structural analysis revealed that the MEV candidates exhibited good stability, and the docking results demonstrated their strong affinity to Toll-like receptors 4 (TLR4). In addition, molecular dynamics simulation confirmed the stable interaction between TLR4 and MEVs. Three injections with MEVs showed a high level of B-cell and T-cell immune responses according to the immunological simulations in silico. Furthermore, in-silico cloning was performed, and the results indicated that the MEVs could be produced in considerable quantities in Escherichia coli (E. coli). Based on these findings, it is reasonable to create a broad-spectrum MEV against different subtypes of influenza A and B viruses in silico.

HLA variants and TCR diversity against SARS-CoV-2 in the pre-COVID-19 era

HLA antigen presentation and T-cell mediated immunity are critical to control acute viral infection such as COVID-19 caused by SARS-CoV-2. Recent data suggest that both the depth of peptide presentation and the breadth of the T-cell repertoire are associated with disease outcome. It has also been shown that unexposed subjects can develop strong T-cell responses against SARS-CoV-2 due to heterologous immunity. In this study, we explored the anti-SARS-CoV-2 T-cell repertoire by analyzing previously published T-cell receptor (TCR) CDR3β immunosequencing data in a cohort of 116 healthy donors and in the context of immune reconstitution after allogeneic hematopoietic stem cell transplantation in 116 recipients collected during the pre-COVID-19 era. For this, 143,310 publicly available SARS-CoV-2 specific T-cell sequences were investigated among the 3.5 million clonotypes in the cohort. We also performed HLA class I peptide binding predictions using the reference proteome of the virus and high resolution genotyping data in these patients. We could demonstrate that individuals are fully equipped at the genetic level to recognize SARS-CoV-2. This is evidenced by the 5% median cumulative frequency of clonotypes having their sequence matched to a SARS-CoV-2 specific T-cell. In addition, any combination of HLA class I variants in this cohort is associated with a broad capacity of presenting hundreds of SARS-CoV-2 derived peptides. These results could be explained by heterologous immunity and random somatic TCR recombination. We speculate that these observations could explain the efficacy of the specific immune response against SARS-CoV-2 in individuals without risk factors of immunodeficiency and infected prior to vaccination.

Re-Evaluating Human Cytomegalovirus Vaccine Design: Prediction of T Cell Epitopes

HCMV vaccine development has traditionally focused on viral antigens identified as key targets of neutralizing antibody (NAb) and/or T cell responses in healthy adults with chronic HCMV infection, such as glycoprotein B (gB), the glycoprotein H-anchored pentamer complex (PC), and the unique long 83 (UL83)-encoded phosphoprotein 65 (pp65). However, the protracted absence of a licensed HCMV vaccine that reduces the risk of infection in pregnancy regardless of serostatus warrants a systematic reassessment of assumptions informing vaccine design. To illustrate this imperative, we considered the hypothesis that HCMV proteins infrequently detected as targets of T cell responses may contain important vaccine antigens. Using an extant dataset from a T cell profiling study, we tested whether HCMV proteins recognized by only a small minority of participants encompass any T cell epitopes. Our analyses demonstrate a prominent skewing of T cell responses away from most viral proteins-although they contain robust predicted CD8 T cell epitopes-in favor of a more restricted set of proteins. Our findings raise the possibility that HCMV may benefit from evading the T cell recognition of certain key proteins and that, contrary to current vaccine design approaches, including them as vaccine antigens could effectively take advantage of this vulnerability.

Neoantigen Targetability in Progressive Advanced Melanoma

PURPOSE

The availability of (neo)antigens and the infiltration of tumors by (neo)antigen-specific T cells are crucial factors in cancer immunotherapy. In this study, we aimed to investigate the targetability of (neo)antigens in advanced progessive melanoma and explore the potential for continued T-cell-based immunotherapy.

EXPERIMENTAL DESIGN

We examined a cohort of eight patients with melanoma who had sequential metastases resected at early and later time points. Antigen-presenting capacity was assessed using IHC and flow cytometry. T-cell infiltration was quantified through multiplex immunofluorescence. Whole-exome and RNA sequencing were conducted to identify neoantigens and assess the expression of neoantigens and tumor-associated antigens. Mass spectrometry was used to evaluate antigen presentation. Tumor recognition by autologous T cells was assessed by coculture assays with cell lines derived from the metastatic lesions.

RESULTS

We observed similar T-cell infiltration in paired early and later metastatic (LM) lesions. Although elements of the antigen-presenting machinery were affected in some LM lesions, both the early and later metastasis-derived cell lines were recognized by autologous T cells. At the genomic level, the (neo)antigen landscape was dynamic, but the (neo)antigen load was stable between paired lesions.

CONCLUSIONS

Our findings indicate that subsequently isolated tumors from patients with late-stage melanoma retain sufficient antigen-presenting capacity, T-cell infiltration, and a stable (neo)antigen load, allowing recognition of tumor cells by T cells. This indicates a continuous availability of T-cell targets in metastases occurring at different time points and supports further exploration of (neo)antigen-specific T-cell-based therapeutic approaches for advanced melanoma.

Linear epitope mapping in the E and NS1 proteins of dengue and Zika viruses: Prospection of peptides for vaccines and diagnostics

The arrival of the Zika virus (ZIKV) in dengue virus (DENV)-endemic areas has posed challenges for both differential diagnosis and vaccine development. Peptides have shown promise in addressing these issues. The aim of this study was to identify the linear epitope profile recognized by serum samples from dengue and Zika patients in the E and NS1 proteins of DENV and ZIKV. This cross-sectional study included individuals of all ages with laboratory-confirmed DENV and ZIKV infections, who were selected through convenience sampling. The serum samples from dengue and Zika patients detected epitopes evenly distributed across the viral proteins in a peptide microarray platform. However, several epitopes were located within "epitope hotspots", characterized by clusters of peptides recognized in more than 30% of the sub-arrays analyzed using individual or pooled serum samples. The serum samples from dengue and Zika patients showed a high level of cross-reactivity with peptides in the DENV and ZIKV proteins. Analysis using an additional peptide microarray platform, which contained peptides selected based on the results of the initial screening, revealed that two DENV and one ZIKV peptide, highly specific to their related viruses, were located within the epitope hotspots; however, they presented low detection rates (32.5, 35.0, and 28.6%, respectively). In addition, two DENV peptides detected at similarly high rates by both dengue and Zika patients were also found within the epitope hotspots. These hotspots contain several immunodominant epitopes that are recognized by a larger number of individuals when compared to 15-amino acid (aa) sequence peptides. Thus, epitope hotspots may have greater potential to serve as antigens in diagnostic tests and vaccine development than peptides composed of only 15 amino acids.

