Molecular mimicry in multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) is a severe, post-infectious sequela of SARS-CoV-2 infection1,2, yet the pathophysiological mechanism connecting the infection to the broad inflammatory syndrome remains unknown. Here we leveraged a large set of samples from patients with MIS-C to identify a distinct set of host proteins targeted by patient autoantibodies including a particular autoreactive epitope within SNX8, a protein involved in regulating an antiviral pathway associated with MIS-C pathogenesis. In parallel, we also probed antibody responses from patients with MIS-C to the complete SARS-CoV-2 proteome and found enriched reactivity against a distinct domain of the SARS-CoV-2 nucleocapsid protein. The immunogenic regions of the viral nucleocapsid and host SNX8 proteins bear remarkable sequence similarity. Consequently, we found that many children with anti-SNX8 autoantibodies also have cross-reactive T cells engaging both the SNX8 and the SARS-CoV-2 nucleocapsid protein epitopes. Together, these findings suggest that patients with MIS-C develop a characteristic immune response to the SARS-CoV-2 nucleocapsid protein that is associated with cross-reactivity to the self-protein SNX8, demonstrating a mechanistic link between the infection and the inflammatory syndrome, with implications for better understanding a range of post-infectious autoinflammatory diseases.

CD8+T-cell response to mutated HLA-B*35-restricted Gag HY9 and HA9 epitopes from HIV-1 variants from Medellin, Colombia

The HLA-B*35 alleles have been associated with a slow or rapid progression of HIV-1 infection. However, the mechanisms related to HIV-1 progression have yet to be entirely understood. Several reports indicate that the binding affinity between the HLA-I molecule and peptides could be associated with an increased CD8+ T-cell response. Novel HLA-B*35-restricted mutated variants have been described from HSNQVSQNY (HY9) and HPVHAGPIA (HA9) epitopes. Bioinformatic analysis has indicated that these mutated epitopes show low and high binding affinity towards HLA-B*35, respectively. However, the polyfunctionality of CD8+ T-cells stimulated with these mutated and wild-type epitopes has yet to be reported. The results suggest that the low-binding affinity H124 N/S125 N/N126S mutated peptide in the HY9 epitope induced a lower percentage of CD107a+CD8+ T-cells than the wild-type epitope. Instead, the high-binding affinity peptides I223V and I223A in the HA9 epitope induced a significantly higher frequency of polyfunctional CD8+ T-cells. Also, a higher proportion of CD8+ T-cells with two functions, with Granzyme B+ Perforin+ being the predominant profile, was observed after stimulation with mutated peptides associated with high binding affinity in the HA9 epitope. These results suggest that the high-affinity mutated peptides induced a more polyfunctional CD8+ T-cell response, which could be related to the control of viral replication.

Development of a Stable Peptide-Major Histocompatibility Complex (MHC) via Sortase and Click Chemistry

T cells play a crucial role in antitumor immune responses and the clearance of infected cells. They identify their targets through the binding of T-cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules present in cancer cells, infected cells, and antigen-presenting cells. This interaction is often weak, requiring multimeric pMHC molecules to enhance the avidity for identifying antigen-specific T cells. Current exchangeable pMHC-I tetramerization methods may overlook TCRs recognizing less stable yet immunogenic peptides. In vivo applications targeting antigen-specific T cells demand the genetic synthesis of a pMHC fusion for each unique peptide antigen, which poses a significant challenge. To address these challenges, we developed a sortase and click chemistry-mediated approach for generating stable pMHC molecules. Leveraging sortase technology, we introduced an azide click-handle near the N-terminus of β2m, proximal to the MHC-peptide-binding groove. Simultaneously, the peptide was engineered with a multi glycine linker and a C-terminal alkyne click-handle. Azide-alkyne click reactions efficiently immobilized the peptide onto the MHC molecule, providing a versatile and efficient method for pMHC generation. The resulting peptide-clicked-MHC specifically binds to its cognate TCR and remains stable for over 3 months at 4 °C in the absence of any additional free peptide. The stability of the pMHC and its affinity to cognate TCRs are influenced by the linker's nature and length. Multi glycine linkers outperform poly(ethylene glycol) (PEG) linkers in this regard. This technology expands the toolkit for identifying and targeting antigen-specific T cells, enhancing our understanding of cancer-specific immune responses, and has the potential to streamline the development of personalized immunotherapies.

Immunoinformatics-Based Design of Multi-epitope DNA and mRNA Vaccines Against Zika Virus

In this study, we used an immunoinformatics approach to predict antigenic epitopes of Zika virus (ZIKV) proteins to assist in designing a vaccine antigen against ZIKV. We performed the prediction of CD8+ T-lymphocyte and antigenic B-cell epitopes of ZIKV proteins. The binding interactions of T-cell epitopes with major histocompatibility complex class I (MHC-I) proteins were assessed. We selected the antigenic, conserved, nontoxic, and immunogenic epitopes, which indicated significant interactions with the human leucocyte antigen (HLA-A and HLA-B) alleles and worldwide population coverage of 76.35%. The predicted epitopes were joined with the help of linkers and an adjuvant. The vaccine antigen was then analyzed through molecular docking with TLR3 and TLR8, and it was in silico cloned in the pVAX1 vector to be used as a DNA vaccine and designed as a mRNA vaccine.

FASTMAP-a flexible and scalable immunopeptidomics pipeline for HLA- and antigen-specific T-cell epitope mapping based on artificial antigen-presenting cells

The study of peptide repertoires presented by major histocompatibility complex (MHC) molecules and the identification of potential T-cell epitopes contribute to a multitude of immunopeptidome-based treatment approaches. Epitope mapping is essential for the development of promising epitope-based approaches in vaccination as well as for innovative therapeutics for autoimmune diseases, infectious diseases, and cancer. It also plays a critical role in the immunogenicity assessment of protein therapeutics with regard to safety and efficacy concerns. The main challenge emerges from the highly polymorphic nature of the human leukocyte antigen (HLA) molecules leading to the requirement of a peptide mapping strategy for a single HLA allele. As many autoimmune diseases are linked to at least one specific antigen, we established FASTMAP, an innovative strategy to transiently co-transfect a single HLA allele combined with a disease-specific antigen into a human cell line. This approach allows the specific identification of HLA-bound peptides using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Using FASTMAP, we found a comparable spectrum of endogenous peptides presented by the most frequently expressed HLA alleles in the world's population compared to what has been described in literature. To ensure a reliable peptide mapping workflow, we combined the HLA alleles with well-known human model antigens like coagulation factor VIII, acetylcholine receptor subunit alpha, protein structures of the SARS-CoV-2 virus, and myelin basic protein. Using these model antigens, we have been able to identify a broad range of peptides that are in line with already published and in silico predicted T-cell epitopes of the specific HLA/model antigen combination. The transient co-expression of a single affinity-tagged MHC molecule combined with a disease-specific antigen in a human cell line in our FASTMAP pipeline provides the opportunity to identify potential T-cell epitopes/endogenously processed MHC-bound peptides in a very cost-effective, fast, and customizable system with high-throughput potential.

