Impact of genomic polymorphisms on the repertoire of human MHC class I-associated peptides

How I treat AML relapse after allogeneic HSCT

ABSTRACT

Allogeneic hematopoietic stem cell transplantation (HSCT) is one of the principal curative approaches in the treatment of acute myeloid leukemia (AML); however, relapse after transplantation remains a catastrophic event with poor prognosis. The incidence of relapse has remained unchanged over the last 3 decades despite an evolving understanding of the immunobiology of the graft-versus-leukemia effect and the immune escape mechanisms that lead to post-HSCT relapse. The approach to posttransplant relapse is highly individualized and is dictated both by disease biology and genomics as well as the patient's clinical status at the time of relapse and the interval between relapse and transplantation. With the help of 3 illustrative cases, we discuss our approach to early, late, and incipient relapse. Current therapeutic strategies incorporate immunosuppression taper when feasible, a variety of targeted and nontargeted chemotherapeutic agents, and consolidative cellular therapies including donor lymphocyte infusions or a second allogeneic transplant. We then summarize evolving frontiers in the treatment and prognostication of relapse, including the critical role of measurable residual disease. Finally, we emphasize enrollment on clinical trials and thoughtful discussions regarding goals of care and supporting frail patients as universal principles that should be incorporated in approaches to treatment of AML relapse after transplantation.

Immunogenic cryptic peptides dominate the antigenic landscape of ovarian cancer

Increased infiltration of CD3+ and CD8+ T cells into ovarian cancer (OC) is linked to better prognosis, but the specific antigens involved are unclear. Recent reports suggest that HLA class I can present peptides from noncoding genomic regions, known as noncanonical or cryptic peptides, but their immunogenicity is underexplored. To address this, we used immunopeptidomic analysis and RNA sequencing on five metastatic OC samples, which identified 311 cryptic peptides (40 to 83 per patient). Despite comprising less than 1% of total peptides, cryptic peptides from noncoding transcripts emerged as the predominant antigen class when compared to the other major classes of known tumor-specific and tumor-associated antigens in OC samples. Notably, nearly 70% of the prioritized cryptic peptides elicited T cell activation, as evidenced by increased 4-1BB and IFN-γ expression in autologous CD8+ T cells. This study reveals noncoding cryptic peptides as an important class of immunogenic antigens in OC.

Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines

Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computational framework incorporating a machine learning algorithm-MHCvalidator-to enhance mass spectrometry-based immunopeptidomics sensitivity. MHCvalidator identifies unique T-cell epitopes presented by the B7 supertype, including an epitope from a + 1-frameshift in a truncated Spike antigen, supported by ribosome profiling. Analysis of 100,512 COVID-19 patient proteomes shows Spike antigen truncation in 0.85% of cases, revealing frameshifted viral antigens at the population level. Our EpiTrack pipeline tracks global mutations of MHCvalidator-identified CD8 + T-cell epitopes from the BNT162b4 vaccine. While most vaccine epitopes remain globally conserved, an immunodominant A*01-associated epitope mutates in Delta and Omicron variants. This work highlights SARS-CoV-2 antigenic features and emphasizes the importance of continuous adaptation in T-cell vaccine development.

Neoantigen prioritization based on antigen processing and presentation

Somatic mutations in tumor cells give rise to mutant proteins, fragments of which are often presented by MHC and serve as neoantigens. Neoantigens are tumor-specific and not expressed in healthy tissues, making them attractive targets for T-cell-based cancer immunotherapy. On the other hand, since most somatic mutations differ from patient to patient, neoantigen-targeted immunotherapy is personalized medicine and requires their identification in each patient. Computational algorithms and machine learning methods have been developed to prioritize neoantigen candidates. In fact, since the number of clinically relevant neoantigens present in a patient is generally limited, this process is like finding a needle in a haystack. Nevertheless, MHC presentation of neoantigens is not random but follows certain rules, and the efficiency of neoantigen detection may be further improved with technological innovations. In this review, we discuss current approaches to the detection of clinically relevant neoantigens, with a focus on antigen processing and presentation.

