The majority of immunogenic epitopes generate CD4+ T cells that are dependent on MHC class II-bound peptide-flanking residues

Geometric deep learning improves generalizability of MHC-bound peptide predictions

The interaction between peptides and major histocompatibility complex (MHC) molecules is pivotal in autoimmunity, pathogen recognition and tumor immunity. Recent advances in cancer immunotherapies demand for more accurate computational prediction of MHC-bound peptides. We address the generalizability challenge of MHC-bound peptide predictions, revealing limitations in current sequence-based approaches. Our structure-based methods leveraging geometric deep learning (GDL) demonstrate promising improvement in generalizability across unseen MHC alleles. Further, we tackle data efficiency by introducing a self-supervised learning approach on structures (3D-SSL). Without being exposed to any binding affinity data, our 3D-SSL outperforms sequence-based methods trained on ~90 times more data points. Finally, we demonstrate the resilience of structure-based GDL methods to biases in binding data on an Hepatitis B virus vaccine immunopeptidomics case study. This proof-of-concept study highlights structure-based methods' potential to enhance generalizability and data efficiency, with possible implications for data-intensive fields like T-cell receptor specificity predictions.

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.

A targeted single mutation in influenza A virus universal epitope transforms immunogenicity and protective immunity via CD4+ T cell activation

CD4+ T cells are central to adaptive immunity. Their role in cross-protection in viral infections such as influenza and severe acute respiratory syndrome (SARS) is well documented; however, molecular rules governing T cell receptor (TCR) engagement of peptide-human leukocyte antigen (pHLA) class II are less understood. Here, we exploit an aspect of HLA class II presentation, the peptide-flanking residues (PFRs), to "tune" CD4+ T cell responses within an in vivo model system of influenza. Using a recombinant virus containing targeted substitutions at immunodominant HLA-DR1 epitopes, we demonstrate limited weight loss and improved clinical scores after heterosubtypic re-challenge. We observe enhanced protection linked to lung-derived influenza-specific CD4+ and CD8+ T cells prior to re-infection. Structural analysis of the ternary TCR:pHLA complex identifies that flanking amino acids influence side chains in the core 9-mer peptide, increasing TCR affinity. Augmentation of CD4+ T cell immunity is achievable with a single mutation, representing a strategy to enhance adaptive immunity that is decoupled from vaccine modality.

Harnessing autoimmunity with dominant self-peptide: Modulating the sustainability of tissue-preferential antigen-specific Tregs by governing the binding stability via peptide flanking residues

Sensitization to self-peptides induces various immunological responses, from autoimmunity to tumor immunity, depending on the peptide sequence; however, the underlying mechanisms remain unclear, and thus, curative therapeutic options considering immunity balance are limited. Herein, two overlapping dominant peptides of myelin proteolipid protein, PLP136-150 and PLP139-151, which induce different forms of experimental autoimmune encephalomyelitis (EAE), monophasic and relapsing EAE, respectively, were investigated. Mice with monophasic EAE exhibited highly resistant to EAE re-induction with any encephalitogenic peptides, whereas mice with relapsing EAE were susceptible, and progressed, to EAE re-induction. This resistance to relapse and re-induction in monophasic EAE mice was associated with the maintenance of potent CD69+CD103+CD4+CD25high regulatory T-cells (Tregs) enriched with antigen specificity, which expanded preferentially in the central nervous system with sustained suppressive activity. This tissue-preferential sustainability of potent antigen-specific Tregs was correlated with the antigenicity of PLP136-150, depending on its flanking residues. That is, the flanking residues of PLP136-150 enable to form pivotally arranged strong hydrogen bonds that secured its binding stability to MHC-class II. These potent Tregs acting tissue-preferentially were induced only by sensitization of PLP136-150, not by its tolerance induction, independent of EAE development. These findings suggest that, for optimal therapy, "benign autoimmunity" can be critically achieved through inverse vaccination with self-peptides by manipulating their flanking residues.

Expanding the MAPPs Assay to Accommodate MHC-II Pan Receptors for Improved Predictability of Potential T Cell Epitopes

A critical step in the immunogenicity cascade is attributed to human leukocyte antigen (HLA) II presentation triggering T cell immune responses. The liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based major histocompatibility complex (MHC) II-associated peptide proteomics (MAPPs) assay is implemented during preclinical risk assessments to identify biotherapeutic-derived T cell epitopes. Although studies indicate that HLA-DP and HLA-DQ alleles are linked to immunogenicity, most MAPPs studies are restricted to using HLA-DR as the dominant HLA II genotype due to the lack of well-characterized immunoprecipitating antibodies. Here, we address this issue by testing various commercially available clones of MHC-II pan (CR3/43, WR18, and Tü39), HLA-DP (B7/21), and HLA-DQ (SPV-L3 and 1a3) antibodies in the MAPPs assay, and characterizing identified peptides according to binding specificity. Our results reveal that HLA II receptor-precipitating reagents with similar reported specificities differ based on clonality and that MHC-II pan antibodies do not entirely exhibit pan-specific tendencies. Since no individual antibody clone is able to recover the complete HLA II peptide repertoire, we recommend a mixed strategy of clones L243, WR18, and SPV-L3 in a single immunoprecipitation step for more robust compound-specific peptide detection. Ultimately, our optimized MAPPs strategy improves the predictability and additional identification of T cell epitopes in immunogenicity risk assessments.

Induction of cancer neoantigens facilitates development of clinically relevant models for the study of pancreatic cancer immunobiology

Neoantigen burden and CD8 T cell infiltrate are associated with clinical outcome in pancreatic ductal adenocarcinoma (PDAC). A shortcoming of many genetic models of PDAC is the lack of neoantigen burden and limited T cell infiltrate. The goal of the present study was to develop clinically relevant models of PDAC by inducing cancer neoantigens in KP2, a cell line derived from the KPC model of PDAC. KP2 was treated with oxaliplatin and olaparib (OXPARPi), and a resistant cell line was subsequently cloned to generate multiple genetically distinct cell lines (KP2-OXPARPi clones). Clones A and E are sensitive to immune checkpoint inhibition (ICI), exhibit relatively high T cell infiltration, and have significant upregulation of genes involved in antigen presentation, T cell differentiation, and chemokine signaling pathways. Clone B is resistant to ICI and is similar to the parental KP2 cell line in terms of relatively low T cell infiltration and no upregulation of genes involved in the pathways noted above. Tumor/normal exome sequencing and in silico neoantigen prediction confirms successful generation of cancer neoantigens in the KP2-OXPARPi clones and the relative lack of cancer neoantigens in the parental KP2 cell line. Neoantigen vaccine experiments demonstrate that a subset of candidate neoantigens are immunogenic and neoantigen synthetic long peptide vaccines can restrain Clone E tumor growth. Compared to existing models, the KP2-OXPARPi clones better capture the diverse immunobiology of human PDAC and may serve as models for future investigations in cancer immunotherapies and strategies targeting cancer neoantigens in PDAC.