Integrated Bioinformatics Analysis Confirms the Diagnostic Value of Nourin-Dependent miR-137 and miR-106b in Unstable Angina Patients

The challenge of rapidly diagnosing myocardial ischemia in unstable angina (UA) patients presenting to the Emergency Department (ED) is due to a lack of sensitive blood biomarkers. This has prompted an investigation into microRNAs (miRNAs) related to cardiac-derived Nourin for potential diagnostic application. The Nourin protein is rapidly expressed in patients with acute coronary syndrome (ACS) (UA and acute myocardial infarction (AMI)). MicroRNAs regulate gene expression through mRNA binding and, thus, may represent potential biomarkers. We initially identified miR-137 and miR-106b and conducted a clinical validation, which demonstrated that they were highly upregulated in ACS patients, but not in healthy subjects and non-ACS controls. Using integrated comprehensive bioinformatics analysis, the present study confirms that the Nourin protein targets miR-137 and miR-106b, which are linked to myocardial ischemia and inflammation associated with ACS. Molecular docking demonstrated robust interactions between the Nourin protein and miR137/hsa-miR-106b, involving hydrogen bonds and hydrophobic interactions, with -10 kcal/mol binding energy. I-TASSER generated Nourin analogs, with the top 10 chosen for structural insights. Antigenic regions and MHCII epitopes within the Nourin SPGADGNGGEAMPGG sequence showed strong binding to HLA-DR/DQ alleles. The Cytoscape network revealed interactions of -miR137/hsa-miR--106b and Phosphatase and tensin homolog (PTEN) in myocardial ischemia. RNA Composer predicted the secondary structure of miR-106b. Schrödinger software identified key Nourin-RNA interactions critical for complex stability. The study identifies miR-137 and miR-106b as potential ACS diagnostic and therapeutic targets. This research underscores the potential of miRNAs targeting Nourin for precision ACS intervention. The analysis leverages RNA Composer, Schrödinger, and I-TASSER tools to explore interactions and structural insights. Robust Nourin-miRNA interactions are established, bolstering the case for miRNA-based interventions in ischemic injury. In conclusion, the study contributes to UA and AMI diagnosis strategies through bioinformatics-guided exploration of Nourin-targeting miRNAs. Supported by comprehensive molecular analysis, the hypoxia-induced miR-137 for cell apoptosis (a marker of cell damage) and the inflammation-induced miR-106b (a marker of inflammation) confirmed their potential clinical use as diagnostic biomarkers. This research reinforces the growing role of miR-137/hsa-miR-106b in the early diagnosis of myocardial ischemia in unstable angina patients.

Antigen presentation in cancer - mechanisms and clinical implications for immunotherapy

Over the past decade, the emergence of effective immunotherapies has revolutionized the clinical management of many types of cancers. However, long-term durable tumour control is only achieved in a fraction of patients who receive these therapies. Understanding the mechanisms underlying clinical response and resistance to treatment is therefore essential to expanding the level of clinical benefit obtained from immunotherapies. In this Review, we describe the molecular mechanisms of antigen processing and presentation in tumours and their clinical consequences. We examine how various aspects of the antigen-presentation machinery (APM) shape tumour immunity. In particular, we discuss genomic variants in HLA alleles and other APM components, highlighting their influence on the immunopeptidomes of both malignant cells and immune cells. Understanding the APM, how it is regulated and how it changes in tumour cells is crucial for determining which patients will respond to immunotherapy and why some patients develop resistance. We focus on recently discovered molecular and genomic alterations that drive the clinical outcomes of patients receiving immune-checkpoint inhibitors. An improved understanding of how these variables mediate tumour-immune interactions is expected to guide the more precise administration of immunotherapies and reveal potentially promising directions for the development of new immunotherapeutic approaches.

Preclinical proof of concept of a tetravalent lentiviral T-cell vaccine against dengue viruses

Dengue virus (DENV) is responsible for approximately 100 million cases of dengue fever annually, including severe forms such as hemorrhagic dengue and dengue shock syndrome. Despite intensive vaccine research and development spanning several decades, a universally accepted and approved vaccine against dengue fever has not yet been developed. The major challenge associated with the development of such a vaccine is that it should induce simultaneous and equal protection against the four DENV serotypes, because past infection with one serotype may greatly increase the severity of secondary infection with a distinct serotype, a phenomenon known as antibody-dependent enhancement (ADE). Using a lentiviral vector platform that is particularly suitable for the induction of cellular immune responses, we designed a tetravalent T-cell vaccine candidate against DENV ("LV-DEN"). This vaccine candidate has a strong CD8+ T-cell immunogenicity against the targeted non-structural DENV proteins, without inducing antibody response against surface antigens. Evaluation of its protective potential in the preclinical flavivirus infection model, i.e., mice knockout for the receptor to the type I IFN, demonstrated its significant protective effect against four distinct DENV serotypes, based on reduced weight loss, viremia, and viral loads in peripheral organs of the challenged mice. These results provide proof of concept for the use of lentiviral vectors for the development of efficient polyvalent T-cell vaccine candidates against all DENV serotypes.

A Bayesian approach to estimate MHC-peptide binding threshold

Major histocompatibility complex (MHC)-peptide binding is a critical step in enabling a peptide to serve as an antigen for T-cell recognition. Accurate prediction of this binding can facilitate various applications in immunotherapy. While many existing methods offer good predictive power for the binding affinity of a peptide to a specific MHC, few models attempt to infer the binding threshold that distinguishes binding sequences. These models often rely on experience-based ad hoc criteria, such as 500 or 1000nM. However, different MHCs may have different binding thresholds. As such, there is a need for an automatic, data-driven method to determine an accurate binding threshold. In this study, we proposed a Bayesian model that jointly infers core locations (binding sites), the binding affinity and the binding threshold. Our model provided the posterior distribution of the binding threshold, enabling accurate determination of an appropriate threshold for each MHC. To evaluate the performance of our method under different scenarios, we conducted simulation studies with varying dominant levels of motif distributions and proportions of random sequences. These simulation studies showed desirable estimation accuracy and robustness of our model. Additionally, when applied to real data, our results outperformed commonly used thresholds.

The structure of songbird MHC class I reveals antigen binding that is flexible at the N-terminus and static at the C-terminus

Long-distance migratory animals such as birds and bats have evolved to withstand selection imposed by pathogens across the globe, and pathogen richness is known to be particularly high in tropical regions. Immune genes, so-called Major Histocompatibility Complex (MHC) genes, are highly duplicated in songbirds compared to other vertebrates, and this high MHC diversity has been hypothesised to result in a unique adaptive immunity. To understand the rationale behind the evolution of the high MHC genetic diversity in songbirds, we determined the structural properties of an MHC class I protein, Acar3, from a long-distance migratory songbird, the great reed warbler Acrocephalus arundinaceus (in short: Acar). The structure of Acar3 was studied in complex with pathogen-derived antigens and shows an overall antigen presentation similar to human MHC class I. However, the peptides bound to Acar3 display an unusual conformation: Whereas the N-terminal ends of the peptides display enhanced flexibility, the conformation of their C-terminal halves is rather static. This uncommon peptide-binding mode in Acar3 is facilitated by a central Arg residue within the peptide-binding groove that fixes the backbone of the peptide at its central position, and potentially permits successful interactions between MHC class I and innate immune receptors. Our study highlights the importance of investigating the immune system of wild animals, such as birds and bats, to uncover unique immune mechanisms which may neither exist in humans nor in model organisms.

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.