Diverging co-translational protein complex assembly pathways are governed by interface energy distribution

Protein-protein interactions are at the heart of all cellular processes, with the ribosome emerging as a platform, orchestrating the nascent-chain interplay dynamics. Here, to study the characteristics governing co-translational protein folding and complex assembly, we combine selective ribosome profiling, imaging, and N-terminomics with all-atoms molecular dynamics. Focusing on conserved N-terminal acetyltransferases (NATs), we uncover diverging co-translational assembly pathways, where highly homologous subunits serve opposite functions. We find that only a few residues serve as "hotspots," initiating co-translational assembly interactions upon exposure at the ribosome exit tunnel. These hotspots are characterized by high binding energy, anchoring the entire interface assembly. Alpha-helices harboring hotspots are highly thermolabile, folding and unfolding during simulations, depending on their partner subunit to avoid misfolding. In vivo hotspot mutations disrupted co-translational complexation, leading to aggregation. Accordingly, conservation analysis reveals that missense NATs variants, causing neurodevelopmental and neurodegenerative diseases, disrupt putative hotspot clusters. Expanding our study to include phosphofructokinase, anthranilate synthase, and nucleoporin subcomplex, we employ AlphaFold-Multimer to model the complexes' complete structures. Computing MD-derived interface energy profiles, we find similar trends. Here, we propose a model based on the distribution of interface energy as a strong predictor of co-translational assembly.

Instability of the HLA-E peptidome of HIV presents a major barrier to therapeutic targeting

Naturally occurring T cells that recognize microbial peptides via HLA-E, a nonpolymorphic HLA class Ib molecule, could provide the foundation for new universal immunotherapeutics. However, confidence in the biological relevance of putative ligands is crucial, given that the mechanisms by which pathogen-derived peptides can access the HLA-E presentation pathway are poorly understood. We systematically interrogated the HIV proteome using immunopeptidomic and bioinformatic approaches, coupled with biochemical and cellular assays. No HIV HLA-E peptides were identified by tandem mass spectrometry analysis of HIV-infected cells. In addition, all bioinformatically predicted HIV peptide ligands (>80) were characterized by poor complex stability. Furthermore, infected cell elimination assays using an affinity-enhanced T cell receptor bispecific targeted to a previously reported HIV Gag HLA-E epitope demonstrated inconsistent presentation of the peptide, despite normal HLA-E expression on HIV-infected cells. This work highlights the instability of the HIV HLA-E peptidome as a major challenge for drug development.

Transfer learning improves pMHC kinetic stability and immunogenicity predictions

The cellular immune response comprises several processes, with the most notable ones being the binding of the peptide to the Major Histocompability Complex (MHC), the peptide-MHC (pMHC) presentation to the surface of the cell, and the recognition of the pMHC by the T-Cell Receptor. Identifying the most potent peptide targets for MHC binding, presentation and T-cell recognition is vital for developing peptide-based vaccines and T-cell-based immunotherapies. Data-driven tools that predict each of these steps have been developed, and the availability of mass spectrometry (MS) datasets has facilitated the development of accurate Machine Learning (ML) methods for class-I pMHC binding prediction. However, the accuracy of ML-based tools for pMHC kinetic stability prediction and peptide immunogenicity prediction is uncertain, as stability and immunogenicity datasets are not abundant. Here, we use transfer learning techniques to improve stability and immunogenicity predictions, by taking advantage of a large number of binding affinity and MS datasets. The resulting models, TLStab and TLImm, exhibit comparable or better performance than state-of-the-art approaches on different stability and immunogenicity test sets respectively. Our approach demonstrates the promise of learning from the task of peptide binding to improve predictions on downstream tasks. The source code of TLStab and TLImm is publicly available at https://github.com/KavrakiLab/TL-MHC.

Molecular insights into the HLA-B35 molecules' classification associated with HIV control

Human leukocyte antigen (HLA) class I molecules have been shown to influence the immune response to HIV infection and acquired immunodeficiency syndrome progression. Polymorphisms within the HLA-B35 molecules divide the family into two groups, namely, Px and PY. The Px group is associated with deleterious effects and accelerated disease progression in HIV+ patients, whereas the PY group is not. The classification is based on the preferential binding of a tyrosine at the C-terminal part of the peptide in the PY group, and a nontyrosine residue in the Px group. However, there is a lack of knowledge on the molecular differences between the two groups. Here, we have investigated three HLA-B35 molecules, namely, HLA-B*35:01 (PY), HLA-B*35:03 (Px) and HLA-B*35:05 (unclassified). We selected an HIV-derived peptide, NY9, and demonstrated that it can trigger a polyfunctional CD8+ T-cell response in HLA-B*35:01+ /HIV+ patients. We determined that in the complex with the NY9 peptide, the PY molecule was more stable than the Px molecule. We solved the crystal structures of the three HLA molecules in complex with the NY9 peptide, and structural similarities with HLA-B*35:01 would classify the HLA-B*35:05 within the PY group. Interestingly, we found that HLA-B*35:05 can also bind a small molecule in its cleft, suggesting that small drugs could bind as well.

Therapeutic cancer vaccines: advancements, challenges, and prospects

With the development and regulatory approval of immune checkpoint inhibitors and adoptive cell therapies, cancer immunotherapy has undergone a profound transformation over the past decades. Recently, therapeutic cancer vaccines have shown promise by eliciting de novo T cell responses targeting tumor antigens, including tumor-associated antigens and tumor-specific antigens. The objective was to amplify and diversify the intrinsic repertoire of tumor-specific T cells. However, the complete realization of these capabilities remains an ongoing pursuit. Therefore, we provide an overview of the current landscape of cancer vaccines in this review. The range of antigen selection, antigen delivery systems development the strategic nuances underlying effective antigen presentation have pioneered cancer vaccine design. Furthermore, this review addresses the current status of clinical trials and discusses their strategies, focusing on tumor-specific immunogenicity and anti-tumor efficacy assessment. However, current clinical attempts toward developing cancer vaccines have not yielded breakthrough clinical outcomes due to significant challenges, including tumor immune microenvironment suppression, optimal candidate identification, immune response evaluation, and vaccine manufacturing acceleration. Therefore, the field is poised to overcome hurdles and improve patient outcomes in the future by acknowledging these clinical complexities and persistently striving to surmount inherent constraints.

Thioamide Analogues of MHC I Antigen Peptides

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

Machine learning methods and harmonized datasets improve immunogenic neoantigen prediction

The accurate selection of neoantigens that bind to class I human leukocyte antigen (HLA) and are recognized by autologous T cells is a crucial step in many cancer immunotherapy pipelines. We reprocessed whole-exome sequencing and RNA sequencing (RNA-seq) data from 120 cancer patients from two external large-scale neoantigen immunogenicity screening assays combined with an in-house dataset of 11 patients and identified 46,017 somatic single-nucleotide variant mutations and 1,781,445 neo-peptides, of which 212 mutations and 178 neo-peptides were immunogenic. Beyond features commonly used for neoantigen prioritization, factors such as the location of neo-peptides within protein HLA presentation hotspots, binding promiscuity, and the role of the mutated gene in oncogenicity were predictive for immunogenicity. The classifiers accurately predicted neoantigen immunogenicity across datasets and improved their ranking by up to 30%. Besides insights into machine learning methods for neoantigen ranking, we have provided homogenized datasets valuable for developing and benchmarking companion algorithms for neoantigen-based immunotherapies.