Insight into Cancer Immunity: MHCs, Immune Cells and Commensal Microbiota

Cancer cells circumvent immune surveillance via diverse strategies. In accordance, a large number of complex studies of the immune system focusing on tumor cell recognition have revealed new insights and strategies developed, largely through major histocompatibility complexes (MHCs). As one of them, tumor-specific MHC-II expression (tsMHC-II) can facilitate immune surveillance to detect tumor antigens, and thereby has been used in immunotherapy, including superior cancer prognosis, clinical sensitivity to immune checkpoint inhibition (ICI) therapy and tumor-bearing rejection in mice. NK cells play a unique role in enhancing innate immune responses, accounting for part of the response including immunosurveillance and immunoregulation. NK cells are also capable of initiating the response of the adaptive immune system to cancer immunotherapy independent of cytotoxic T cells, clearly demonstrating a link between NK cell function and the efficacy of cancer immunotherapies. Eosinophils were shown to feature pleiotropic activities against a variety of solid tumor types, including direct interactions with tumor cells, and accessorily affect immunotherapeutic response through intricating cross-talk with lymphocytes. Additionally, microbial sequencing and reconstitution revealed that commensal microbiota might be involved in the modulation of cancer progression, including positive and negative regulatory bacteria. They may play functional roles in not only mucosal modulation, but also systemic immune responses. Here, we present a panorama of the cancer immune network mediated by MHCI/II molecules, immune cells and commensal microbiota and a discussion of prospective relevant intervening mechanisms involved in cancer immunotherapies.

HLA class II immunogenic mutation burden predicts response to immune checkpoint blockade

BACKGROUND

Whereas human leukocyte antigen (HLA) class I mutation-associated neoantigen burden has been linked with response to immune checkpoint blockade (ICB), the role of HLA class II-restricted neoantigens in clinical responses to ICB is less studied. We used computational approaches to assess HLA class II immunogenic mutation (IMM) burden in patients with melanoma and lung cancer treated with ICB.

PATIENTS AND METHODS

We analyzed whole-exome sequence data from four cohorts of ICB-treated patients with melanoma (n = 110) and non-small-cell lung cancer (NSCLC) (n = 123). MHCnuggets, a neural network-based model, was applied to estimate HLA class II IMM burdens and cellular fractions of IMMs were calculated to assess mutation clonality. We evaluated the combined impact of HLA class II germline genetic variation and class II IMM burden on clinical outcomes. Correlations between HLA class II IMM burden and density of tumor-infiltrating lymphocytes were computed from expression data.

RESULTS

Responding tumors harbored a significantly higher HLA class II IMM burden for both melanoma and NSCLC (P ≤ 9.6e-3). HLA class II IMM burden was correlated with longer survival, particularly in the NSCLC cohort and in the context of low intratumoral IMM heterogeneity (P < 0.001). HLA class I and II IMM landscapes were largely distinct suggesting a complementary role for class II IMMs in tumor rejection. A higher HLA class II IMM burden was associated with CD4+ T-cell infiltration and programmed death-ligand 1 expression. Transcriptomic analyses revealed an inflamed tumor microenvironment for tumors harboring a high HLA class II IMM burden.

CONCLUSIONS

HLA class II IMM burden identified patients with NSCLC and melanoma that attained longer survival after ICB treatment. Our findings suggest that HLA class II IMMs may impact responses to ICB in a manner that is distinct and complementary to HLA class I-mediated responses.

High-resolution profiling of MHC II peptide presentation capacity reveals SARS-CoV-2 CD4 T cell targets and mechanisms of immune escape

Understanding peptide presentation by specific MHC alleles is fundamental for controlling physiological functions of T cells and harnessing them for therapeutic use. However, commonly used in silico predictions and mass spectroscopy have their limitations in precision, sensitivity, and throughput, particularly for MHC class II. Here, we present MEDi, a novel mammalian epitope display that allows an unbiased, affordable, high-resolution mapping of MHC peptide presentation capacity. Our platform provides a detailed picture by testing every antigen-derived peptide and is scalable to all the MHC II alleles. Given the urgent need to understand immune evasion for formulating effective responses to threats such as SARS-CoV-2, we provide a comprehensive analysis of the presentability of all SARS-CoV-2 peptides in the context of several HLA class II alleles. We show that several mutations arising in viral strains expanding globally resulted in reduced peptide presentability by multiple HLA class II alleles, while some increased it, suggesting alteration of MHC II presentation landscapes as a possible immune escape mechanism.

Identification of neoantigens for individualized therapeutic cancer vaccines

Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are not expressed in healthy tissues, they are attractive targets for therapeutic cancer vaccines. Because the vast majority of cancer mutations are unique to the individual patient, harnessing the full potential of this rich source of targets requires individualized treatment approaches. Many computational algorithms and machine-learning tools have been developed to identify mutations in sequence data, to prioritize those that are more likely to be recognized by T cells and to design tailored vaccines for every patient. In this Review, we fill the gaps between the understanding of basic mechanisms of T cell recognition of neoantigens and the computational approaches for discovery of somatic mutations and neoantigen prediction for cancer immunotherapy. We present a new classification of neoantigens, distinguishing between guarding, restrained and ignored neoantigens, based on how they confer proficient antitumour immunity in a given clinical context. Such context-based differentiation will contribute to a framework that connects neoantigen biology to the clinical setting and medical peculiarities of cancer, and will enable future neoantigen-based therapies to provide greater clinical benefit.

OUP accepted manuscript

Motivation

Computationally predicting major histocompatibility complex (MHC)-peptide binding affinity is an important problem in immunological bioinformatics. Recent cutting-edge deep learning-based methods for this problem are unable to achieve satisfactory performance for MHC class II molecules. This is because such methods generate the input by simply concatenating the two given sequences: (the estimated binding core of) a peptide and (the pseudo sequence of) an MHC class II molecule, ignoring biological knowledge behind the interactions of the two molecules. We thus propose a binding core-aware deep learning-based model, DeepMHCII, with a binding interaction convolution layer, which allows to integrate all potential binding cores (in a given peptide) with the MHC pseudo (binding) sequence, through modeling the interaction with multiple convolutional kernels.

Results

Extensive empirical experiments with four large-scale datasets demonstrate that DeepMHCII significantly outperformed four state-of-the-art methods under numerous settings, such as 5-fold cross-validation, leave one molecule out, validation with independent testing sets and binding core prediction. All these results and visualization of the predicted binding cores indicate the effectiveness of our model, DeepMHCII, and the importance of properly modeling biological facts in deep learning for high predictive performance and efficient knowledge discovery.

Availability and implementation

DeepMHCII is publicly available at https://github.com/yourh/DeepMHCII.

Supplementary information

Supplementary data are available at Bioinformatics online.