A Wider and Deeper Peptide-Binding Groove for the Class I Molecules from B15 Compared with B19 Chickens Correlates with Relative Resistance to Marek's Disease

The chicken MHC is known to confer decisive resistance or susceptibility to various economically important pathogens, including the iconic oncogenic herpesvirus that causes Marek's disease (MD). Only one classical class I gene, BF2, is expressed at a high level in chickens, so it was relatively easy to discern a hierarchy from well-expressed thermostable fastidious specialist alleles to promiscuous generalist alleles that are less stable and expressed less on the cell surface. The class I molecule BF2*1901 is better expressed and more thermostable than the closely related BF2*1501, but the peptide motif was not simpler as expected. In this study, we confirm for newly developed chicken lines that the chicken MHC haplotype B15 confers resistance to MD compared with B19. Using gas phase sequencing and immunopeptidomics, we find that BF2*1901 binds a greater variety of amino acids in some anchor positions than does BF2*1501. However, by x-ray crystallography, we find that the peptide-binding groove of BF2*1901 is narrower and shallower. Although the self-peptides that bound to BF2*1901 may appear more various than those of BF2*1501, the structures show that the wider and deeper peptide-binding groove of BF2*1501 allows stronger binding and thus more peptides overall, correlating with the expected hierarchies for expression level, thermostability, and MD resistance. Our study provides a reasonable explanation for greater promiscuity for BF2*1501 compared with BF2*1901, corresponding to the difference in resistance to MD.

Immunoinformatics design of multi-epitope vaccine using OmpA, OmpD and enterotoxin against non-typhoidal salmonellosis

BACKGROUND

Non-typhoidal Salmonella (NTS) is one of the important bacteria that cause foodborne diseases and invasive infections in children and elderly people. Since NTS infection is difficult to control due to the emergence of antibiotic-resistant species and its adverse effect on immune response, the development of a vaccine against NTS would be necessary. This study aimed to develop a multi-epitope vaccine against the most prevalent serovars of NTS (Salmonella Typhimurium, Salmonella Enteritidis) using an immunoinformatics approach and targeting OmpA, OmpD, and enterotoxin (Stn).

RESULTS

Initially, the B cell and T cell epitopes were predicted. Then, epitopes and suitable adjuvant were assembled by molecular linkers to construct a multi-epitope vaccine. The computational tools predicted the tertiary structure, refined the tertiary structure and validated the final vaccine construct. The effectiveness of the vaccine was evaluated via molecular docking, molecular dynamics simulation, and in silico immune simulation. The vaccine model had good binding affinity and stability with MHC-I, MHC-II, and toll-like receptors (TLR-1, 2, 4) as well as activation of T cells, IgM, IgG, IFN-γ and IL-2 responses. Furthermore, after codon optimization of the vaccine sequence, this sequence was cloned in E. coli plasmid vector pET-30a (+) within restriction sites of HindIII and BamHI.

CONCLUSIONS

This study, for the first time, introduced a multi-epitope vaccine based on OmpA, OmpD and enterotoxin (Stn) of NTS that could stimulate T and B cell immune responses and produced in the prokaryotic system. This vaccine was validated in-silico phase which is an essential study to reduce challenges before in vitro and in vivo studies.

Human adenovirus type 7 virus-like particle vaccine induces Dendritic cell maturation through the TLR4/NF-κB pathway and is highly immunogenic

Human adenovirus type 7 (HAdv-7) infection is the main cause of upper respiratory tract infection, bronchitis and pneumonia in children. At present, there are no anti-adenovirus drugs or preventive vaccines in the market. Therefore, it is necessary to develop a safe and effective anti-adenovirus type 7 vaccine. In this study, we designed a virus-like particle vaccine expressing the epitopes of hexon and penton of adenovirus type 7 with hepatitis B core protein (HBc) as the vector to induce high-level humoral and cellular immune responses. To evaluate the effectiveness of the vaccine, we first detected the expression of molecular markers on the surface of antigen presenting cells and the secretion of proinflammatory cytokines in vitro. We then measured the levels of neutralizing antibodies and T cell activation in vivo. The results showed that the HAdv-7 virus-like particles (VLPs) recombinant subunit vaccine could activate the innate immune response, including the TLR4/NF-κB pathway which upregulated the expression of MHC II, CD80, CD86, CD40 and cytokines. The vaccine also triggered a strong neutralizing antibody and cellular immune response and activated T lymphocytes. Therefore, the HAdv-7 VLPs promoted humoral and cellular immune responses, thereby potentially enhancing protection against HAdv-7 infection.

The mode of action of tapasin on major histocompatibility class I (MHC-I) molecules

Tapasin (Tsn) plays a critical role in antigen processing and presentation by major histocompatibility complex class I (MHC-I) molecules. The mechanism of Tsn-mediated peptide loading and exchange hinges on the conformational dynamics governing the interaction of Tsn and MHC-I with recent structural and functional studies pinpointing the critical sites of direct or allosteric regulation. In this review, we highlight these recent findings and relate them to the extensive molecular and cellular data that are available for these evolutionary interdependent proteins. Furthermore, allotypic differences of MHC-I with regard to the editing and chaperoning function of Tsn are reviewed and related to the mechanistic observations. Finally, evolutionary aspects of the mode of action of Tsn will be discussed, a short comparison with the Tsn-related molecule TAPBPR (Tsn-related protein) will be given, and the impact of Tsn on noncanonical MHC-I molecules will be described.

[Molecular mechanisms of impaired antigenic presentation as a cause of tumor escape from immune surveillance]

The review summarizes data on the features of antigen presentation in tumor cells. The molecular mechanisms of the antitumor immune response are considered with an emphasis on the ability of tumor cells to avoid the action of immune surveillance. The features of expression of MHC molecules depending on treatment regimens are provided. Ways to improve existing and create new treatment regimens aimed at elimination of tumor cells because of antitumor immune response are discussed.

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.

Deep learning reveals predictive sequence concepts within immune repertoires to immunotherapy

T cell receptor (TCR) sequencing has been used to characterize the immune response to cancer. However, most analyses have been restricted to quantitative measures such as clonality that do not leverage the complementarity-determining region 3 (CDR3) sequence. We use DeepTCR, a framework of deep learning algorithms, to reveal sequence concepts that are predictive of response to immunotherapy. We demonstrate that DeepTCR can predict response and use the model to infer the antigenic specificities of the predictive signature and their unique dynamics during therapy. The predictive signature of nonresponse is associated with high frequencies of TCRs predicted to recognize tumor-specific antigens, and these tumor-specific TCRs undergo a higher degree of dynamic changes on therapy in nonresponders versus responders. These results are consistent with a biological model where the hallmark of nonresponders is an accumulation of tumor-specific T cells that undergo turnover on therapy, possibly because of the dysfunctional state of these T cells in nonresponders.

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens

Clostridium perfringens is a dangerous bacterium and known biological warfare weapon associated with several diseases, whose lethal toxins can produce necrosis in humans. However, there is no safe and fully effective vaccine against C. perfringens for humans yet. To address this problem, we computationally screened its whole proteome, identifying highly immunogenic proteins, domains, and epitopes. First, we identified that the proteins with the highest epitope density are Collagenase A, Exo-alpha-sialidase, alpha n-acetylglucosaminidase and hyaluronoglucosaminidase, representing potential recombinant vaccine candidates. Second, we further explored the toxins, finding that the non-toxic domain of Perfringolysin O is enriched in CTL and HTL epitopes. This domain could be used as a potential sub-unit vaccine to combat gas gangrene. And third, we designed a multi-epitope protein containing 24 HTL-epitopes and 34 CTL-epitopes from extracellular regions of transmembrane proteins. Also, we analyzed the structural properties of this novel protein using molecular dynamics. Altogether, we are presenting a thorough immunoinformatic exploration of the whole proteome of C. perfringens, as well as promising whole-protein, domain-based and multi-epitope vaccine candidates. These can be evaluated in preclinical trials to assess their immunogenicity and protection against C. perfringens infection.