The impact of mutational clonality in predicting the response to immune checkpoint inhibitors in advanced urothelial cancer

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment and can result in complete remissions even at advanced stages of the disease. However, only a small fraction of patients respond to the treatment. To better understand which factors drive clinical benefit, we have generated whole exome and RNA sequencing data from 27 advanced urothelial carcinoma patients treated with anti-PD-(L)1 monoclonal antibodies. We assessed the influence on the response of non-synonymous mutations (tumor mutational burden or TMB), clonal and subclonal mutations, neoantigen load and various gene expression markers. We found that although TMB is significantly associated with response, this effect can be mostly explained by clonal mutations, present in all cancer cells. This trend was validated in an additional cohort. Additionally, we found that responders with few clonal mutations had abnormally high levels of T and B cell immune markers, suggesting that a high immune cell infiltration signature could be a better predictive biomarker for this subset of patients. Our results support the idea that highly clonal cancers are more likely to respond to ICI and suggest that non-additive effects of different signatures should be considered for predictive models.

BMX-A and BMX-S: Accessible cell-free methods to estimate peptide-MHC-I affinity and stability

The affinity and stability of peptide binding to Major Histocompatibility Complex Class I (MHC-I) molecules are fundamental parameters that underpin the specificity and magnitude of CD8+ T cell responses. These parameters can be estimated in some cases by computational tools, but experimental validation remains valuable, especially for stability. Methods to measure peptide binding can be broadly categorised into either cell-based assays using TAP-deficient cell lines such as RMA/S, or cell-free strategies, such as peptide competition-binding assays and surface plasmon resonance. Cell-based assays are subject to confounding biological activity, including peptide trimming by peptidases and dilution of peptide-loaded MHC-I on the surface of cells through cell division. Current cell-free methods require in-house production and purification of MHC-I. In this study, we present the development of new cell-free assays to estimate the relative affinity and dissociation kinetics of peptide binding to MHC-I. These assays, which we have called BMX-A (relative affinity) and BMX-S (kinetic stability), are reliable, scalable and accessible, in that they use off-the-shelf commercial reagents and standard flow cytometry techniques.

Generation of novel complete HLA class I monoallelic cell lines used in an MHC stabilization assay for neoantigen evaluation

Immunogenic neoantigens derived from somatic mutations in cancer have been identified through clinical studies with the cloning of tumor-infiltrating T cells, and cancer driver gene mutation-derived epitopes have been reported; however, these are rare. At present, the validation of epitopes predicted in silico is difficult as human T-cell clonal diversity cannot be reproduced in vitro or in experimental animal models. To confirm the epitope peptides presented by human leukocyte antigen (HLA) class I molecules predicted in silico, biochemical methods such as major histocompatibility complex (MHC) stabilization assays and mass spectrometry-mediated identification have been developed based on HLA-A*02:01 monoallelic T2 cells and HLA-C*01:02 monoallelic LCL721.221 cells. Therefore, in the present study, to prevent confusion due to peptide cross-presentation among HLA molecules, HLA class I monoallelic B-cell clones were generated from the TISI cell line by knocking out HLA-ABC and TAP2, and knocking in HLA alleles. To explore cancer driver mutations as potential targets for immunotherapy, exome sequencing data from 5,143 patients with cancer enrolled in a comprehensive genome analysis project at the Shizuoka Cancer Center were used to identify somatic amino acid substituted mutations and the 50 most frequent mutations in five genes, TP53, EGFR, PIK3CA, KRAS and BRAF, were identified. Using NetMHC4.1, the present study predicted whether epitopes derived from these mutations are presented on major HLA-ABC alleles in Japanese individuals and synthesized 138 peptides for MHC stabilization assays. The authors also attempted to examine the candidate epitopes at physiological temperatures by using antibody clone G46-2.6, which can detect HLA-ABC, independent of β2-microglobulin association. In the assays, although the peptide-induced HLA expression levels were associated with the predicted affinities, the respective HLA alleles exhibited varying degrees of responsiveness, and unexpectedly, p53-mutant epitopes with predicted weak affinities exhibited strong responses. These results suggested that MHC stabilization assays using completely monoallelic HLA-expressing B-cell lines are useful for evaluating the presentation of neoantigen epitopes.

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.

Usefulness of Docking and Molecular Dynamics in Selecting Tumor Neoantigens to Design Personalized Cancer Vaccines: A Proof of Concept

Personalized cancer vaccines based on neoantigens are a new and promising treatment for cancer; however, there are still multiple unresolved challenges to using this type of immunotherapy. Among these, the effective identification of immunogenic neoantigens stands out, since the in silico tools used generate a significant portion of false positives. Inclusion of molecular simulation techniques can refine the results these tools produce. In this work, we explored docking and molecular dynamics to study the association between the stability of peptide-HLA complexes and their immunogenicity, using as a proof of concept two HLA-A2-restricted neoantigens that were already evaluated in vitro. The results obtained were in accordance with the in vitro immunogenicity, since the immunogenic neoantigen ASTN1 remained bound at both ends to the HLA-A2 molecule. Additionally, molecular dynamic simulation suggests that position 1 of the peptide has a more relevant role in stabilizing the N-terminus than previously proposed. Likewise, the mutations may have a "delocalized" effect on the peptide-HLA interaction, which means that the mutated amino acid influences the intensity of the interactions of distant amino acids of the peptide with the HLA. These findings allow us to propose the inclusion of molecular simulation techniques to improve the identification of neoantigens for cancer vaccines.

Molecular basis of differential HLA class I-restricted T cell recognition of a highly networked HIV peptide

Cytotoxic-T-lymphocyte (CTL) mediated control of HIV-1 is enhanced by targeting highly networked epitopes in complex with human-leukocyte-antigen-class-I (HLA-I). However, the extent to which the presenting HLA allele contributes to this process is unknown. Here we examine the CTL response to QW9, a highly networked epitope presented by the disease-protective HLA-B57 and disease-neutral HLA-B53. Despite robust targeting of QW9 in persons expressing either allele, T cell receptor (TCR) cross-recognition of the naturally occurring variant QW9_S3T is consistently reduced when presented by HLA-B53 but not by HLA-B57. Crystal structures show substantial conformational changes from QW9-HLA to QW9_S3T-HLA by both alleles. The TCR-QW9-B53 ternary complex structure manifests how the QW9-B53 can elicit effective CTLs and suggests sterically hindered cross-recognition by QW9_S3T-B53. We observe populations of cross-reactive TCRs for B57, but not B53 and also find greater peptide-HLA stability for B57 in comparison to B53. These data demonstrate differential impacts of HLAs on TCR cross-recognition and antigen presentation of a naturally arising variant, with important implications for vaccine design.

Impact of peptide:HLA complex stability for the identification of SARS-CoV-2-specific CD8+T cells

Induction of a lasting protective immune response is dependent on presentation of epitopes to patrolling T cells through the HLA complex. While peptide:HLA (pHLA) complex affinity alone is widely exploited for epitope selection, we demonstrate that including the pHLA complex stability as a selection parameter can significantly reduce the high false discovery rate observed with predicted affinity. In this study, pHLA complex stability was measured on three common class I alleles and 1286 overlapping 9-mer peptides derived from the SARS-CoV-2 Spike protein. Peptides were pooled based on measured stability and predicted affinity. Strikingly, stability of the pHLA complex was shown to strongly select for immunogenic epitopes able to activate functional CD8⁺T cells. This result was observed across the three studied alleles and in both vaccinated and convalescent COVID-19 donors. Deconvolution of peptide pools showed that specific CD8⁺T cells recognized one or two dominant epitopes. Moreover, SARS-CoV-2 specific CD8⁺T cells were detected by tetramer-staining across multiple donors. In conclusion, we show that stability analysis of pHLA is a key factor for identifying immunogenic epitopes.