Peptides for T cell selection in the thymus

Major histocompatibility complex (MHC)-associated peptides generated and displayed by antigen-presenting cells in the thymus are essential for the generation of functional and self-tolerant T cells that protect our body from various pathogens. The peptides displayed by cortical thymic epithelial cells (cTECs) are generated by unique enzymatic machineries including the thymoproteasomes, and are involved in the positive selection of self-protective T cells. On the other hand, the peptides displayed by medullary thymic epithelial cells (mTECs) and thymic dendritic cells (DCs) are involved in further selection to establish self-tolerance in T cells. Although the biochemical nature of the peptide repertoire displayed in the thymus remains unclear, many studies have suggested a thymus-specific mechanism for the generation of MHC-associated peptides in the thymus. In this review, we summarize basic knowledge and recent advances in MHC-associated thymic peptides, focusing on the generation and function of thymoproteasome-dependent peptides specifically displayed by cTECs.

T cell receptor recognition of hybrid insulin peptides bound to HLA-DQ8

HLA-DQ8, a genetic risk factor in type I diabetes (T1D), presents hybrid insulin peptides (HIPs) to autoreactive CD4+ T cells. The abundance of spliced peptides binding to HLA-DQ8 and how they are subsequently recognised by the autoreactive T cell repertoire is unknown. Here we report, the HIP (GQVELGGGNAVEVLK), derived from splicing of insulin and islet amyloid polypeptides, generates a preferred peptide-binding motif for HLA-DQ8. HLA-DQ8-HIP tetramer⁺ T cells from the peripheral blood of a T1D patient are characterised by repeated TRBV5 usage, which matches the TCR bias of CD4+ T cells reactive to the HIP peptide isolated from the pancreatic islets of a patient with T1D. The crystal structure of three TRBV5+ TCR-HLA-DQ8-HIP complexes shows that the TRBV5-encoded TCR β-chain forms a common landing pad on the HLA-DQ8 molecule. The N- and C-termini of the HIP is recognised predominantly by the TCR α-chain and TCR β-chain, respectively, in all three TCR ternary complexes. Accordingly, TRBV5 + TCR recognition of HIP peptides might occur via a 'polarised' mechanism, whereby each chain within the αβTCR heterodimer recognises distinct origins of the spliced peptide presented by HLA-DQ8.

MHC heterogeneity and response of metastases to immunotherapy

In recent years, immunotherapy has proven to be an effective treatment against cancer. Cytotoxic T lymphocytes perform an important role in this anti-tumor immune response, recognizing cancer cells as foreign, through the presentation of tumor antigens by MHC class I molecules. However, tumors and metastases develop escape mechanisms for evading this immunosurveillance and may lose the expression of these polymorphic molecules to become invisible to cytotoxic T lymphocytes. In other situations, they may maintain MHC class I expression and promote immunosuppression of cytotoxic T lymphocytes. Therefore, the analysis of the expression of MHC class I molecules in tumors and metastases is important to elucidate these escape mechanisms. Moreover, it is necessary to determine the molecular mechanisms involved in these alterations to reverse them and recover the expression of MHC class I molecules on tumor cells. This review discusses the role and regulation of MHC class I expression in tumor progression. We focus on altered MHC class I phenotypes present in tumors and metastases, as well as the molecular mechanisms responsible for MHC-I alterations, emphasizing the mechanisms of recovery of the MHC class I molecules expression on cancer cells. The individualized study of the HLA class I phenotype of the tumor and the metastases of each patient will allow choosing the most appropriate immunotherapy treatment based on a personalized medicine.

HLA-DRB1 molecules and the presentation of anchor peptides from RhD, RhCE, and KEL proteins

BACKGROUND

Antigens from the Rh and Kell systems are recognized as the most immunogenic in clinical practice. This study evaluated the possible molecular mechanisms involved in the interaction of antigenic peptides with the DRB1 molecules, which help to explain the high frequency of anti-K and association of D + C antibodies in transfusion and incompatible pregnancy.

STUDY DESIGN AND METHODS

We included 201 patients with antibodies against antigens from the Rh and Kell systems and compare them with 174,015 controls. HLA-DRB1 genotyping and in silico analysis were performed. The NetMHCIIpan software was used to identify RhD-, RhCE-, and KEL-derived anchor peptides that bind to DRB1 molecules.

RESULTS

HLA-DRB1*15 is associated with an increased risk of D, C, E, and K alloimmunization, while the HLA-DRB1*01 and *12 alleles are overrepresented in patients with anti-C and anti-D, respectively. In silico analysis showed that three polymorphic points (60I, 68S, and 103S) common to C and D antigens can be presented by several DRB1 molecules, including DRB1*15:01. The DRB1*09:01 molecule, although not showing statistical significance, was able to interact strongly with almost all five anchor peptides from the sequence containing the polymorphic determinants of E antigen, except 217-WMFWPSVNS-225.

CONCLUSION

The DRB1*15 molecule has specific physicochemical characteristics in residues 11P and 13R in the P4 pocket that can favor the response to various antigenic peptides. Anti-K alloimmunization is unrestricted for interaction with specific DRB1 molecules, which suggests that almost all individuals in our population have DRB1 molecules capable of binding to KEL-derived anchor peptides and produce anti-K when stimulated.

MHCII3D-Robust Structure Based Prediction of MHC II Binding Peptides

Knowledge of MHC II binding peptides is highly desired in immunological research, particularly in the context of cancer, autoimmune diseases, or allergies. The most successful prediction methods are based on machine learning methods trained on sequences of experimentally characterized binding peptides. Here, we describe a complementary approach called MHCII3D, which is based on structural scaffolds of MHC II-peptide complexes and statistical scoring functions (SSFs). The MHC II alleles reported in the Immuno Polymorphism Database are processed in a dedicated 3D-modeling pipeline providing a set of scaffold complexes for each distinct allotype sequence. Antigen protein sequences are threaded through the scaffolds and evaluated by optimized SSFs. We compared the predictive power of MHCII3D with different sequence-based machine learning methods. The Pearson correlation to experimentally determine IC₅₀ values for MHC II Automated Server Benchmarks data sets from IEDB (Immune Epitope Database) is 0.42, which is in the competitor methods range. We show that MHCII3D is quite robust in leaving one molecule out tests and is therefore not prone to overfitting. Finally, we provide evidence that MHCII3D can complement the current sequence-based methods and help to identify problematic entries in IEDB. Scaffolds and MHCII3D executables can be freely downloaded from our web pages.