Refining the DC-targeting vaccination for preventing emerging infectious diseases

The development of safe, long-term, effective vaccines is still a challenge for many infectious diseases. Thus, the search of new vaccine strategies and production platforms that allow rapidly and effectively responding against emerging or reemerging pathogens has become a priority in the last years. Targeting the antigens directly to dendritic cells (DCs) has emerged as a new approach to enhance the immune response after vaccination. This strategy is based on the fusion of the antigens of choice to monoclonal antibodies directed against specific DC surface receptors such as CD40. Since time is essential, in silico approaches are of high interest to select the most immunogenic and conserved epitopes to improve the T- and B-cells responses. The purpose of this review is to present the advances in DC vaccination, with special focus on DC targeting vaccines and epitope mapping strategies and provide a new framework for improving vaccine responses against infectious diseases.

Exploring whole proteome to contrive multi-epitope-based vaccine for NeoCoV: An immunoinformtics and in-silico approach

Neo-Coronavirus (NeoCoV) is a novel Betacoronavirus (β-CoVs or Beta-CoVs) discovered in bat specimens in South Africa during 2011. The viral sequence is highly similar to Middle East Respiratory Syndrome, particularly that of structural proteins. Thus, scientists have emphasized the threat posed by NeoCoV associated with human angiotensin-converting enzyme 2 (ACE2) usage, which could lead to a high death rate and faster transmission rate in humans. The development of a NeoCoV vaccine could provide a promising option for the future control of the virus in case of human infection. In silico predictions can decrease the number of experiments required, making the immunoinformatics approaches cost-effective and convenient. Herein, with the aid of immunoinformatics and reverse vaccinology, we aimed to formulate a multi-epitope vaccine that may be used to prevent and treat NeoCoV infection. Based on the NeoCoV proteins, B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were shortlisted. Four vaccines (Neo-1-4) were devised by fusing shortlisted epitopes with appropriate adjuvants and linkers. The secondary and three-dimensional structures of final vaccines were then predicted. The binding interactions of these potential vaccines with toll-like immune receptors (TLR-2, TLR-3, and TLR-4) and major histocompatibility complex molecules (MHC-I and II) reveal that they properly fit into the receptors' binding domains. Besides, Neo-1 and Neo-4 vaccines exhibited better docking energies of -101.08 kcal/mol and -114.47 kcal/mol, respectively, with TLR-3 as compared to other vaccine constructs. The constructed vaccines are highly antigenic, non-allergenic, soluble, non-toxic, and topologically assessable with good physiochemical characteristics. Codon optimization and in-silico cloning confirmed efficient expression of the designed vaccines in Escherichia coli strain K12. In-silico immune simulation indicated that Neo-1 and Neo-4 vaccines could induce a strong immune response against NeoCoV. Lastly, the binding stability and strong binding affinity of Neo-1 and Neo-4 with TLR-3 receptor were validated using molecular dynamics simulations and free energy calculations (Molecular Mechanics/Generalized Born Surface Area method). The final vaccines require experimental validation to establish their safety and effectiveness in preventing NeoCoV infections.

New vistas unfold: Chicken MHC molecules reveal unexpected ways to present peptides to the immune system

The functions of a wide variety of molecules with structures similar to the classical class I and class II molecules encoded by the major histocompatibility complex (MHC) have been studied by biochemical and structural studies over decades, with many aspects for humans and mice now enshrined in textbooks as dogma. However, there is much variation of the MHC and MHC molecules among the other jawed vertebrates, understood in the most detail for the domestic chicken. Among the many unexpected features in chickens is the co-evolution between polymorphic TAP and tapasin genes with a dominantly-expressed class I gene based on a different genomic arrangement compared to typical mammals. Another important discovery was the hierarchy of class I alleles for a suite of properties including size of peptide repertoire, stability and cell surface expression level, which is also found in humans although not as extreme, and which led to the concept of generalists and specialists in response to infectious pathogens. Structural studies of chicken class I molecules have provided molecular explanations for the differences in peptide binding compared to typical mammals. These unexpected phenomena include the stringent binding with three anchor residues and acidic residues at the peptide C-terminus for fastidious alleles, and the remodelling binding sites, relaxed binding of anchor residues in broad hydrophobic pockets and extension at the peptide C-terminus for promiscuous alleles. The first few studies for chicken class II molecules have already uncovered unanticipated structural features, including an allele that binds peptides by a decamer core. It seems likely that the understanding of how MHC molecules bind and present peptides to lymphocytes will broaden considerably with further unexpected discoveries through biochemical and structural studies for chickens and other non-mammalian vertebrates.

Comprehensive analysis of mycobacterium tuberculosis antigen-specific CD4+ T cell responses restricted by single HLA class II allotype in an individual

Mycobacterium tuberculosis infection is generally asymptomatic as latent tuberculosis, but it is still known as the world’s leading bacterial cause of death. The diagnosis of latent tuberculosis infection relies on the evidence of cellular immunity to mycobacterial antigens. Since the association between HLA class II and tuberculosis infection has been reported in several population groups, a detailed study on the CD4+ T cell response to major tuberculosis antigens is needed. To elucidate which HLA class II allotypes in an individual are preferentially used in tuberculosis, CD4+ T cells specific to TB10.4, Ag85b, ESAT-6, and CFP-10 of Mycobacterium tuberculosis antigens were analyzed comprehensively. A total of 33 healthy donors were analyzed by ex vivo and cultured ELISPOT using panels of artificial antigen-presenting cells expressing a single HLA class II allotype. The CD4+ T cell responses were increased by an average of 39-fold in cultured ELISPOT compared with ex vivo ELISPOT. In ex vivo and cultured ELISPOT, CD4+ T cell responses showed significantly higher by HLA-DR than those of HLA-DQ and HLA-DP locus. In cultured ELISPOT, 9 HLA-DR allotypes, 4 HLA-DQ allotypes, and 3 HLA-DP allotypes showed positive CD4+ T cell responses. Among ten donors with positive CD4+ T cell responses when tested for mixed Mycobacterium tuberculosis antigens, seven donors were positive for only a single allotype, and three were positive for two allotypes in an individual. However, only one allotype was used for a single antigen-specific response when a single tuberculosis antigen was used individually. These results on the distribution of HLA class II allotypes showing high CD4+ T-cell responses to Mycobacterium tuberculosis antigens and the intra-individual allotype dominance will provide valuable information for understanding the immunobiology and immunogenetics of tuberculosis, which can contribute to the development of more effective vaccines.