Phase 1 study to determine the safety and dosing of autologous PBMCs modified to present HPV16 antigens (SQZ-PBMC-HPV) in HLA-A*02+ patients with HPV16+ solid tumors

We conducted a dose escalation Phase 1 study of autologous PBMCs loaded by microfluidic squeezing (Cell Squeeze® technology) with HPV16 E6 and E7 antigens (SQZ-PBMC-HPV), in HLA-A*02+ patients with advanced/metastatic HPV16+ cancers. Preclinical studies in murine models had shown such cells resulted in stimulation and proliferation of antigen specific CD8+ cells, and demonstrated antitumor activity. Administration of SQZ-PBMC-HPV was every 3 weeks. Enrollment followed a modified 3+3 design with primary objectives to define safety, tolerability, and the recommended Phase 2 dose. Secondary and exploratory objectives were antitumor activity, manufacturing feasibility, and pharmacodynamic evaluation of immune responses. Eighteen patients were enrolled at doses ranging from 0.5 × 106 to 5.0 × 106 live cells/kg. Manufacture proved feasible and required < 24 h within the overall vein-to-vein time of 1 - 2 weeks; at the highest dose, a median of 4 doses were administered. No DLTs were observed. Most related TEAEs were Grade 1 - 2, and one Grade 2 cytokine release syndrome SAE was reported. Tumor biopsies in three patients showed 2 to 8-fold increases in CD8+ tissue infiltrating lymphocytes, including a case that exhibited increased MHC-I+ and PD-L1+ cell densities and reduced numbers of HPV+ cells. Clinical benefit was documented for the latter case. SQZ-PBMC-HPV was well tolerated; 5.0 × 106 live cells/kg with double priming was chosen as the recommended Phase 2 dose. Multiple participants exhibited pharmacodynamic changes consistent with immune responses supporting the proposed mechanism of action for SQZ-PBMC-HPV, including patients previously refractory to checkpoint inhibitors.

An ultra-high-throughput screen for the evaluation of peptide HLA-Binder interactions

Peptide human leukocyte antigen (pHLA) targeting therapeutics like T-cell receptor based adoptive cell therapy or bispecific T cell engaging receptor molecules hold great promise for the treatment of cancer. Comprehensive pre-clinical screening of therapeutic candidates is important to ensure patient safety but is challenging because of the size of the potential off-target space. By combining stabilized peptide-receptive HLA molecules with microarray printing and screening, we have developed an ultra-high-throughput screening platform named ValidaTe that enables large scale evaluation of pHLA-binder interactions. We demonstrate its potential by measuring and analyzing over 30.000 binding curves for a high-affinity T cell Engaging Receptor towards a large pHLA library. Compared to a dataset obtained by conventional bio-layer interferometry measurements, we illustrate that a massively increased throughput (over 650 fold) is obtained by our microarray screening, paving the way for use in pre-clinical safety screening of pHLA-targeting drugs.

Universal open MHC-I molecules for rapid peptide loading and enhanced complex stability across HLA allotypes

The polymorphic nature and intrinsic instability of class I major histocompatibility complex (MHC-I) and MHC-like molecules loaded with suboptimal peptides, metabolites, or glycolipids presents a fundamental challenge for identifying disease-relevant antigens and antigen-specific T cell receptors (TCRs), hindering the development of autologous therapeutics. Here, we leverage the positive allosteric coupling between the peptide and light chain (β 2 microglobulin, β 2 m) subunits for binding to the MHC-I heavy chain (HC) through an engineered disulfide bond bridging conserved epitopes across the HC/β 2 m interface, to generate conformationally stable, open MHC-I molecules. Biophysical characterization shows that open MHC-I molecules are properly folded protein complexes of enhanced thermal stability compared to the wild type, when loaded with low- to intermediate-affinity peptides. Using solution NMR, we characterize the effects of the disulfide bond on the conformation and dynamics of the MHC-I structure, ranging from local changes in β 2 m interacting sites of the peptide binding groove to long-range effects on the α 2-1 helix and α 3 domain. The interchain disulfide bond stabilizes empty MHC-I molecules in a peptide-receptive, open conformation to promote peptide exchange across multiple human leucocyte antigen (HLA) allotypes, covering representatives from five HLA-A, six HLA-B supertypes, and oligomorphic HLA-Ib molecules. Our structural design, combined with conditional β-peptide ligands, provides a universal platform for generating ready-to-load MHC-I systems of enhanced stability, enabling a range of approaches to screen antigenic epitope libraries and probe polyclonal TCR repertoires in the context of highly polymorphic HLA-I allotypes, as well as oligomorphic nonclassical molecules.

Significance Statement

We outline a structure-guided approach for generating conformationally stable, open MHC-I molecules with enhanced ligand exchange kinetics spanning five HLA-A, all HLA-B supertypes, and oligomorphic HLA-Ib allotypes. We present direct evidence of positive allosteric cooperativity between peptide binding and β 2 m association with the heavy chain by solution NMR and HDX-MS spectroscopy. We demonstrate that covalently linked β 2 m serves as a conformational chaperone to stabilize empty MHC-I molecules in a peptide-receptive state, by inducing an open conformation and preventing intrinsically unstable heterodimers from irreversible aggregation. Our study provides structural and biophysical insights into the conformational properties of MHC-I ternary complexes, which can be further applied to improve the design of ultra-stable, universal ligand exchange systems in a pan-HLA allelic setting.

Current Trends in Neoantigen-Based Cancer Vaccines

Cancer immunotherapies are treatments that use drugs or cells to activate patients’ own immune systems against cancer cells. Among them, cancer vaccines have recently been rapidly developed. Based on tumor-specific antigens referred to as neoantigens, these vaccines can be in various forms such as messenger (m)RNA and synthetic peptides to activate cytotoxic T cells and act with or without dendritic cells. Growing evidence suggests that neoantigen-based cancer vaccines possess a very promising future, yet the processes of immune recognition and activation to relay identification of a neoantigen through the histocompatibility complex (MHC) and T-cell receptor (TCR) remain unclear. Here, we describe features of neoantigens and the biological process of validating neoantigens, along with a discussion of recent progress in the scientific development and clinical applications of neoantigen-based cancer vaccines.

Advancing our knowledge of antigen processing with computational modelling, structural biology, and immunology

Antigen processing is an immunological mechanism by which intracellular peptides are transported to the cell surface while bound to Major Histocompatibility Complex molecules, where they can be surveyed by circulating CD8+ or CD4+ T-cells, potentially triggering an immunological response. The antigen processing pathway is a complex multistage filter that refines a huge pool of potential peptide ligands derived from protein degradation into a smaller ensemble for surface presentation. Each stage presents unique challenges due to the number of ligands, the polymorphic nature of MHC and other protein constituents of the pathway and the nature of the interactions between them. Predicting the ensemble of displayed peptide antigens, as well as their immunogenicity, is critical for improving T cell vaccines against pathogens and cancer. Our predictive abilities have always been hindered by an incomplete empirical understanding of the antigen processing pathway. In this review, we highlight the role of computational and structural approaches in improving our understanding of antigen processing, including structural biology, computer simulation, and machine learning techniques, with a particular focus on the MHC-I pathway.