Role of Human Leukocyte Antigen System as A Predictive Biomarker for Checkpoint-Based Immunotherapy in Cancer Patients

Recent advances in cancer immunotherapy have clearly shown that checkpoint-based immunotherapy is effective in a small subgroup of cancer patients. However, no effective predictive biomarker has been identified so far. The major histocompatibility complex, better known in humans as human leukocyte antigen (HLA), is a very polymorphic gene complex consisting of more than 200 genes. It has a crucial role in activating an appropriate host immune response against pathogens and tumor cells by discriminating self and non-self peptides. Several lines of evidence have shown that down-regulation of expression of HLA class I antigen derived peptide complexes by cancer cells is a mechanism of tumor immune escape and is often associated to poor prognosis in cancer patients. In addition, it has also been shown that HLA class I and II antigen expression, as well as defects in the antigen processing machinery complex, may predict tumor responses in cancer immunotherapy. Nevertheless, the role of HLA in predicting tumor responses to checkpoint-based immunotherapy is still debated. In this review, firstly, we will describe the structure and function of the HLA system. Secondly, we will summarize the HLA defects and their clinical significance in cancer patients. Thirdly, we will review the potential role of the HLA as a predictive biomarker for checkpoint-based immunotherapy in cancer patients. Lastly, we will discuss the potential strategies that may restore HLA function to implement novel therapeutic strategies in cancer patients.

Neoantigen-specific CD4+ T-cell response is critical for the therapeutic efficacy of cryo-thermal therapy

Background

Traditional tumor thermal ablations, such as radiofrequency ablation (RFA) and cryoablation, can result in good local control of tumor, but traditional tumor thermal ablations are limited by poor long-term survival due to the failure of control of distal metastasis. Our previous studies developed a novel cryo-thermal therapy to treat the B16F10 melanoma mouse model. Long-term survival and T-cell-mediated durable antitumor immunity were achieved after cryo-thermal therapy, but whether tumor antigen-specific T-cells were augmented by cryo-thermal therapy was not determined.

Methods

The long-term antitumor therapeutic efficacy of cryo-thermal therapy was performed in B16F10 murine melanoma models. Splenocytes derived from mice treated with RFA or cryo-thermal therapy were coincubated with tumor antigen peptides to detect the frequency of antigen specific CD4⁺ and CD8⁺ T-cells by flow cytometry. Splenocytes were then stimulated and expanded by αCD3 or peptides and adoptive T-cell therapy experiments were performed to identify the antitumor efficacy of T-cells induced by RFA and cryo-thermal therapy. Naïve mice and tumor-bearing mice were used as control groups.

Results

Local cryo-thermal therapy generated a stronger systematic antitumor immune response than RFA and a long-lasting antitumor immunity that protected against tumor rechallenge. In vitro studies showed that the antigen-specific CD8⁺ T-cell response was induced by both cryo-thermal therapy and RFA, but the strong neoantigen-specific CD4⁺ T-cell response was only induced by cryo-thermal therapy. Cryo-thermal therapy-induced strong antitumor immune response was mainly mediated by CD4⁺ T-cells, particularly neoantigen-specific CD4⁺ T-cells.

Conclusion

Cryo-thermal therapy induced a stronger and broader antigen-specific memory T-cells. Specifically, cryo-thermal therapy, but not RFA, led to a strong neoantigen-specific CD4⁺ T-cell response that mediated the resistance to tumor challenge.

Role of ultraviolet mutational signature versus tumor mutation burden in predicting response to immunotherapy

Hydrophobic neoantigens are more immunogenic because they are better presented by the major histocompatibility complex and better recognized by T cells. Tumor cells can evade the immune response by expressing checkpoints such as programmed death ligand 1. Checkpoint blockade reactivates immune recognition and can be effective in diseases such as melanoma, which harbors a high tumor mutational burden (TMB). Cancers presenting low or intermediate TMB can also respond to checkpoint blockade, albeit less frequently, suggesting the need for biological markers predicting response. We calculated the hydrophobicity of neopeptides produced by probabilistic in silico simulation of the genomic UV exposure mutational signature. We also computed the hydrophobicity of potential neopeptides and extent of UV exposure based on the UV mutational signature enrichment (UVMSE) score in The Cancer Genome Atlas (TCGA; N = 3543 tumors), and in our cohort of 151 immunotherapy‐treated patients. In silico simulation showed that UV exposure significantly increased hydrophobicity of neopeptides, especially over multiple mutagenic cycles. There was also a strong correlation (R² = 0.953) between weighted UVMSE and hydrophobicity of neopeptides in TCGA melanoma patients. Importantly, UVMSE was able to predict better response (P = 0.0026), progression‐free survival (P = 0.036), and overall survival (P = 0.052) after immunotherapy in patients with low/intermediate TMB, but not in patients with high TMB. We show that higher UVMSE scores could be a useful predictor of better immunotherapy outcome, especially in patients with low/intermediate TMB, likely due to increased hydrophobicity (and hence immunogenicity) of neopeptides.

Expected immune recognition of COVID-19 virus by memory from earlier infections with common coronaviruses in a large part of the world population

SARS-CoV-2 is the coronavirus agent of the COVID-19 pandemic causing high mortalities. In contrast, the widely spread human coronaviruses OC43, HKU1, 229E, and NL63 tend to cause only mild symptoms. The present study shows, by in silico analysis, that these common human viruses are expected to induce immune memory against SARS-CoV-2 by sharing protein fragments (antigen epitopes) for presentation to the immune system by MHC class I. A list of such epitopes is provided. The number of these epitopes and the prevalence of the common coronaviruses suggest that a large part of the world population has some degree of specific immunity against SARS-CoV-2 already, even without having been infected by that virus. For inducing protection, booster vaccinations enhancing existing immunity are less demanding than primary vaccinations against new antigens. Therefore, for the discussion on vaccination strategies against COVID-19, the available immune memory against related viruses should be part of the consideration.

Expected immune recognition of COVID-19 virus by memory from earlier infections with common coronaviruses in a large part of the world population

SARS-CoV-2 is the coronavirus agent of the COVID-19 pandemic causing high mortalities. In contrast, the widely spread human coronaviruses OC43, HKU1, 229E, and NL63 tend to cause only mild symptoms. The present study shows, by in silico analysis, that these common human viruses are expected to induce immune memory against SARS-CoV-2 by sharing protein fragments (antigen epitopes) for presentation to the immune system by MHC class I. A list of such epitopes is provided. The number of these epitopes and the prevalence of the common coronaviruses suggest that a large part of the world population has some degree of specific immunity against SARS-CoV-2 already, even without having been infected by that virus. For inducing protection, booster vaccinations enhancing existing immunity are less demanding than primary vaccinations against new antigens. Therefore, for the discussion on vaccination strategies against COVID-19, the available immune memory against related viruses should be part of the consideration.