Susceptibility and Severity of COVID-19 Are Both Associated With Lower Overall Viral–Peptide Binding Repertoire of HLA Class I Molecules, Especially in Younger People

An important number of studies have been conducted on the potential association between human leukocyte antigen (HLA) genes and COVID-19 susceptibility and severity since the beginning of the pandemic. However, case–control and peptide-binding prediction methods tended to provide inconsistent conclusions on risk and protective HLA alleles, whereas some researchers suggested the importance of considering the overall capacity of an individual’s HLA Class I molecules to present SARS-CoV-2-derived peptides. To close the gap between these approaches, we explored the distributions of HLA-A, -B, -C, and -DRB1 1st-field alleles in 142 Iranian patients with COVID-19 and 143 ethnically matched healthy controls, and applied in silico predictions of bound viral peptides for each individual’s HLA molecules. Frequency comparison revealed the possible predisposing roles of HLA-A*03, B*35, and DRB1*16 alleles and the protective effect of HLA-A*32, B*58, B*55, and DRB1*14 alleles in the viral infection. None of these results remained significant after multiple testing corrections, except HLA-A*03, and no allele was associated with severity, either. Compared to peptide repertoires of individual HLA molecules that are more likely population-specific, the overall coverage of virus-derived peptides by one’s HLA Class I molecules seemed to be a more prominent factor associated with both COVID-19 susceptibility and severity, which was independent of affinity index and threshold chosen, especially for people under 60 years old. Our results highlight the effect of the binding capacity of different HLA Class I molecules as a whole, and the more essential role of HLA-A compared to HLA-B and -C genes in immune responses against SARS-CoV-2 infection.

Next-generation sequencing: unraveling genetic mechanisms that shape cancer immunotherapy efficacy

Immunity is governed by fundamental genetic processes. These processes shape the nature of immune cells and set the rules that dictate the myriad complex cellular interactions that power immune systems. Everything from the generation of T cell receptors and antibodies, control of epitope presentation, and recognition of pathogens by the immunoediting of cancer cells is, in large part, made possible by core genetic mechanisms and the cellular machinery that they encode. In the last decade, next-generation sequencing has been used to dissect the complexities of cancer immunity with potent effect. Sequencing of exomes and genomes has begun to reveal how the immune system recognizes “foreign” entities and distinguishes self from non-self, especially in the setting of cancer. High-throughput analyses of transcriptomes have revealed deep insights into how the tumor microenvironment affects immunotherapy efficacy. In this Review, we discuss how high-throughput sequencing has added to our understanding of how immune systems interact with cancer cells and how cancer immunotherapies work.

dbPepNeo2.0: A Database for Human Tumor Neoantigen Peptides From Mass Spectrometry and TCR Recognition

Neoantigens are widely reported to induce T-cell response and lead to tumor regression, indicating a promising potential to immunotherapy. Previously, we constructed an open-access database, i.e., dbPepNeo, providing a systematic resource for human tumor neoantigens to storage and query. In order to expand data volume and application scope, we updated dbPepNeo to version 2.0 (http://www.biostatistics.online/dbPepNeo2). Here, we provide about 801 high-confidence (HC) neoantigens (increased by 170%) and 842,289 low-confidence (LC) HLA immunopeptidomes (increased by 107%). Notably, 55 class II HC neoantigens and 630 neoantigen-reactive T-cell receptor-β (TCRβ) sequences were firstly included. Besides, two new analytical tools are developed, DeepCNN-Ineo and BLASTdb. DeepCNN-Ineo predicts the immunogenicity of class I neoantigens, and BLASTdb performs local alignments to look for sequence similarities in dbPepNeo2.0. Meanwhile, the web features and interface have been greatly improved and enhanced.

Human herpesvirus diversity is altered in HLA class I binding peptides

Herpesviruses are ubiquitous, genetically diverse DNA viruses, with long-term presence in humans associated with infrequent but significant pathology. Human leukocyte antigen (HLA) class I presents intracellularly derived peptide fragments from infected tissue cells to CD8+ T and natural killer cells, thereby directing antiviral immunity. Allotypes of highly polymorphic HLA class I are distinguished by their peptide binding repertoires. Because this HLA class I variation is a major determinant of herpesvirus disease, we examined if sequence diversity of virus proteins reflects evasion of HLA presentation. Using population genomic data from Epstein–Barr virus (EBV), human cytomegalovirus (HCMV), and Varicella–Zoster virus, we tested whether diversity differed between the regions of herpesvirus proteins that can be recognized, or not, by HLA class I. Herpesviruses exhibit lytic and latent infection stages, with the latter better enabling immune evasion. Whereas HLA binding peptides of lytic proteins are conserved, we found that EBV and HCMV proteins expressed during latency have increased peptide sequence diversity. Similarly, latent, but not lytic, herpesvirus proteins have greater population structure in HLA binding than nonbinding peptides. Finally, we found patterns consistent with EBV adaption to the local HLA environment, with less efficient recognition of EBV isolates by high-frequency HLA class I allotypes. Here, the frequency of CD8+ T cell epitopes inversely correlated with the frequency of HLA class I recognition. Previous analyses have shown that pathogen-mediated natural selection maintains exceptional polymorphism in HLA residues that determine peptide recognition. Here, we show that HLA class I peptide recognition impacts diversity of globally widespread pathogens.

The intrinsic and microenvironmental features of diffuse midline glioma; implications for the development of effective immunotherapeutic treatment strategies

Diffuse midline glioma (DMG), including those of the brainstem (diffuse intrinsic pontine glioma), are pediatric tumors of the central nervous system (CNS). Recognized as the most lethal of all childhood cancers, palliative radiotherapy remains the only proven treatment option, however, even for those that respond, survival is only temporarily extended. DMG harbor an immunologically “cold” tumor microenvironment (TME) with few infiltrating immune cells. The mechanisms underpinning the cold TME are not well understood. Low expression levels of immune checkpoint proteins, including PD-1, PD-L1, and CTLA-4, are recurring features of DMG and likely contribute to the lack of response to immune checkpoint inhibitors (ICIs). The unique epigenetic signatures (including stem cell-like methylation patterns), a low tumor mutational burden, and recurring somatic mutations (H3K27M, TP53, ACVR1, MYC, and PIK3CA), possibly play a role in the reduced efficacy of traditional immunotherapies. Therefore, to circumvent the lack of efficacy thus far seen for the use of ICIs, adoptive cell transfer (including chimeric antigen receptor T cells) and the use of oncolytic viruses, are currently being evaluated for the treatment of DMG. It remains an absolute imperative that we improve our understanding of DMG’s intrinsic and TME features if patients are to realize the potential benefits offered by these sophisticated treatments. Herein, we summarize the limitations of immunotherapeutic approaches, highlight the emerging safety and clinical efficacy shown for sophisticated cell-based therapies, as well as the evolving knowledge underpinning the DMG-immune axis, to guide the development of immunotherapies that we hope will improve outcomes.