NetCleave: An Open-Source Algorithm for Predicting C-Terminal Antigen Processing for MHC-I and MHC-II

T cell epitopes presented on the surface of mammalian cells are subjected to a complex network of antigen processing and presentation. Among them, C-terminal antigen processing constitutes one of the main bottlenecks for the generation of epitopes, as it defines the C-terminal end of the final epitope and delimits the peptidome that will be presented downstream. Previously (Amengual-Rigo and Guallar, Sci Rep 111(11):1-8, 2021), we demonstrated that NetCleave stands out as one of the best algorithms for the prediction of C-terminal processing, which in its turn can be crucial to design peptide-based vaccination strategies. In this chapter, we provide a pipeline to exploit the full capabilities of NetCleave, an open-source and retrainable algorithm for predicting the C-terminal antigen processing for the MHC-I and MHC-II pathways.

B.1.1.7 (Alpha) variant is the most antigenic compared to Wuhan strain, B.1.351, B.1.1.28/triple mutant and B.1.429 variants

The rapid spread of the SARS-CoV-2 virus and its variants has created a catastrophic impact worldwide. Several variants have emerged, including B.1.351 (Beta), B.1.1.28/triple mutant (P.1), B.1.1.7 (Alpha), and B.1.429 (Epsilon). We performed comparative and comprehensive antigenicity mapping of the total S-glycoprotein using the Wuhan strain and the other variants and identified 9-mer, 15-mer, and 20-mer CTL epitopes through in silico analysis. The study found that 9-mer CTL epitope regions in the B.1.1.7 variant had the highest antigenicity and an average of the three epitope types. Cluster analysis of the 9-mer CTL epitopes depicted one significant cluster at the 70% level with two nodes (KGFNCYFPL and EGFNCYFPL). The phage-displayed peptides showed mimic 9-mer CTL epitopes with three clusters. CD spectra analysis showed the same band pattern of S-glycoprotein of Wuhan strain and all variants other than B.1.429. The developed 3D model of the superantigen (SAg)-like regions found an interaction pattern with the human TCR, indicating that the SAg-like component might interact with the TCR beta chain. The present study identified another partial SAg-like region (ANQFNSAIGKI) from the S-glycoprotein. Future research should examine the molecular mechanism of antigen processing for CD8⁺ T cells, especially all the variants’ antigens of S-glycoprotein.

Planar Junctionless Field-Effect Transistor for Detecting Biomolecular Interactions

Label-free field-effect transistor-based immunosensors are promising candidates for proteomics and peptidomics-based diagnostics and therapeutics due to their high multiplexing capability, fast response time, and ability to increase the sensor sensitivity due to the short length of peptides. In this work, planar junctionless field-effect transistor sensors (FETs) were fabricated and characterized for pH sensing. The device with SiO₂ gate oxide has shown voltage sensitivity of 41.8 ± 1.4, 39.9 ± 1.4, 39.0 ± 1.1, and 37.6 ± 1.0 mV/pH for constant drain currents of 5, 10, 20, and 50 nA, respectively, with a drain to source voltage of 0.05 V. The drift analysis shows a stability over time of −18 nA/h (pH 7.75), −3.5 nA/h (pH 6.84), −0.5 nA/h (pH 4.91), 0.5 nA/h (pH 3.43), corresponding to a pH drift of −0.45, −0.09, −0.01, and 0.01 per h. Theoretical modeling and simulation resulted in a mean value of the surface states of 3.8 × 10¹⁵/cm² with a standard deviation of 3.6 × 10¹⁵/cm². We have experimentally verified the number of surface sites due to APTES, peptide, and protein immobilization, which is in line with the theoretical calculations for FETs to be used for detecting peptide-protein interactions for future applications.

Primary and secondary functions of HLA-E are determined by stability and conformation of the peptide-bound complexes

MHC-E regulates NK cells by displaying MHC class Ia signal peptides (VL9) to NKG2A:CD94 receptors. MHC-E can also present sequence-diverse, lower-affinity, pathogen-derived peptides to T cell receptors (TCRs) on CD8+ T cells. To understand these affinity differences, human MHC-E (HLA-E)-VL9 versus pathogen-derived peptide structures are compared. Small-angle X-ray scatter (SAXS) measures biophysical parameters in solution, allowing comparison with crystal structures. For HLA-E-VL9, there is concordance between SAXS and crystal parameters. In contrast, HLA-E-bound pathogen-derived peptides produce larger SAXS dimensions that reduce to their crystallographic dimensions only when excess peptide is supplied. Further crystallographic analysis demonstrates three amino acids, exclusive to MHC-E, that not only position VL9 close to the α2 helix, but also allow non-VL9 peptide binding with re-configuration of a key TCR-interacting α2 region. Thus, non-VL9-bound peptides introduce an alternative peptide-binding motif and surface recognition landscape, providing a likely basis for VL9- and non-VL9-HLA-E immune discrimination.

Cancer vaccines: past, present and future; a review article

Immunotherapy and vaccines have revolutionized disease treatment and prevention. Vaccines against infectious diseases have been in use for several decades. In contrast, only few cancer vaccines have been approved for human use. These include preventative vaccines against infectious agents associated with cancers, and therapeutic vaccines used as immunotherapy agents to treat cancers. Challenges in developing cancer vaccines include heterogeneity within and between cancer types, screening and identification of appropriate tumour-specific antigens, and the choice of vaccine delivery platforms. Recent advances in all of these areas and the lessons learnt from COVID-19 vaccines have significantly boosted interest in cancer vaccines. Further advances in these areas are expected to facilitate development of effective novel cancer vaccines. In this review, we aim to discuss the past, the present, and the future of cancer vaccines.

Combination neoantigen-based dendritic cell vaccination and adoptive T-cell transfer induces antitumor responses against recurrence of hepatocellular carcinoma

A high rate of recurrence after curative therapy is a major challenge for the management of hepatocellular carcinoma (HCC). Currently, no effective adjuvant therapy is available to prevent HCC recurrence. We designed a personalized neoantigen-loaded dendritic cell vaccine and neoantigen-activated T cell therapy, and used it as adjuvant therapy to treat ten HCC patients who had undergone curative resection or radiofrequency ablation in the first stage of a phase II trial (NCT03067493). The primary outcomes were safety and neoantigen-specific immune response. Disease-free survival (DFS) was also evaluated. The immunotherapy was successfully administered to all the patients without unexpected delay and demonstrated a reasonable safety profile with no grade {greater than or equal to}3 treatment-related side effects reported. 70% of patients generated de novo circulating multiclonal neoantigen-specific T-cell responses. Induced neoantigen-specific immunity was maintained over time, and epitope spreading was observed. Patients who generated immune responses to treatment exhibited prolonged DFS compared to nonresponders (p=0.012), with 71.4% experiencing no relapse for two years after curative treatment. High expression of an immune stimulatory signature, enhanced immune-cell infiltration (i.e., CD8+ T cells), and upregulated expression of T-cell inflammatory gene profiles were found in the primary tumors of the responders. In addition, neoantigen depletion (immunoediting) was present in the recurrent tumors compared to the primary tumors (7/9 vs. 1/17, p=0.014), suggesting that immune evasion occurred under the pressure of immunotherapy. Our study indicates that neoantigen-based combination immunotherapy is feasible, safe, and has the potential to reduce HCC recurrence after curative treatment.