Cancer Cell-Intrinsic Expression of MHC Class II Regulates the Immune Microenvironment and Response to Anti-PD-1 Therapy in Lung Adenocarcinoma

MHC class II (MHCII) expression is usually restricted to APC but can be expressed by cancer cells. We examined the effect of cancer cell-specific MHCII (csMHCII) expression in lung adenocarcinoma on T cell recruitment to tumors and response to anti-PD-1 therapy using two orthotopic immunocompetent murine models of non-small cell lung cancer: CMT167 (CMT) and Lewis lung carcinoma (LLC). We previously showed that CMT167 tumors are eradicated by anti-PD1 therapy, whereas LLC tumors are resistant. RNA sequencing analysis of cancer cells recovered from tumors revealed that csMHCII correlated with response to anti-PD1 therapy, with immunotherapy-sensitive CMT167 cells being csMHCII positive, whereas resistant LLC cells were csMHCII negative. To test the functional effects of csMHCII, MHCII expression was altered on the cancer cells through loss- and gain-of-function of CIITA, a master regulator of the MHCII pathway. Loss of CIITA in CMT167 decreased csMHCII and converted tumors from anti-PD-1 sensitive to anti-PD-1 resistant. This was associated with lower levels of Th1 cytokines, decreased T cell infiltration, increased B cell numbers, and decreased macrophage recruitment. Conversely, overexpression of CIITA in LLC cells resulted in csMHCII in vitro and in vivo. Enforced expression of CIITA increased T cell infiltration and sensitized tumors to anti-PD-1 therapy. csMHCII expression was also examined in a subset of surgically resected human lung adenocarcinomas by multispectral imaging, which provided a survival benefit and positively correlated with T cell infiltration. These studies demonstrate a functional role for csMHCII in regulating T cell infiltration and sensitivity to anti-PD-1.

Pegylated recombinant human granulocyte colony-stimulating factor regulates the immune status of patients with small cell lung cancer

BACKGROUND

Small cell lung cancer (SCLC) is an aggressive disease involving immunodeficiency for which chemotherapy is the standard treatment. Pegylated recombinant human granulocyte colony-stimulating factor (PEG-rhG-CSF) is widely used for primary or secondary prophylaxis of febrile neutropenia (FN) in chemotherapy. However, whether PEG-rhG-CSF influences immune cells, such as lymphocytes, remains unclear.

METHODS

A total of 17 treatment-naïve SCLC patients were prospectively enrolled and divided into the PEG-rhG-CSF and control groups according to their FN risk. Longitudinal sampling of peripheral blood was performed before, after and 4-6 days after the first cycle of chemotherapy. Flow cytometry was used to assess lymphocyte subsets, including CD3⁺ T, CD4⁺ T, CD8⁺ T, NK, and B cells. The diversity and clonality of the T-cell receptor (TCR) repertoire was analyzed by next-generation sequencing.

RESULTS

In the PEG-rhG-CSF group, the proportions of CD3⁺ T and CD4⁺ T cells had increased significantly (P = 0.002, P = 0.020, respectively), whereas there was no increase in CD8⁺ T cells. Further, TCR diversity increased (P = 0.009) and clonality decreased (P = 0.004) significantly after PEG-rhG-CSF treatment. However, these factors showed opposite trends before and after chemotherapy. Vβ and Jβ gene fragment types, which determine TCR diversity, were significantly amplified in the PEG-rhG-CSF group. The change in TCR diversity was significantly correlated with changes in the CD3⁺ T or CD4⁺ T cell proportions, but not the CD8⁺ T cell proportion.

CONCLUSIONS

PEG-rhG-CSF regulates the immune status of SCLC patients; CD4⁺ T cells may be the main effector cells involved in this process. These findings may optimize the treatment of SCLC.

KEY POINTS

PEG-rhG-CSF regulates SCLC immunity. PEG-rhG-CSF increased CD3⁺ T and CD4⁺ T cell proportions. PEG-rhG-CSF increased TCR diversity and decreased clonality in peripheral blood. Change in TCR diversity were correlated with CD3⁺ T or CD4⁺ T changes.

Personalized Neo-Epitope Vaccines for Cancer Treatment

After more than a century of efforts to establish cancer immunotherapy in clinical practice, the advent of checkpoint inhibition (CPI) therapy was a critical breakthrough toward this direction (Hodi et al. in Cell Rep 13(2):412-424, 2010; Wolchok et al. in N Engl J Med 369(2):122-133, 2013; Herbst et al. in Nature 515(7528):563-567, 2014; Tumeh et al. in Nature 515(7528):568-571, 2014). Further, CPIs shifted the focus from long studied shared tumor-associated antigens to mutated ones. As cancer is caused by mutations in somatic cells, the concept to utilize these correlates of 'foreignness' to enable recognition and lysis of the cancer cell by T cell immunity seems an obvious thing to do.

Human leukocyte antigen (HLA) class II peptide flanking residues tune the immunogenicity of a human tumor-derived epitope

CD4+ T-cells recognize peptide antigens, in the context of human leukocyte antigen (HLA) class II molecules (HLA-II), which through peptide-flanking residues (PFRs) can extend beyond the limits of the HLA binding. The role of the PFRs during antigen recognition is not fully understood; however, recent studies have indicated that these regions can influence T-cell receptor (TCR) affinity and pHLA-II stability. Here, using various biochemical approaches including peptide sensitivity ELISA and ELISpot assays, peptide-binding assays and HLA-II tetramer staining, we focused on CD4+ T-cell responses against a tumor antigen, 5T4 oncofetal trophoblast glycoprotein (5T4), which have been associated with improved control of colorectal cancer. Despite their weak TCR-binding affinity, we found that anti-5T4 CD4+ T-cells are polyfunctional and that their PFRs are essential for TCR recognition of the core bound nonamer. The high-resolution (1.95 Å) crystal structure of HLA-DR1 presenting the immunodominant 20-mer peptide 5T4111-130, combined with molecular dynamic simulations, revealed how PFRs explore the HLA-proximal space to contribute to antigen reactivity. These findings advance our understanding of what constitutes an HLA-II epitope and indicate that PFRs can tune weak affinity TCR-pHLA-II interactions.

Harnessing Tumor Mutations for Truly Individualized Cancer Vaccines

T cells are key effectors of anticancer immunity. They are capable of distinguishing tumor cells from normal ones by recognizing major histocompatibility complex-bound cancer-specific peptides. Accumulating evidence suggests that peptides associated with T cell-mediated tumor rejection arise predominantly from somatically mutated proteins and are unique to every patient's tumor. Knowledge of an individual's cancer mutanome (the entirety of cancer mutations) allows harnessing this enormous tumor cell-specific repertoire of highly immunogenic antigens for individualized cancer vaccines. This review outlines the preclinical and clinical state of individualized cancer vaccine development and the challenges ahead.