Evaluating performance of existing computational models in predicting CD8+ T cell pathogenic epitopes and cancer neoantigens

T cell recognition of a cognate peptide-major histocompatibility complex (pMHC) presented on the surface of infected or malignant cells is of the utmost importance for mediating robust and long-term immune responses. Accurate predictions of cognate pMHC targets for T cell receptors would greatly facilitate identification of vaccine targets for both pathogenic diseases and personalized cancer immunotherapies. Predicting immunogenic peptides therefore has been at the center of intensive research for the past decades but has proven challenging. Although numerous models have been proposed, performance of these models has not been systematically evaluated and their success rate in predicting epitopes in the context of human pathology has not been measured and compared. In this study, we evaluated the performance of several publicly available models, in identifying immunogenic CD8+ T cell targets in the context of pathogens and cancers. We found that for predicting immunogenic peptides from an emerging virus such as severe acute respiratory syndrome coronavirus 2, none of the models perform substantially better than random or offer considerable improvement beyond HLA ligand prediction. We also observed suboptimal performance for predicting cancer neoantigens. Through investigation of potential factors associated with ill performance of models, we highlight several data- and model-associated issues. In particular, we observed that cross-HLA variation in the distribution of immunogenic and non-immunogenic peptides in the training data of the models seems to substantially confound the predictions. We additionally compared key parameters associated with immunogenicity between pathogenic peptides and cancer neoantigens and observed evidence for differences in the thresholds of binding affinity and stability, which suggested the need to modulate different features in identifying immunogenic pathogen versus cancer peptides. Overall, we demonstrate that accurate and reliable predictions of immunogenic CD8+ T cell targets remain unsolved; thus, we hope our work will guide users and model developers regarding potential pitfalls and unsettled questions in existing immunogenicity predictors.

Functional Profile of CD8+ T-Cells in Response to HLA-A*02:01-Restricted Mutated Epitopes Derived from the Gag Protein of Circulating HIV-1 Strains from Medellín, Colombia

CD8⁺ T-cells play a crucial role in the control of HIV replication. HIV-specific CD8⁺ T-cell responses rapidly expand since the acute phase of the infection, and it has been observed that HIV controllers harbor CD8⁺ T-cells with potent anti-HIV capacity. The development of CD8⁺ T-cell-based vaccine against HIV-1 has focused on searching for immunodominant epitopes. However, the strong immune pressure of CD8⁺ T-cells causes the selection of viral variants with mutations in immunodominant epitopes. Since HIV-1 mutations are selected under the context of a specific HLA-I, the circulation of viral variants with these mutations is highly predictable based on the most prevalent HLA-I within a population. We previously demonstrated the adaptation of circulating strains of HIV-1 to the HLA-A*02 molecule by identifying mutations under positive selection located in GC9 and SL9 epitopes derived from the Gag protein. Also, we used an in silico prediction approach and evaluated whether the mutations found had a higher or lower affinity to the HLA-A*02. Although this strategy allowed predicting the interaction between mutated peptides and HLA-I, the functional response of CD8⁺ T-cells that these peptides induce is unknown. In the present work, peripheral blood mononuclear cells from 12 HIV-1⁺ HLA-A*02:01⁺ individuals were stimulated with the mutated and wild-type peptides derived from the GC9 and SL9 epitopes. The functional profile of CD8⁺ T-cells was evaluated using flow cytometry, and the frequency of subpopulations was determined according to their number of functions and the polyfunctionality index. The results suggest that the quality of the response (polyfunctionality) could be associated with the binding affinity of the peptide to the HLA molecule, and the functional profile of specific CD8⁺ T-cells to mutated epitopes in individuals under cART is maintained.

In silico analysis of mutant epitopes in new SARS-CoV-2 lineages suggest global enhanced CD8+ T cell reactivity and also signs of immune response escape

SARS-CoV-2 variants of concern have emerged since the COVID-19 outburst, notably the lineages detected in the UK, South Africa, and Brazil. Their increased transmissibility and higher viral load put them in the spotlight. Much has been investigated on the ability of those new variants to evade antibody recognition. However, little attention has been given to pre-existing and induced SARS-CoV-2-specific CD8+ T cell responses by new lineages. In this work, we predicted SARS-CoV-2-specific CD8+ T cell epitopes from the main variants of concern and their potential to trigger or hinder CD8+ T cell response by using HLA binding and TCR reactivity in silico predictions. Also, we estimated the population's coverage for different lineages, which accounts for the ability to present a set of peptides based on the most frequent HLA alleles of a given population. We considered binding predictions to 110 ccClass I HLA alleles from 29 countries to investigate differences in the fraction of individuals expected to respond to a given epitope set from new and previous lineages. We observed a higher population coverage for the variant detected in the UK (B.1.1.7), and South Africa (B.1.351), as well as for the Brazilian P.1 lineage, but not P.2, compared to the reference lineage. Moreover, individual mutations such as Spike N501Y and Nucleocapsid D138Y were predicted to have an overall stronger affinity through HLA-I than the reference sequence while Spike E484K shows signs of evasion. In summary, we provided evidence for the existence of potentially immunogenic and conserved epitopes across new SARS-CoV-2 variants, but also mutant peptides exhibiting diminished or abolished HLA-I binding. It also highlights the augmented population coverage for three new lineages. Whether these changes imply more T cell reactivity or potential to evade from CD8+ T cell responses requires experimental verification.

Epitope length variants balance protective immune responses and viral escape in HIV-1 infection

Cytotoxic T lymphocyte (CTL) and natural killer (NK) cell responses to a single optimal 10-mer epitope (KK10) in the human immunodeficiency virus type-1 (HIV-1) protein p24Gag are associated with enhanced immune control in patients expressing human leukocyte antigen (HLA)-B∗27:05. We find that proteasomal activity generates multiple length variants of KK10 (4-14 amino acids), which bind TAP and HLA-B∗27:05. However, only epitope forms ≥8 amino acids evoke peptide length-specific and cross-reactive CTL responses. Structural analyses reveal that all epitope forms bind HLA-B∗27:05 via a conserved N-terminal motif, and competition experiments show that the truncated epitope forms outcompete immunogenic epitope forms for binding to HLA-B∗27:05. Common viral escape mutations abolish (L136M) or impair (R132K) production of KK10 and longer epitope forms. Peptide length influences how well the inhibitory NK cell receptor KIR3DL1 binds HLA-B∗27:05 peptide complexes and how intraepitope mutations affect this interaction. These results identify a viral escape mechanism from CTL and NK responses based on differential antigen processing and peptide competition.

Biomarkers of response to PD-1 pathway blockade

The binding of T cell immune checkpoint proteins programmed death 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to their ligands allows immune evasion by tumours. The development of therapeutic antibodies, termed checkpoint inhibitors, that bind these molecules or their ligands, has provided a means to release this brake on the host anti-tumour immune response. However, these drugs are costly, are associated with potentially severe side effects, and only benefit a small subset of patients. It is therefore important to identify biomarkers that discriminate between responders and non-responders. This review discusses the determinants for a successful response to antibodies that bind PD-1 or its ligand PD-L1, dividing them into markers found in the tumour biopsy and those in non-tumour samples. It provides an update on the established predictive biomarkers (tumour PD-L1 expression, tumour mismatch repair deficiency and tumour mutational burden) and assesses the evidence for new potential biomarkers.

Mechanisms of MHC-I Downregulation and Role in Immunotherapy Response

Immunotherapy has become a key therapeutic strategy in the treatment of many cancers. As a result, research efforts have been aimed at understanding mechanisms of resistance to immunotherapy and how anti-tumor immune response can be therapeutically enhanced. It has been shown that tumor cell recognition by the immune system plays a key role in effective response to T cell targeting therapies in patients. One mechanism by which tumor cells can avoid immunosurveillance is through the downregulation of Major Histocompatibility Complex I (MHC-I). Downregulation of MHC-I has been described as a mechanism of intrinsic and acquired resistance to immunotherapy in patients with cancer. Depending on the mechanism, the downregulation of MHC-I can sometimes be therapeutically restored to aid in anti-tumor immunity. In this article, we will review current research in MHC-I downregulation and its impact on immunotherapy response in patients, as well as possible strategies for therapeutic upregulation of MHC-I.