Harnessing Fuzzy Rule Based System for Screening Major Histocompatibility Complex Class I Peptide Epitopes from the Whole Proteome: An Implementation on the Proteome of Leishmania donovani

The development of peptide-based vaccines is enhanced by immunoinformatics, which predicts the patterns that B cells and T cells recognize. Although several tools are available for predicting the Major histocompatibility complex (MHC-I) binding peptides, the wide variants of human leucocyte antigen allele make it challenging to choose a peptide that will induce an immune response in a majority of people. In addition, for a peptide to be considered a potential vaccine candidate, factors such as T cell affinity, proteasome cleavage, and similarity to human proteins also play a major role. Identifying peptides that satisfy the earlier cited measures across the entire proteome is, therefore, challenging. Hence, the fuzzy inference system (FIS) is proposed to detect each peptide's potential as a vaccine candidate and assign it either a very high, high, moderate, or low ranking. The FIS includes input features from 6 modules (binding of 27 major alleles, T cell propensity, pro-inflammatory response, proteasome cleavage, transporter associated with antigen processing, and similarity with human peptide) and rules derived from an observation of features on positive samples. On validation of experimentally verified peptides, a balanced accuracy of ∼80% was achieved, with a Mathew's correlation coefficient score of 0.67 and an F-1 score of 0.74. In addition, the method was implemented on complete proteome of Leishmania donovani, which contains ∼4,800,000 peptides. Lastly, a searchable database of the ranked results of the L. donovani proteome was made and is available online (MHC-FIS-LdDB). It is hoped that this method will simplify the identification of potential MHC-I binding candidates from a large proteome.

Systematic Determination of TCR–Antigen and Peptide–MHC Binding Kinetics among Field Variants of a Theileria parva Polymorphic CTL Epitope

Positions 1–3 in the Tp9 CTL epitope are required for binding to BoLA-1*023:01.

Positions 5–8 in the Tp9 epitope are required for TCR recognition in diverse CTLs.

Tp9-specific CTLs from Muguga-immunized animals can cross-react with variants 4 and 7.

CTLs are known to contribute to immunity toward Theileria parva, the causative agent of East Coast fever. The Tp9_67–75 CTL epitope from the Muguga strain of T. parva is polymorphic in other parasite strains. Identifying the amino acids important for MHC class I binding, as well as TCR recognition of epitopes, can allow the strategic selection of Ags to induce cellular immunity toward T. parva. In this study, we characterized the amino acids important for MHC class I binding and TCR recognition in the Tp9_67–75 epitope using alanine scanning and a series of variant peptide sequences to probe these interactions. In a peptide–MHC class I binding assay, we found that the amino acids at positions 1, 2, and 3 were critical for binding to its restricting MHC class I molecule BoLA-1*023:01. With IFN-γ ELISPOT and peptide–MHC class I Tet staining assays on two parasite-specific bovine CTL lines, we showed that amino acids at positions 5–8 in the epitope were required for TCR recognition. Only two of eight naturally occurring polymorphic Tp9 epitopes were recognized by both CTLs. Finally, using a TCR avidity assay, we found that a higher TCR avidity was associated with a stronger functional response toward one of two variants recognized by the CTL. These data add to the growing knowledge on the cross-reactivity of epitope-specific CTLs and specificities that may be required in the selection of Ags in the design of a wide-spectrum vaccine for East Coast fever.

Engineering immunoproteasome-expressing mesenchymal stromal cells: A potent cellular vaccine for lymphoma and melanoma in mice

Dendritic cells (DCs) excel at cross-presenting antigens, but their effectiveness as cancer vaccine is limited. Here, we describe a vaccination approach using mesenchymal stromal cells (MSCs) engineered to express the immunoproteasome complex (MSC-IPr). Such modification instills efficient antigen cross-presentation abilities associated with enhanced major histocompatibility complex class I and CD80 expression, de novo production of interleukin-12, and higher chemokine secretion. This cross-presentation capacity of MSC-IPr is highly dependent on their metabolic activity. Compared with DCs, MSC-IPr hold the ability to cross-present a vastly different epitope repertoire, which translates into potent re-activation of T cell immunity against EL4 and A20 lymphomas and B16 melanoma tumors. Moreover, therapeutic vaccination of mice with pre-established tumors efficiently controls cancer growth, an effect further enhanced when combined with antibodies targeting PD-1, CTLA4, LAG3, or 4-1BB under both autologous and allogeneic settings. Therefore, MSC-IPr constitute a promising subset of non-hematopoietic antigen-presenting cells suitable for designing universal cell-based cancer vaccines.

Position-Scanning Peptide Libraries as Particle Immunogens for Improving CD8+ T-Cell Responses

Short peptides reflecting major histocompatibility complex (MHC) class I (MHC-I) epitopes frequently lack sufficient immunogenicity to induce robust antigen (Ag)-specific CD8+ T cell responses. In the current work, it is demonstrated that position-scanning peptide libraries themselves can serve as improved immunogens, inducing Ag-specific CD8+ T cells with greater frequency and function than the wild-type epitope. The approach involves displaying the entire position-scanning library onto immunogenic nanoliposomes. Each library contains the MHC-I epitope with a single randomized position. When a recently identified MHC-I epitope in the glycoprotein gp70 envelope protein of murine leukemia virus (MuLV) is assessed, only one of the eight positional libraries tested, randomized at amino acid position 5 (Pos5), shows enhanced induction of Ag-specific CD8+ T cells. A second MHC-I epitope from gp70 is assessed in the same manner and shows, in contrast, multiple positional libraries (Pos1, Pos3, Pos5, and Pos8) as well as the library mixture give rise to enhanced CD8+ T cell responses. The library mixture Pos1-3-5-8 induces a more diverse epitope-specific T-cell repertoire with superior antitumor efficacy compared to an established single mutation mimotope (AH1-A5). These data show that positional peptide libraries can serve as immunogens for improving CD8+ T-cell responses against endogenously expressed MHC-I epitopes.

Immunodominance complexity: lessons yet to be learned from dominant T cell responses to SARS-COV-2

Immunodominance is a complex and highly debated topic of T cell biology. The current SARS-CoV-2 pandemic has provided the opportunity to profile adaptive immune responses and determine molecular factors contributing to emerging responses towards immunodominant viral epitopes. Here, we discuss parameters that alter the dynamics of CD8 viral epitope processing, generation and T-cell responses, and how immunodominance counteracts viral immune escape mechanisms that develop in the context of emerging SARS-CoV-2 variants.

Systematic discovery and validation of T cell targets directed against oncogenic KRAS mutations

Oncogenic mutations in KRAS can be recognized by T cells on specific class I human leukocyte antigen (HLA-I) molecules, leading to tumor control. To date, the discovery of T cell targets from KRAS mutations has relied on occasional T cell responses in patient samples or the use of transgenic mice. To overcome these limitations, we have developed a systematic target discovery and validation pipeline. We evaluate the presentation of mutant KRAS peptides on individual HLA-I molecules using targeted mass spectrometry and identify 13 unpublished KRASG12C/D/R/V mutation/HLA-I pairs and nine previously described pairs. We assess immunogenicity, generating T cell responses to nearly all targets. Using cytotoxicity assays, we demonstrate that KRAS-specific T cells and T cell receptors specifically recognize endogenous KRAS mutations. The discovery and validation of T cell targets from KRAS mutations demonstrate the potential for this pipeline to aid the development of immunotherapies for important cancer targets.