HLAPepBinder: An Ensemble Model for The Prediction Of HLA-Peptide Binding

Background

Human leukocyte antigens (HLAs) play a pivotal role in orchestrating the host's immune response, offering a promising avenue with reduced adverse effects compared to conventional treatments. Cancer immunotherapies use HLA class I molecules for T cells to recognize tumor antigens, emphasizing the importance of identifying peptides that bind effectively to HLAs. Computer modeling of HLA-peptide binding speeds up the search for immunogenic epitopes, which enhances the prospect of personalized medicine and targeted therapies. The Immune Epitope Database (IEDB) is a vital repository, housing curated immune epitope data and prediction tools for HLA-peptide binding. It can be challenging for immunologists to choose the best tool from the IEDB for predicting HLA-peptide binding. This has led to the creation of consensus-based methods that combine the results of several predictors. One of the major challenges in these methods is how to effectively integrate the results from multiple predictors.

Objectives

Previous consensus-based methods integrate at most three tools by relying on simple strategies, such as selecting prediction methods based on their proximity to HLA in training data. In this study, we introduce HLAPepBinder, a novel consensus approach using ensemble machine learning methods to predict HLA-peptide binding, addressing the challenges biologists face in model selection.

Materials and Methods

The key contribution is the development of an automatic pipeline named HLAPepBinder that integrates the predictions of multiple models using a random forest approach. Unlike previous approaches, HLAPepBinder seamlessly integrates results from all nine predictors, providing a comprehensive and accurate predictive framework. By combining the strengths of these models, HLAPepBinder eliminates the need for manual model selection, providing a streamlined and reliable solution for biologists.

Results

HLAPepBinder offers a practical and high-performing alternative for HLA-peptide binding predictions, outperforming both traditional methods and complex deep learning models. Compared to the recently introduced transformer-based model, TranspHLA, which requires substantial computational resources, HLAPepBinder demonstrates superior performance in both prediction accuracy and resource efficiency. Notably, it operates effectively in limited computational environments, making it accessible to researchers with minimal resources. The codes are available online at https://github.com/CBRC-lab/HLAPepBinder.

Conclusion

Our study introduces a novel ensemble-learning model designed to enhance the accuracy and efficiency of HLA-peptide binding predictions. Due to the lack of reliable negative data and the typical assumption of unknown interactions being negative, we focus on analyzing the unknown HLA-peptide bindings in the test set that our model predicts with 100% certainty as positive bindings. Using HLAPepBinder, we identify 26 HLA-peptide pairs with absolute prediction confidence. These predictions are validated through a multi-step pipeline involving literature review, BLAST sequence similarity analysis, and molecular docking studies. This comprehensive validation process highlights HLAPepBinder's ability to make accurate and reliable predictions, contributing significantly to advancements in immunotherapy and vaccine development.

Minor histocompatibility antigens to predict, monitor or manipulate GvL and GvHD after allogeneic hematopoietic cell transplantation

Allogeneic hematopoietic cell transplantation (alloHCT) provides a potential curative treatment for haematological malignancies. The therapeutic Graft-versus-Leukaemia (GvL) effect is induced by donor T cells attacking patient hematopoietic (malignant) cells. However, if healthy non-hematopoietic tissues are targeted, Graft-versus-Disease (GvHD) may develop. After HLA-matched alloHCT, GvL and GvHD are induced by donor T cells recognizing polymorphic peptides presented by HLA on patient cells, so-called minor histocompatibility antigens (MiHAs). The balance between GvL and GvHD depends on the tissue distribution of MiHAs and T-cell frequencies targeting these MiHAs. T cells against broadly expressed MiHAs induce GvL and GvHD, whereas those targeting MiHAs with hematopoietic-restricted expression induce GvL without GvHD. Recently, the MiHA repertoire identified in natural immune responses after alloHCT was expanded to 159 total HLA-I-restricted MiHAs, including 14 hematopoietic-restricted MiHAs. This review explores their potential relevance to predict, monitor, and manipulate GvL and GvHD for improving clinical outcome after HLA-matched alloHCT.

pXg: Comprehensive Identification of Noncanonical MHC-I-Associated Peptides From De Novo Peptide Sequencing Using RNA-Seq Reads

Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as noncanonical major histocompatibility complex-I (MHC-I)-associated peptides (ncMAPs), that bind to MHC-I may make good immunotherapeutic targets. De novo peptide sequencing is a great way to find ncMAPs since it can detect peptide sequences from their tandem mass spectra without using any sequence databases. However, this strategy has not been widely applied for ncMAP identification because there is not a good way to estimate its false-positive rates. In order to completely and accurately identify immunopeptides using de novo peptide sequencing, we describe a unique pipeline called proteomics X genomics. In contrast to current pipelines, it makes use of genomic data, RNA-Seq abundance and sequencing quality, in addition to proteomic features to increase the sensitivity and specificity of peptide identification. We show that the peptide-spectrum match quality and genetic traits have a clear relationship, showing that they can be utilized to evaluate peptide-spectrum matches. From 10 samples, we found 24,449 canonical MHC-I-associated peptides and 956 ncMAPs by using a target-decoy competition. Three hundred eighty-seven ncMAPs and 1611 canonical MHC-I-associated peptides were new identifications that had not yet been published. We discovered 11 ncMAPs produced from a squirrel monkey retrovirus in human cell lines in addition to the two ncMAPs originating from a complementarity determining region 3 in an antibody thanks to the unrestricted search space assumed by de novo sequencing. These entirely new identifications show that proteomics X genomics can make the most of de novo peptide sequencing's advantages and its potential use in the search for new immunotherapeutic targets.

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Recurrent Myocarditis in Patients With Desmosomal Pathogenic Variants: Is Self Antigen Presentation the Link?

Myocarditis is frequently associated with viral infections. Increasing evidence points to an association between myocarditis and inherited cardiomyopathies, though it is unclear whether myocarditis is a driver or an accessory. We present a primary vignette and case series highlighting recurrent myocarditis in patients later found to harbor pathogenic desmosomal variants and provide clinical and basic science context, exploring 2 potentially overlapping hypotheses: that stress induces cellular injury and death in structurally abnormal myocytes and that recurrent viral myocardial and truncated desomosomal protein byproducts as 2 hits could lead to loss of immune tolerance and subsequent autoreactivity.

Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery

The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.

Associations of minor histocompatibility antigens with outcomes following allogeneic hematopoietic cell transplantation

The role of minor histocompatibility antigens (mHAs) in mediating graft versus leukemia and graft versus host disease (GvHD) following allogeneic hematopoietic cell transplantation (alloHCT) is recognized but not well-characterized. By implementing improved methods for mHA prediction in two large patient cohorts, this study aimed to comprehensively explore the role of mHAs in alloHCT by analyzing whether (1) the number of predicted mHAs, or (2) individual mHAs are associated with clinical outcomes. The study population consisted of 2249 donor-recipient pairs treated for acute myeloid leukemia and myelodysplastic syndrome with alloHCT. A Cox proportional hazard model showed that patients with a class I mHA count greater than the population median had an increased hazard of GvHD mortality (hazard ratio [HR] = 1.39, 95% confidence interval [CI] = 1.01, 1.77, p = .046). Competing risk analyses identified the class I mHAs DLRCKYISL (GSTP), WEHGPTSLL (CRISPLD2), and STSPTTNVL (SERPINF2) were associated with increased GVHD mortality (HR = 2.84, 95% CI = 1.52, 5.31, p = .01), decreased leukemia-free survival (LFS) (HR = 1.94, 95% CI = 1.27, 2.95, p = .044), and increased disease-related mortality (DRM) (HR = 2.32, 95% CI = 1.5, 3.6, p = .008), respectively. One class II mHA YQEIAAIPSAGRERQ (TACC2) was associated with increased risk of treatment-related mortality (TRM) (HR = 3.05, 95% CI = 1.75, 5.31, p = .02). WEHGPTSLL and STSPTTNVL were both present within HLA haplotype B*40:01-C*03:04 and showed a positive dose-response relationship with increased all-cause mortality and DRM and decreased LFS, indicating these two mHAs contribute to the risk of mortality in an additive manner. Our study reports the first large-scale investigation of the associations of predicted mHA peptides with clinical outcomes following alloHCT.

Identification and Characterization of Copy Number Variations Regions in West African Taurine Cattle