Involvement of Th1Th17 Cell Subpopulations in the Immune Responses of Mothers Who Gave Birth to Children with Congenital Zika Syndrome (CZS)

High levels of T helper 17 cell (Th17)-related cytokines have been shown in acute Zika virus (ZIKV) infection. We hypothesized that the high levels of Th17-related cytokines, associated with a regulatory environment during pregnancy, create a favorable milieu for the differentiation of CD4+Th17 cells. We present data from a cross-sectional study on mothers who confirmed ZIKV infection by qRT-PCR and their children. We also recruited non-pregnant women infected with ZIKV in the same period. ZIKV infection occurred between 2015 and 2017. We collected samples for this study between 2018 and 2019, years after the initial infection. We highlight that, after in vitro stimulation with ZIKV CD4 megapool (ZIKV MP), we found a lower frequency of IL-17-producing CD4+ T cells (Th17), especially in the mothers, confirmed by the decrease in IL-17 production in the supernatant. However, a higher frequency of CD4+ IL-17+ IFN-γ+ T cells (Th1Th17) responding to the ZIKV MP was observed in the cells of the mothers and children but not in those of the non-pregnant women. Our data indicate that the priming of CD4 T cells of the Th1Th17 phenotype occurred preferentially in the mothers who gave birth to children with CZS and in the children.

An Update on "Reverse Vaccinology": The Pathway from Genomes and Epitope Predictions to Tailored, Recombinant Vaccines

In this chapter, we review the computational approaches that have led to a new generation of vaccines in recent years. There are many alternative routes to develop vaccines based on the concept of reverse vaccinology. They all follow the same basic principles-mining available genome and proteome information for antigen candidates, and recombinantly expressing them for vaccine production. Some of the same principles have been used successfully for cancer therapy approaches. In this review, we focus on infectious diseases, describing the general workflow from bioinformatic predictions of antigens and epitopes down to examples where such predictions have been used successfully for vaccine development.

Germline HLA landscape does not predict efficacy of pembrolizumab monotherapy across solid tumor types

We evaluated the impact of class I and class II human leukocyte antigen (HLA) genotypes, heterozygosity, and diversity on the efficacy of pembrolizumab. Seventeen pembrolizumab clinical trials across eight tumor types and one basket trial in patients with advanced solid tumors were included (n > 3,500 analyzed). Germline DNA was genotyped using a custom genotyping array. HLA diversity (measured by heterozygosity and evolutionary divergence) across class I loci was not associated with improved response to pembrolizumab, either within each tumor type evaluated or across all patients. Similarly, HLA heterozygosity at each class I and class II gene was not associated with response to pembrolizumab after accounting for the number of tests conducted. No conclusive association between HLA genotype and response to pembrolizumab was identified in this dataset. Germline HLA genotype or diversity alone is not an important independent determinant of response to pembrolizumab and should not be used for clinical decision-making in patients treated with pembrolizumab.

Immunoinformatics prediction of potential immunodominant epitopes from human coronaviruses and association with autoimmunity

Cross-reactivity between different human coronaviruses (HCoVs) might contribute to COVID-19 outcomes. Here, we aimed to predict conserved peptides among different HCoVs that could elicit cross-reacting B cell and T cell responses. Three hundred fifty-one full-genome sequences of HCoVs, including SARS-CoV-2 (51), SARS-CoV-1 (50), MERS-CoV (50), and common cold species OC43 (50), NL63 (50), 229E (50), and HKU1 (50) were downloaded aligned using Geneious Prime 20.20. Identification of epitopes in the conserved regions of HCoVs was carried out using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. Further, we identified sequences that bind multiple common MHC and modeled the three-dimensional structures of the protein regions. The search yielded 73 linear and 35 discontinuous epitopes. A total of 16 B-cell and 19 T-cell epitopes were predicted through a comprehensive bioinformatic screening of conserved regions derived from HCoVs. The 16 potentially cross-reactive B-cell epitopes included 12 human proteins and four viral proteins among the linear epitopes. Likewise, we identified 19 potentially cross-reactive T-cell epitopes covering viral proteins. Interestingly, two conserved regions: LSFVSLAICFVIEQF (NSP2) and VVHSVNSLVSSMEVQSL (spike), contained several matches that were described epitopes for SARS-CoV. Most of the predicted B cells were buried within the SARS-CoV-2 protein regions’ functional domains, whereas T-cell stretched close to the functional domains. Additionally, most SARS-CoV-2 predicted peptides (80%) bound to different HLA types associated with autoimmune diseases. We identified a set of potential B cell and T cell epitopes derived from the HCoVs that could contribute to different diseases manifestation, including autoimmune disorders.

Revisiting the Principles of Designing a Vaccine

Immune principles formulated by Jenner, Pasteur, and early immunologists served as fundamental propositions for vaccine discovery against many dreadful pathogens. However, decisive success in the form of an efficacious vaccine still eludes for diseases such as tuberculosis, leishmaniasis, and trypanosomiasis. Several antileishmanial vaccine trials have been undertaken in past decades incorporating live, attenuated, killed, or subunit vaccination, but the goal remains unmet. In light of the above facts, we have to reassess the principles of vaccination by dissecting factors associated with the hosts' immune response. This chapter discusses the pathogen-associated perturbations at various junctures during the generation of the immune response which inhibits antigenic processing, presentation, or remodels memory T cell repertoire. This can lead to ineffective priming or inappropriate activation of memory T cells during challenge infection. Thus, despite a protective primary response, vaccine failure can occur due to altered immune environments in the presence of pathogens.

A machine learning model for ranking candidate HLA class I neoantigens based on known neoepitopes from multiple human tumor types

Tumor neoepitopes presented by major histocompatibility complex (MHC) class I are recognized by tumor-infiltrating lymphocytes (TIL) and are targeted by adoptive T-cell therapies. Identifying which mutant neoepitopes from tumor cells are capable of recognition by T cells can assist in the development of tumor-specific, cell-based therapies and can shed light on antitumor responses. Here, we generate a ranking algorithm for class I candidate neoepitopes by using next-generation sequencing data and a dataset of 185 neoepitopes that are recognized by HLA class I-restricted TIL from individuals with metastatic cancer. Random forest model analysis showed that the inclusion of multiple factors impacting epitope presentation and recognition increased output sensitivity and specificity compared to the use of predicted HLA binding alone. The ranking score output provides a set of class I candidate neoantigens that may serve as therapeutic targets and provides a tool to facilitate in vitro and in vivo studies aimed at the development of more effective immunotherapies.