SAGE1: a Potential Target Antigen for Lung Cancer T-Cell Immunotherapy

A fundamental understanding of cancer-specific antigens is crucial for successful T-cell immunotherapy. Sarcoma antigen 1 (SAGE1) is a cancer/testis antigen that has not yet been verified for T-cell immunotherapy applications. Here, we examined SAGE1 RNA expression and carried out IHC analyses, revealing that SAGE1 is expressed in 50% of non-small cell lung-cancer samples (n = 40). To verify the immunogenicity of SAGE1, we discovered a novel HLA-A*24:02 (HLA-A24)-restricted SAGE1 epitope (SAGE1_597-606, VFSTAPPAFI) using mass spectrometry and identified SAGE1_597-606-specific T-cell clones and T-cell receptors (TCR) from peripheral bloods of HLA-A24⁺ donors. The highest affinity TCR VF3 (K_D = 4.3 μM) demonstrated the highest antitumor potency. Moreover, VF3-transduced T cells mediated the efficient killing of HLA-A24⁺/SAGE1⁺ tumor cells in vitro and effectively inhibited the growth of lung cancer xenografts in mice. Together, our data suggest that SAGE1 could be a target for T-cell immunotherapies against lung cancer, while its specific TCRs could be candidates for developing reagents to treat SAGE1⁺ tumors.

Negative trade-off between neoantigen repertoire breadth and the specificity of HLA-I molecules shapes antitumor immunity

Human leukocyte antigen class I (HLA-I) genes shape our immune response against pathogens and cancer. Certain HLA-I variants can bind a wider range of peptides than others, a feature that could be favorable against a range of viral diseases. However, the implications of this phenomenon on cancer immune response are unknown. Here we quantified peptide repertoire breadth (or promiscuity) of a representative set of HLA-I alleles and found that patients with cancer who were carrying HLA-I alleles with high peptide-binding promiscuity have significantly worse prognosis after immune checkpoint inhibition. This can be explained by a reduced capacity of the immune system to discriminate tumor neopeptides from self-peptides when patients carry highly promiscuous HLA-I variants, shifting the regulation of tumor-infiltrating T cells from activation to tolerance. In summary, HLA-I peptide-binding specificity shapes neopeptide immunogenicity and the self-immunopeptidome repertoire in an antagonistic manner, and could underlie a negative trade-off between antitumor immunity and genetic susceptibility to viral infections.

Structure-guided T cell vaccine design for SARS-CoV-2 variants and sarbecoviruses

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that escape convalescent and vaccine-induced antibody responses has renewed focus on the development of broadly protective T-cell-based vaccines. Here, we apply structure-based network analysis and assessments of HLA class I peptide stability to define mutationally constrained CD8+ T cell epitopes across the SARS-CoV-2 proteome. Highly networked residues are conserved temporally among circulating variants and sarbecoviruses and disproportionately impair spike pseudotyped lentivirus infectivity when mutated. Evaluation of HLA class I stabilizing activity for 18 globally prevalent alleles identifies CD8+ T cell epitopes within highly networked regions with limited mutational frequencies in circulating SARS-CoV-2 variants and deep-sequenced primary isolates. Moreover, these epitopes elicit demonstrable CD8+ T cell reactivity in convalescent individuals but reduced recognition in recipients of mRNA-based vaccines. These data thereby elucidate key mutationally constrained regions and immunogenic epitopes in the SARS-CoV-2 proteome for a global T-cell-based vaccine against emerging variants and SARS-like coronaviruses.

Neoantigen Controversies

Next-generation sequencing technologies have revolutionized our ability to catalog the landscape of somatic mutations in tumor genomes. These mutations can sometimes create so-called neoantigens, which allow the immune system to detect and eliminate tumor cells. However, efforts that stimulate the immune system to eliminate tumors based on their molecular differences have had less success than has been hoped for, and there are conflicting reports about the role of neoantigens in the success of this approach. Here we review some of the conflicting evidence in the literature and highlight key aspects of the tumor-immune interface that are emerging as major determinants of whether mutation-derived neoantigens will contribute to an immunotherapy response. Accounting for these factors is expected to improve success rates of future immunotherapy approaches.

Can Glycosylation Mask the Detection of MHC Expressing p53 Peptides by T Cell Receptors?

Proteins of the major histocompatibility complex (MHC) class I, or human leukocyte antigen (HLA) in humans interact with endogenous peptides and present them to T cell receptors (TCR), which in turn tune the immune system to recognize and discriminate between self and foreign (non-self) peptides. Of especial importance are peptides derived from tumor-associated antigens. T cells recognizing these peptides are found in cancer patients, but not in cancer-free individuals. What stimulates this recognition, which is vital for the success of checkpoint based therapy? A peptide derived from the protein p53 (residues 161–169 or p161) was reported to show this behavior. T cells recognizing this unmodified peptide could be further stimulated in vitro to create effective cancer killing CTLs (cytotoxic T lymphocytes). We hypothesize that the underlying difference may arise from post-translational glycosylation of p161 in normal individuals, likely masking it against recognition by TCR. Defects in glycosylation in cancer cells may allow the presentation of the native peptide. We investigate the structural consequences of such peptide glycosylation by investigating the associated structural dynamics.

Selective HLA restriction enables the evaluation and interpretation of immunogenic breadth at comparable levels to that observed with broader HLA distribution

Existing approaches to identifying predictive T-cell epitopes have traditionally utilized either 2-digit HLA super-families or more commonly utilizing autologous HLA alleles to facilitate the predictions. However, the use of these criteria may not consider the HLA representation within any target population. Here we propose a modification to concept of utilizing autologous HLA whereby subsets of individuals are selected for their specific HLA allele profiles and the representation they provide within a given population. Using this selective approach to HLA selection and the linkages to specific individuals may enable the design of more targeted experimentalstrategies.

Biochemical and functional characterization of mutant KRAS epitopes validates this oncoprotein for immunological targeting

Activating RAS missense mutations are among the most prevalent genomic alterations observed in human cancers and drive oncogenesis in the three most lethal tumor types. Emerging evidence suggests mutant KRAS (mKRAS) may be targeted immunologically, but mKRAS epitopes remain poorly defined. Here we employ a multi-omics approach to characterize HLA class I-restricted mKRAS epitopes. We provide proteomic evidence of mKRAS epitope processing and presentation by high prevalence HLA class I alleles. Select epitopes are immunogenic enabling mKRAS-specific TCRαβ isolation. TCR transfer to primary CD8⁺ T cells confers cytotoxicity against mKRAS tumor cell lines independent of histologic origin, and the kinetics of lytic activity correlates with mKRAS peptide-HLA class I complex abundance. Adoptive transfer of mKRAS-TCR engineered CD8⁺ T cells leads to tumor eradication in a xenograft model of metastatic lung cancer. This study validates mKRAS peptides as bona fide epitopes facilitating the development of immune therapies targeting this oncoprotein.

KRAS is commonly mutated at codon 12 in several cancer types, offering a unique opportunity for the development of neoantigen-targeted immunotherapy. Here the authors present a pipeline for the prediction, identification and validation of HLA class-I restricted mutant KRAS G12 peptides, leading to the generation of mutant KRAS-specific T cell receptors for adoptive T cell immunotherapy.