Ligandomes obtained from different HLA-class II-molecules are homologous for N- and C-terminal residues outside the peptide-binding cleft

Human CD4+ T lymphocytes play an important role in inducing potent immune responses. T cells are activated and stimulated by peptides presented in human leucocyte antigen (HLA)-class II molecules. These HLA-class II molecules typically present peptides of between 12 and 20 amino acids in length. The region that interacts with the HLA molecule, designated as the peptide-binding core, is highly conserved in the residues which anchor the peptide to the molecule. In addition, as these peptides are the product of proteolytic cleavages, certain conserved residues may be expected at the N- and C-termini outside the binding core. To study whether similar conserved residues are present in different cell types, potentially harbouring different proteolytic enzymes, the ligandomes of HLA-DRB1*03:01/HLA-DRB > 1 derived from two different cell types (dendritic cells and EBV-transformed B cells) were identified with mass spectrometry and the binding core and N- and C-terminal residues of a total of 16,568 peptides were analysed using the frequencies of the amino acids in the human proteome. Similar binding motifs were found as well as comparable conservations in the N- and C-terminal residues. Furthermore, the terminal conservations of these ligandomes were compared to the N- and C-terminal conservations of the ligandome acquired from dendritic cells homozygous for HLA-DRB1*04:01. Again, comparable conservations were evident with only minor differences. Taken together, these data show that there are conservations in the terminal residues of peptides, presumably the result of the activity of proteases involved in antigen processing.

Quantification of Uncertainty in Peptide-MHC Binding Prediction Improves High-Affinity Peptide Selection for Therapeutic Design

The computational identification of peptides that can bind the major histocompatibility complex (MHC) with high affinity is an essential step in developing personal immunotherapies and vaccines. We introduce PUFFIN, a deep residual network-based computational approach that quantifies uncertainty in peptide-MHC affinity prediction that arises from observational noise and the lack of relevant training examples. With PUFFIN's uncertainty metrics, we define binding likelihood, the probability a peptide binds to a given MHC allele at a specified affinity threshold. Compared to affinity point estimates, we find that binding likelihood correlates better with the observed affinity and reduces false positives in high-affinity peptide design. When applied to examine an existing peptide vaccine, PUFFIN identifies an alternative vaccine formulation with higher binding likelihood. PUFFIN is freely available for download at http://github.com/gifford-lab/PUFFIN.

Immunogenicity of Protein Pharmaceuticals

Protein therapeutics have drastically changed the landscape of treatment for many diseases by providing a regimen that is highly specific and lacks many off-target toxicities. The clinical utility of many therapeutic proteins has been undermined by the potential development of unwanted immune responses against the protein, limiting their efficacy and negatively impacting its safety profile. This review attempts to provide an overview of immunogenicity of therapeutic proteins, including immune mechanisms and factors influencing immunogenicity, impact of immunogenicity, preclinical screening methods, and strategies to mitigate immunogenicity.

Biological Consequences of MHC-II Expression by Tumor Cells in Cancer

Immunotherapy has emerged as a key pillar of cancer treatment. To build upon the recent successes of immunotherapy, intense research efforts are aimed at a molecular understanding of antitumor immune responses, identification of biomarkers of immunotherapy response and resistance, and novel strategies to circumvent resistance. These studies are revealing new insight into the intricacies of tumor cell recognition by the immune system, in large part through MHCs. Although tumor cells widely express MHC-I, a subset of tumors originating from a variety of tissues also express MHC-II, an antigen-presenting complex traditionally associated with professional antigen-presenting cells. MHC-II is critical for antigen presentation to CD4+ T lymphocytes, whose role in antitumor immunity is becoming increasingly appreciated. Accumulating evidence demonstrates that tumor-specific MHC-II associates with favorable outcomes in patients with cancer, including those treated with immunotherapies, and with tumor rejection in murine models. Herein, we will review current research regarding tumor-enriched MHC-II expression and regulation in a range of human tumors and murine models, and the possible therapeutic applications of tumor-specific MHC-II.

Footprints of antigen processing boost MHC class II natural ligand predictions

Background

Major histocompatibility complex class II (MHC-II) molecules present peptide fragments to T cells for immune recognition. Current predictors for peptide to MHC-II binding are trained on binding affinity data, generated in vitro and therefore lacking information about antigen processing.

Methods

We generate prediction models of peptide to MHC-II binding trained with naturally eluted ligands derived from mass spectrometry in addition to peptide binding affinity data sets.

Results

We show that integrated prediction models incorporate identifiable rules of antigen processing. In fact, we observed detectable signals of protease cleavage at defined positions of the ligands. We also hypothesize a role of the length of the terminal ligand protrusions for trimming the peptide to the MHC presented ligand.

Conclusions

The results of integrating binding affinity and eluted ligand data in a combined model demonstrate improved performance for the prediction of MHC-II ligands and T cell epitopes and foreshadow a new generation of improved peptide to MHC-II prediction tools accounting for the plurality of factors that determine natural presentation of antigens.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0594-6) contains supplementary material, which is available to authorized users.

Improved methods for predicting peptide binding affinity to MHC class II molecules

Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2.

Quantification of HLA-DM-Dependent Major Histocompatibility Complex of Class II Immunopeptidomes by the Peptide Landscape Antigenic Epitope Alignment Utility

The major histocompatibility complex of class II (MHCII) immunopeptidome represents the repertoire of antigenic peptides with the potential to activate CD4⁺ T cells. An understanding of how the relative abundance of specific antigenic epitopes affects the outcome of T cell responses is an important aspect of adaptive immunity and offers a venue to more rationally tailor T cell activation in the context of disease. Recent advances in mass spectrometric instrumentation, computational power, labeling strategies, and software analysis have enabled an increasing number of stratified studies on HLA ligandomes, in the context of both basic and translational research. A key challenge in the case of MHCII immunopeptidomes, often determined for different samples at distinct conditions, is to derive quantitative information on consensus epitopes from antigenic peptides of variable lengths. Here, we present the design and benchmarking of a new algorithm [peptide landscape antigenic epitope alignment utility (PLAtEAU)] allowing the identification and label-free quantification (LFQ) of shared consensus epitopes arising from series of nested peptides. The algorithm simplifies the complexity of the dataset while allowing the identification of nested peptides within relatively short segments of protein sequences. Moreover, we apply this algorithm to the comparison of the ligandomes of cell lines with two different expression levels of the peptide-exchange catalyst HLA-DM. Direct comparison of LFQ intensities determined at the peptide level is inconclusive, as most of the peptides are not significantly enriched due to poor sampling. Applying the PLAtEAU algorithm for grouping of the peptides into consensus epitopes shows that more than half of the total number of epitopes is preferentially and significantly enriched for each condition. This simplification and deconvolution of the complex and ambiguous peptide-level dataset highlights the value of the PLAtEAU algorithm in facilitating robust and accessible quantitative analysis of immunopeptidomes across cellular contexts. In silico analysis of the peptides enriched for each HLA-DM expression conditions suggests a higher affinity of the pool of peptides isolated from the high DM expression samples. Interestingly, our analysis reveals that while for certain autoimmune-relevant epitopes their presentation increases upon DM expression others are clearly edited out from the peptidome.