In-Silico Vaccine Design Based on a Novel Vaccine Candidate Against Infections Caused by Acinetobacter baumannii

Acinetobacter baumannii is notorious for causing serious infections of the skin, lungs, soft tissues, bloodstream, and urinary tract. Despite the overwhelming information available so far, there has still been no approved vaccine in the market to prevent these infections. Therefore, this study focuses on developing a rational vaccine design using the technique of epitope mapping to curb the infections caused by A. baumannii. An outer membrane protein with immunogenic potential as well as all the properties of a good vaccine candidate was selected and used to calculate epitopes for selection on the basis of a low percentile rank, high binding scores, good immunological properties, and non-allergenicity. Thus, a 240 amino-acid vaccine sequence was obtained by manually joining all the epitopes in sequence-wise manner with the appropriate linkers, namely AAY, GPGPG, and EAAAK. Additionally, a 50S ribosomal protein L7/L12, agonist to the human innate immune receptors was attached to the N-terminus to increase the overall immune response towards the vaccine. As a result, enhanced overall protein stability, expression, immunostimulatory capabilities, and solubility of the designed construct were observed. Molecular dynamic simulations revealed the compactness and stability of the polypeptide construct. Moreover, molecular docking exhibited strong binding of the designed vaccine with TLR-4 and TLR-9. In-silico immune simulations indicated an immense increment in T-cell and B-cell populations. Bioinformatic tools also significantly assisted with optimizing codons which allowed for successful cloning of constructs into desired host vectors. Using in-silico tools to design a vaccine against A. baumannii demonstrated that this construct could pave the way for successfully combating infections caused by multidrug-resistant bacteria.

A Model of Minor Histocompatibility Antigens in Allogeneic Hematopoietic Cell Transplantation

Minor histocompatibility antigens (mHAg) composed of peptides presented by HLA molecules can cause immune responses involved in graft-versus-host disease (GVHD) and graft-versus-leukemia effects after allogeneic hematopoietic cell transplantation (HCT). The current study was designed to identify individual graft-versus-host genomic mismatches associated with altered risks of acute or chronic GVHD or relapse after HCT between HLA-genotypically identical siblings. Our results demonstrate that in allogeneic HCT between a pair of HLA-identical siblings, a mHAg manifests as a set of peptides originating from annotated proteins and non-annotated open reading frames, which i) are encoded by a group of highly associated recipient genomic mismatches, ii) bind to HLA allotypes in the recipient, and iii) evoke a donor immune response. Attribution of the immune response and consequent clinical outcomes to individual peptide components within this set will likely differ from patient to patient according to their HLA types.

Highly-contiguous bovine genomes underpin accurate functional analyses and updated nomenclature of MHC class I

The major histocompatibility complex (MHC) class I region of cattle is both highly polymorphic and, unlike many species, highly variable in gene content between haplotypes. Cattle MHC class I alleles were historically grouped by sequence similarity in the more conserved 3' end of the coding sequence to form phylogenetic allele groups. This has formed the basis of current cattle MHC class I nomenclature. We presently describe and compare five fully assembled MHC class I haplotypes using the latest cattle and yak genome assemblies. Of the five previously described "pseudogenes" in the cattle MHC class I region, Pseudogene 3 is putatively functional in all haplotypes and Pseudogene 6 and Pseudogene 7 are putatively functional in some haplotypes. This was reinforced by evidence of transcription. Based on full gene sequences as well as 3' coding sequence, we identified distinct subgroups of BoLA-3 and BoLA-6 that represent distinct genetic loci. We further examined allele-specific expression using transcriptomic data revealing that certain alleles are consistently weakly expressed compared to others. These observations will help to inform further studies into how MHC class I region variability influences T cell and natural killer cell functions in cattle.

Identification and Characterization of Rift Valley Fever Virus-Specific T Cells Reveals a Dependence on CD40/CD40L Interactions for Prevention of Encephalitis

Rift Valley fever virus (RVFV) is an arbovirus found throughout Africa. It causes disease that is typically mild and self-limiting; however, some infected individuals experience severe manifestations, including hepatitis, encephalitis, or even death. Reports of RVFV encephalitis are notable among immunosuppressed individuals, suggesting a role for adaptive immunity in preventing this severe complication. This phenomenon has been modeled in C57BL/6 mice depleted of CD4 T cells prior to infection with DelNSs RVFV (RVFV containing a deletion of nonstructural protein NSs), resulting in late-onset encephalitis accompanied by high levels of viral RNA in the brain in 30% of animals. In this study, we sought to define the specific type(s) of CD4 T cells that mediate protection from RVFV encephalitis. The viral epitopes targeted by CD4 and CD8 T cells were defined in C57BL/6 mice, and tetramers for both CD4 and CD8 T cells were generated. RVFV-specific CD8 T cells were expanded and of a cytotoxic and proliferating phenotype in the liver following infection. RVFV-specific CD4 T cells were identified in the liver and spleen following infection and phenotyped as largely Th1 or Tfh subtypes. Knockout mice lacking various aspects of pathways important in Th1 and Tfh development and function were used to demonstrate that T-bet, CD40, CD40L, and major histocompatibility complex class II (MHC-II) mediated protection from RVFV encephalitis, while gamma interferon (IFN-γ) and interleukin-12 (IL-12) were dispensable. Virus-specific antibody responses correlated with protection from encephalitis in all mouse strains, suggesting that Tfh/B cell interactions modulate clinical outcome in this model. IMPORTANCE The prevention of RVFV encephalitis requires intact adaptive immunity. In this study, we developed reagents to detect RVFV-specific T cells and provide evidence for Tfh cells and CD40/CD40L interactions as critical mediators of this protection.

CAR T cells with dual targeting of CD19 and CD22 in pediatric and young adult patients with relapsed or refractory B cell acute lymphoblastic leukemia: a phase 1 trial

Chimeric antigen receptor (CAR) T cells targeting CD19 or CD22 have shown remarkable activity in B cell acute lymphoblastic leukemia (B-ALL). The major cause of treatment failure is antigen downregulation or loss. Dual antigen targeting could potentially prevent this, but the clinical safety and efficacy of CAR T cells targeting both CD19 and CD22 remain unclear. We conducted a phase 1 trial in pediatric and young adult patients with relapsed or refractory B-ALL (n = 15) to test AUTO3, autologous transduced T cells expressing both anti-CD19 and anti-CD22 CARs (AMELIA trial, EUDRA CT 2016-004680-39). The primary endpoints were the incidence of grade 3–5 toxicity in the dose-limiting toxicity period and the frequency of dose-limiting toxicities. Secondary endpoints included the rate of morphological remission (complete response or complete response with incomplete bone marrow recovery) with minimal residual disease-negative response, as well as the frequency and severity of adverse events, expansion and persistence of AUTO3, duration of B cell aplasia, and overall and event-free survival. The study endpoints were met. AUTO3 showed a favorable safety profile, with no dose-limiting toxicities or cases of AUTO3-related severe cytokine release syndrome or neurotoxicity reported. At 1 month after treatment the remission rate (that is, complete response or complete response with incomplete bone marrow recovery) was 86% (13 of 15 patients). The 1 year overall and event-free survival rates were 60% and 32%, respectively. Relapses were probably due to limited long-term AUTO3 persistence. Strategies to improve CAR T cell persistence are needed to fully realize the potential of dual targeting CAR T cell therapy in B-ALL.

Bicistronic CAR T cells targeting CD19 and CD22 exhibit clinical activity and low toxicity in pediatric and young adult patients with B cell acute lymphoblastic leukemia, with relapses associated with limited CAR T cell persistence.