Targeting Neoepitopes to Treat Solid Malignancies: Immunosurgery

Successful outcome of immune checkpoint blockade in patients with solid cancers is in part associated with a high tumor mutational burden (TMB) and the recognition of private neoantigens by T-cells. The quality and quantity of target recognition is determined by the repertoire of ‘neoepitope’-specific T-cell receptors (TCRs) in tumor-infiltrating lymphocytes (TIL), or peripheral T-cells. Interferon gamma (IFN-γ), produced by T-cells and other immune cells, is essential for controlling proliferation of transformed cells, induction of apoptosis and enhancing human leukocyte antigen (HLA) expression, thereby increasing immunogenicity of cancer cells. TCR αβ-dependent therapies should account for tumor heterogeneity and availability of the TCR repertoire capable of reacting to neoepitopes and functional HLA pathways. Immunogenic epitopes in the tumor-stroma may also be targeted to achieve tumor-containment by changing the immune-contexture in the tumor microenvironment (TME). Non protein-coding regions of the tumor-cell genome may also contain many aberrantly expressed, non-mutated tumor-associated antigens (TAAs) capable of eliciting productive anti-tumor immune responses. Whole-exome sequencing (WES) and/or RNA sequencing (RNA-Seq) of cancer tissue, combined with several layers of bioinformatic analysis is commonly used to predict possible neoepitopes present in clinical samples. At the ImmunoSurgery Unit of the Champalimaud Centre for the Unknown (CCU), a pipeline combining several tools is used for predicting private mutations from WES and RNA-Seq data followed by the construction of synthetic peptides tailored for immunological response assessment reflecting the patient’s tumor mutations, guided by MHC typing. Subsequent immunoassays allow the detection of differential IFN-γ production patterns associated with (intra-tumoral) spatiotemporal differences in TIL or peripheral T-cells versus TIL. These bioinformatics tools, in addition to histopathological assessment, immunological readouts from functional bioassays and deep T-cell ‘adaptome’ analyses, are expected to advance discovery and development of next-generation personalized precision medicine strategies to improve clinical outcomes in cancer in the context of i) anti-tumor vaccination strategies, ii) gauging mutation-reactive T-cell responses in biological therapies and iii) expansion of tumor-reactive T-cells for the cellular treatment of patients with cancer.

HLA class-I-peptide stability mediates CD8+ T cell immunodominance hierarchies and facilitates HLA-associated immune control of HIV

Defining factors that govern CD8+ T cell immunodominance is critical for the rational design of vaccines for viral pathogens. Here, we assess the contribution of human leukocyte antigen (HLA) class-I-peptide stability for 186 optimal HIV epitopes across 18 HLA alleles using transporter associated with antigen processing (TAP)-deficient mono-allelic HLA-expressing cell lines. We find that immunodominant HIV epitopes increase surface stabilization of HLA class-I molecules in comparison to subdominant epitopes. HLA class-I-peptide stability is also strongly correlated with overall immunodominance hierarchies, particularly for epitopes from high-abundance proteins (e.g., Gag). Moreover, HLA alleles associated with HIV protection are preferentially stabilized by epitopes derived from topologically important viral regions at a greater frequency than neutral and risk alleles. These findings indicate that relative stabilization of HLA class-I is a key factor for CD8+ T cell epitope immunodominance hierarchies, with implications for HIV control and the design of T-cell-based vaccines.

A Novel HAGE/WT1-ImmunoBody® Vaccine Combination Enhances Anti-Tumour Responses When Compared to Either Vaccine Alone

Many cancers, including myeloid leukaemia express the cancer testis antigen (CTA) DDX43 (HAGE) and/or the oncogene Wilms’ tumour (WT1). Here we demonstrate that HAGE/WT1-ImmunoBody^® vaccines derived T-cells can kill ex-vivo human CML cell lines expressing these antigens and significantly delay B16/HHDII⁺/DR1⁺/HAGE⁺/WT1⁺ tumour growth in the HHDII/DR1 mice and prolonged mouse survival in the prophylactic setting in comparison to non-immunised control mice. We show that immunisation of HHDII/DR1 mice with HAGE- and WT1-ImmunoBody^® DNA vaccines in a prime-boost regime in two different flanks induce significant IFN-γ release by splenocytes from treated mice, and a significant level of cytotoxicity against tumour targets expressing HAGE/WT1 in vitro. More importantly, the combined HAGE/WT1 ImmunoBody^® vaccine significantly delayed tumour growth in the B16/HHDII⁺/DR1⁺/HAGE⁺/WT1⁺ tumour model and prolonged mouse survival in the prophylactic setting in comparison to non-immunised control mice. Overall, this work demonstrates that combining both HAGE- and WT1-ImmunoBody^® into a single vaccine is better than either vaccine alone. This combination vaccine could be given to patients whose cancer expresses HAGE and WT1 in parallel with existing therapies in order to decrease the chance of disease progression and relapse.

NetCleave: an open-source algorithm for predicting C-terminal antigen processing for MHC-I and MHC-II

Antigens presented on the cell surface have been subjected to multiple biological processes. Among them, C-terminal antigen processing constitutes one of the main bottlenecks of the peptide presentation pathways, as it delimits the peptidome that will be subjected downstream. Here, we present NetCleave, an open-source and retrainable algorithm for the prediction of the C-terminal antigen processing for both MHC-I and MHC-II pathways. NetCleave architecture consists of a neural network trained on 46 different physicochemical descriptors of the cleavage site amino acids. Our results demonstrate that prediction of C-terminal antigen processing achieves high accuracy on MHC-I (AUC of 0.91), while it remains challenging for MHC-II (AUC of 0.66). Moreover, we evaluated the performance of NetCleave and other prediction tools for the evaluation of four independent immunogenicity datasets (H2-Db, H2-Kb, HLA-A*02:01 and HLA-B:07:02). Overall, we demonstrate that NetCleave stands out as one of the best algorithms for the prediction of C-terminal processing, and we provide one of the first evidence that C-terminal processing predictions may help in the discovery of immunogenic peptides.

Challenges targeting cancer neoantigens in 2021: a systematic literature review

Introduction: Cancer neoantigens represent important targets of cancer immunotherapy. The goal of cancer neoantigen vaccines is to induce neoantigen-specific immune responses and antitumor immunity while minimizing the potential for autoimmune toxicity. Advances in sequencing technologies, neoantigen prediction algorithms, and other technologies have dramatically improved the ability to identify and prioritize cancer neoantigens. Unfortunately, results from preclinical studies and early phase clinical trials highlight important challenges to the successful clinical translation of neoantigen cancer vaccines.Areas covered: In this review, we provide an overview of current strategies for the identification and prioritization of cancer neoantigens with a particular emphasis on the two most common strategies used for neoantigen identification: (1) direct identification of peptide ligands eluted from peptide-MHC complexes, and (2) next-generation sequencing combined with neoantigen prediction algorithms. We highlight the limitations of current neoantigen prediction pipelines, and discuss broader challenges associated with cancer neoantigen vaccines including tumor purity/heterogeneity and the immunosuppressive tumor microenvironment.Expert opinion: Despite current limitations, neoantigen prediction is likely to improve rapidly based on advances in sequencing, machine learning, and information sharing. The successful development of robust cancer neoantigen prediction strategies is likely to have a significant impact, with the potential to facilitate cancer neoantigen vaccine design.

Peptide-MHC I complex stability measured by nanoscale differential scanning fluorimetry reveals molecular mechanism of thermal denaturation

Recombinant major histocompatibility complex class I molecules are used in diagnostic and therapeutic approaches in cancer immunotherapy, with many studies exploring their binding to antigenic peptides. Current techniques for kinetic peptide binding studies are hampered by high sample consumption, low throughput, interference with protein stability, and/or high background signal. Here, we validate nanoscale differential scanning fluorimetry (nanoDSF), a method using the tryptophan fluorescence of class I molecules, for class I/peptide binding, and we use it to determine the molecular mechanism of the thermal denaturation of HLA-A*02:01.