Conserved Binding Regions Provide the Clue for Peptide-Based Vaccine Development: A Chemical Perspective

Synthetic peptides have become invaluable biomedical research and medicinal chemistry tools for studying functional roles, i.e., binding or proteolytic activity, naturally-occurring regions’ immunogenicity in proteins and developing therapeutic agents and vaccines. Synthetic peptides can mimic protein sites; their structure and function can be easily modulated by specific amino acid replacement. They have major advantages, i.e., they are cheap, easily-produced and chemically stable, lack infectious and secondary adverse reactions and can induce immune responses via T- and B-cell epitopes. Our group has previously shown that using synthetic peptides and adopting a functional approach has led to identifying Plasmodium falciparumconserved regions binding to host cells. Conserved high activity binding peptides’ (cHABPs) physicochemical, structural and immunological characteristics have been taken into account for properly modifying and converting them into highly immunogenic, protection-inducing peptides (mHABPs) in the experimental Aotus monkey model. This article describes stereo–electron and topochemical characteristics regarding major histocompatibility complex (MHC)-mHABP-T-cell receptor (TCR) complex formation. Some mHABPs in this complex inducing long-lasting, protective immunity have been named immune protection-inducing protein structures (IMPIPS), forming the subunit components in chemically synthesized vaccines. This manuscript summarizes this particular field and adds our recent findings concerning intramolecular interactions (H-bonds or π-interactions) enabling proper IMPIPS structure as well as the peripheral flanking residues (PFR) to stabilize the MHCII-IMPIPS-TCR interaction, aimed at inducing long-lasting, protective immunological memory.

CD4 and CD8 T lymphocyte interplay in controlling tumor growth

The outstanding clinical success of immune checkpoint blockade has revived the interest in underlying mechanisms of the immune system that are capable of eliminating tumors even in advanced stages. In this scenario, CD4 and CD8 T cell responses are part of the cancer immune cycle and both populations significantly influence the clinical outcome. In general, the immune system has evolved several mechanisms to protect the host against cancer. Each of them has to be undermined or evaded during cancer development to enable tumor outgrowth. In this review, we give an overview of T lymphocyte-driven control of tumor growth and discuss the involved tumor-suppressive mechanisms of the immune system, such as senescence surveillance, cancer immunosurveillance, and cancer immunoediting with respect to recent clinical developments of immunotherapies. The main focus is on the currently existing knowledge about the CD4 and CD8 T lymphocyte interplay that mediates the control of tumor growth.

Computational Identification and Characterization of a Promiscuous T-Cell Epitope on the Extracellular Protein 85B of Mycobacterium spp. for Peptide-Based Subunit Vaccine Design

Tuberculosis (TB) is a reemerging disease that remains as a leading cause of morbidity and mortality in humans. To identify and characterize a T-cell epitope suitable for vaccine design, we have utilized the Vaxign server to assess all antigenic proteins of Mycobacterium spp. recorded to date in the Protegen database. We found that the extracellular protein 85B displayed the most robust antigenicity among the proteins identified. Computational tools for identifying T-cell epitopes predicted an epitope, 181-QQFIYAGSLSALLDP-195, that could bind to at least 13 major histocompatibility complexes, revealing the promiscuous nature of the epitope. Molecular docking simulation demonstrated that the epitope could bind to the binding groove of MHC II and MHC I molecules by several hydrogen bonds. Molecular docking analysis further revealed that the epitope had a distinctive binding pattern to all DRB1 and A and B series of MHC molecules and presented almost no polymorphism in its binding site. Moreover, using "Allele Frequency Database," we checked the frequency of HLA alleles in the worldwide population and found a higher frequency of both class I and II HLA alleles in individuals living in TB-endemic regions. Our results indicate that the identified peptide might be a universal candidate to produce an efficient epitope-based vaccine for TB.

A deimmunised form of the ribotoxin, α-sarcin, lacking CD4+ T cell epitopes and its use as an immunotoxin warhead

Fungal ribotoxins that block protein synthesis can be useful warheads in the context of a targeted immunotoxin. α-Sarcin is a small (17 kDa) fungal ribonuclease produced by Aspergillus giganteus that functions by catalytically cleaving a single phosphodiester bond in the sarcin–ricin loop of the large ribosomal subunit, thus making the ribosome unrecognisable to elongation factors and leading to inhibition of protein synthesis. Peptide mapping using an ex vivo human T cell assay determined that α-sarcin contained two T cell epitopes; one in the N-terminal 20 amino acids and the other in the C-terminal 20 amino acids. Various mutations were tested individually within each epitope and then in combination to isolate deimmunised α-sarcin variants that had the desired properties of silencing T cell epitopes and retention of the ability to inhibit protein synthesis (equivalent to wild-type, WT α-sarcin). A deimmunised variant (D9T/Q142T) demonstrated a complete lack of T cell activation in in vitro whole protein human T cell assays using peripheral blood mononuclear cells from donors with diverse HLA allotypes. Generation of an immunotoxin by fusion of the D9T/Q142T variant to a single-chain Fv targeting Her2 demonstrated potent cell killing equivalent to a fusion protein comprising the WT α-sarcin. These results represent the first fungal ribotoxin to be deimmunised with the potential to construct a new generation of deimmunised immunotoxin therapeutics.

Single-molecule motions of MHC class II rely on bound peptides

The major histocompatibility complex (MHC) class II protein can bind peptides of different lengths in the region outside the peptide-binding groove. Peptide-flanking residues (PFRs) contribute to the binding affinity of the peptide for MHC and change the immunogenicity of the peptide/MHC complex with regard to T cell receptor (TCR). The mechanisms underlying these phenomena are currently unknown. The molecular flexibility of the peptide/MHC complex may be an important determinant of the structures recognized by certain T cells. We used single-molecule x-ray analysis (diffracted x-ray tracking (DXT)) and fluorescence anisotropy to investigate these mechanisms. DXT enabled us to monitor the real-time Brownian motion of the peptide/MHC complex and revealed that peptides without PFRs undergo larger rotational motions than peptides with PFRs. Fluorescence anisotropy further revealed that peptides without PFRs exhibit slightly larger motions on the nanosecond timescale. These results demonstrate that peptides without PFRs undergo dynamic motions in the groove of MHC and consequently are able to assume diverse structures that can be recognized by T cells.

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4(+) T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1 .

Mutant MHC class II epitopes drive therapeutic immune responses to cancer

Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient's tumour possesses a unique set of mutations ('the mutanome') that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient's individual tumour-specific mutations. Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4(+) T cells. Vaccination with such CD4(+) immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4(+) T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient's tumour with vaccines produced 'just in time'.

HLA-DRB1*07:01 allele is primarily associated with the Diego a alloimmunization in a Brazilian population

BACKGROUND

The Diego blood group presents a major polymorphic site at Residue 854, causing a proline (Di(b) antigen) to leucine (Di(a) antigen) substitution. Di(a) alloimmunization has been observed among Asian and Native South American populations. Considering that Brazilians represent a genetically diverse population, and considering that we have observed a high incidence of Di(a) alloimmunization, we typed HLA-DRB1 alleles in these patients and performed in silico studies to investigate the possible associated mechanisms.

STUDY DESIGN AND METHODS

We studied 212 alloimmunized patients, of whom 24 presented immunoglobulin G anti-Di(a) , 15 received Di(a+) red blood cells and were not immunized, and 1008 were healthy donors. HLA typing was performed using commercial kits. In silico analyses were performed using the TEPITOPEpan software to identify Diego-derived anchor peptide binding to HLA-DRB1 molecules. Residue alignment was performed using the IMGT/HLA for amino acid identity and homology analyses.

RESULTS

HLA-DRB1*07:01 allele was overrepresented in Di(a) -alloimmunized patients compared to nonimmunized patients and to healthy donors. Two motifs were predicted to be potential epitopes for Di(a) alloimmunization, the WVVKSTLAS motif was predicted to bind several HLA-DR molecules, and the FVLILTVPL motif exhibited highest affinity for the HLA-DRB1*07:01 molecule. Pocket 4 of the DRB1*07:01 molecule contained specific residues not found in other HLA-DRB1 molecules, particularly those at Positions 13(Y), 74(Q), and 78(V).

CONCLUSION

Individuals carrying the HLA-DRB1*07:01 allele present an increased risk for Di(a) alloimmunization. The identification of susceptible individuals and the knowledge of potential sensitization peptides are relevant approaches for transfusion care, diagnostic purposes, and desensitization therapies.

Determining the breadth of the respiratory syncytial virus-specific T cell response

Respiratory syncytial virus (RSV) is the most common cause of viral lower respiratory tract infections in infants and children under the age of 5. Studies examining RSV infection in susceptible BALB/c mice indicate that both CD4 and CD8 T cells not only contribute to viral clearance but also facilitate RSV-induced disease. However, efforts to understand the mechanisms by which RSV-specific T cells mediate disease following acute RSV infection have been hampered by the lack of defined RSV-specific T cell epitopes. Using an overlapping peptide library spanning each of the RSV-derived proteins, intracellular cytokine staining for gamma interferon was utilized to identify novel RSV-specific CD4 and CD8 T cell epitopes. Five novel CD8 T cell epitopes were revealed within the RSV fusion (F) protein and glycoprotein (G). In addition, five previously unidentified CD4 T cell epitopes were discovered, including epitopes in the phosphoprotein (P), polymerase protein (L), M2-1 protein, and nucleoprotein (N). Though the initial CD4 T cell epitopes were 15 amino acids in length, synthesis of longer peptides increased the frequency of responding CD4 T cells. Our results indicate that CD4 T cell epitopes that are 17 amino acids in length result in more optimal CD4 T cell stimulation than the commonly used 15-mer peptides.

IMPORTANCE

Respiratory syncytial virus (RSV) is the leading cause of hospitalization for lower respiratory tract infection in children. T cells play a critical role in clearing an acute RSV infection, as well as contributing to RSV-induced disease. Here we examined the breadth of the RSV-specific T cell response, using for the first time an overlapping peptide library spanning the entire viral genome. We identified 5 new CD4 and 5 new CD8 T cell epitopes, including a CD8 T cell epitope within the G protein that was previously believed not to elicit a CD8 T cell response. Importantly, we also demonstrated that the use of longer, 17-mer peptides elicits a higher frequency of responding CD4 T cells than the more commonly used 15-mer peptides. Our results demonstrate the breadth of the CD4 and CD8 T cell response to RSV and demonstrate the importance of using longer peptides when stimulating CD4 T cell responses.

Respiratory syncytial virus: current progress in vaccine development

Respiratory syncytial virus (RSV) is the etiological agent for a serious lower respiratory tract disease responsible for close to 200,000 annual deaths worldwide. The first infection is generally most severe, while re-infections usually associate with a milder disease. This observation and the finding that re-infection risks are inversely associated with neutralizing antibody titers suggest that immune responses generated toward a first RSV exposure can significantly reduce morbidity and mortality throughout life. For more than half a century, researchers have endeavored to design a vaccine for RSV that can mimic or improve upon natural protective immunity without adverse events. The virus is herein described together with the hurdles that must be overcome to develop a vaccine and some current vaccine development approaches.

HLA-DM constrains epitope selection in the human CD4 T cell response to vaccinia virus by favoring the presentation of peptides with longer HLA-DM-mediated half-lives

HLA-DM (DM) is a nonclassical MHC class II (MHC II) protein that acts as a peptide editor to mediate the exchange of peptides loaded onto MHC II during Ag presentation. Although the ability of DM to promote peptide exchange in vitro and in vivo is well established, the role of DM in epitope selection is still unclear, especially in human response to infectious disease. In this study, we addressed this question in the context of the human CD4 T cell response to vaccinia virus. We measured the IC(50), intrinsic dissociation t(1/2), and DM-mediated dissociation t(1/2) for a large set of peptides derived from the major core protein A10L and other known vaccinia epitopes bound to HLA-DR1 and compared these properties to the presence and magnitude of peptide-specific CD4(+) T cell responses. We found that MHC II-peptide complex kinetic stability in the presence of DM distinguishes T cell epitopes from nonrecognized peptides in A10L peptides and also in a set of predicted tight binders from the entire vaccinia genome. Taken together, these analyses demonstrate that DM-mediated dissociation t(1/2) is a strong and independent factor governing peptide immunogenicity by favoring the presentation of peptides with greater kinetic stability in the presence of DM.

Modification of the carboxy-terminal flanking region of a universal influenza epitope alters CD4⁺ T-cell repertoire selection

Human CD4(+) αβ T cells are activated via T-cell receptor recognition of peptide epitopes presented by major histocompatibility complex (MHC) class II (MHC-II). The open ends of the MHC-II binding groove allow peptide epitopes to extend beyond a central nonamer core region at both the amino- and carboxy-terminus. We have previously found that these non-bound C-terminal residues can alter T cell activation in an MHC allele-transcending fashion, although the mechanism for this effect remained unclear. Here we show that modification of the C-terminal peptide-flanking region of an influenza hemagglutinin (HA(305-320)) epitope can alter T-cell receptor binding affinity, T-cell activation and repertoire selection of influenza-specific CD4(+) T cells expanded from peripheral blood. These data provide the first demonstration that changes in the C-terminus of the peptide-flanking region can substantially alter T-cell receptor binding affinity, and indicate a mechanism through which peptide flanking residues could influence repertoire selection.

Respiratory syncytial virus vaccine development

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract viral disease in infants and young children. Presently, there are no explicit recommendations for RSV treatment apart from supportive care. The virus is therefore responsible for an estimated 160,000 deaths per year worldwide. Despite half a century of dedicated research, there remains no licensed vaccine product. Herein are described past and current efforts to harness innate and adaptive immune potentials to combat RSV. A plethora of candidate vaccine products and strategies are reviewed. The development of a successful RSV vaccine may ultimately stem from attention to historical lessons, in concert with an integral partnering of immunology and virology research fields.