A total of 106 West African taurine cattle belonging to the Lagunaire breed of Benin (33), the N’Dama population of Burkina Faso (48), and N’Dama cattle sampled in Congo (25) were analyzed for Copy Number Variations (CNVs) using the BovineHDBeadChip of Illumina and two different CNV calling programs: PennCNV and QuantiSNP. Furthermore, 89 West African zebu samples (Bororo cattle of Mali and Zebu Peul sampled in Benin and Burkina Faso) were used as an outgroup to ensure that analyses reflect the taurine cattle genomic background. Analyses identified 307 taurine-specific CNV regions (CNVRs), covering about 56 Mb on all bovine autosomes. Gene annotation enrichment analysis identified a total of 840 candidate genes on 168 taurine-specific CNVRs. Three different statistically significant functional term annotation clusters (from ACt1 to ACt3) involved in the immune function were identified: ACt1 includes genes encoding lipocalins, proteins involved in the modulation of immune response and allergy; ACt2 includes genes encoding coding B-box-type zinc finger proteins and butyrophilins, involved in innate immune processes; and Act3 includes genes encoding lectin receptors, involved in the inflammatory responses to pathogens and B- and T-cell differentiation. The overlap between taurine-specific CNVRs and QTL regions associated with trypanotolerant response and tick-resistance was relatively low, suggesting that the mechanisms underlying such traits may not be determined by CNV alterations. However, four taurine-specific CNVRs overlapped with QTL regions associated with both traits on BTA23, therefore suggesting that CNV alterations in major histocompatibility complex (MHC) genes can partially explain the existence of genetic mechanisms shared between trypanotolerance and tick resistance in cattle. This research contributes to the understanding of the genomic features of West African taurine cattle.

Induced pluripotent stem cells display a distinct set of MHC I-associated peptides shared by human cancers

Previous reports showed that mouse vaccination with pluripotent stem cells (PSCs) induces durable anti-tumor immune responses via T cell recognition of some elusive oncofetal epitopes. We characterize the MHC I-associated peptide (MAP) repertoire of human induced PSCs (iPSCs) using proteogenomics. Our analyses reveal a set of 46 pluripotency-associated MAPs (paMAPs) absent from the transcriptome of normal tissues and adult stem cells but expressed in PSCs and multiple adult cancers. These paMAPs derive from coding and allegedly non-coding (48%) transcripts involved in pluripotency maintenance, and their expression in The Cancer Genome Atlas samples correlates with source gene hypomethylation and genomic aberrations common across cancer types. We find that several of these paMAPs were immunogenic. However, paMAP expression in tumors coincides with activation of pathways instrumental in immune evasion (WNT, TGF-β, and CDK4/6). We propose that currently available inhibitors of these pathways could synergize with immune targeting of paMAPs for the treatment of poorly differentiated cancers.

Deciphering the immunopeptidome in vivo reveals new tumour antigens

Immunosurveillance of cancer requires the presentation of peptide antigens on major histocompatibility complex class I (MHC-I) molecules1-5. Current approaches to profiling of MHC-I-associated peptides, collectively known as the immunopeptidome, are limited to in vitro investigation or bulk tumour lysates, which limits our understanding of cancer-specific patterns of antigen presentation in vivo6. To overcome these limitations, we engineered an inducible affinity tag into the mouse MHC-I gene (H2-K1) and targeted this allele to the KrasLSL-G12D/+Trp53fl/fl mouse model (KP/KbStrep)7. This approach enabled us to precisely isolate MHC-I peptides from autochthonous pancreatic ductal adenocarcinoma and from lung adenocarcinoma (LUAD) in vivo. In addition, we profiled the LUAD immunopeptidome from the alveolar type 2 cell of origin up to late-stage disease. Differential peptide presentation in LUAD was not predictable by mRNA expression or translation efficiency and is probably driven by post-translational mechanisms. Vaccination with peptides presented by LUAD in vivo induced CD8+ T cell responses in naive mice and tumour-bearing mice. Many peptides specific to LUAD, including immunogenic peptides, exhibited minimal expression of the cognate mRNA, which prompts the reconsideration of antigen prediction pipelines that triage peptides according to transcript abundance8. Beyond cancer, the KbStrep allele is compatible with other Cre-driver lines to explore antigen presentation in vivo in the pursuit of understanding basic immunology, infectious disease and autoimmunity.

The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome

INTRODUCTION

The comprehensive collection of peptides presented by Major Histocompatibility Complex (MHC) molecules on the cell surface is collectively known as the immunopeptidome. The analysis and interpretation of such data sets holds great promise for furthering our understanding of basic immunology and adaptive immune activation and regulation, and for direct rational discovery of T cell antigens and the design of T-cell based therapeutics and vaccines. These applications are however challenged by the complex nature of immunopeptidome data.

AREAS COVERED

Here, we describe the benefits and shortcomings of applying liquid chromatography-tandem mass spectrometry (MS) to obtain large scale immunopeptidome data sets and illustrate how the accurate analysis and optimal interpretation of such data is reliant on the availability of refined and highly optimized machine learning approaches.

EXPERT OPINION

Further we demonstrate how the accuracy of immunoinformatics prediction methods within the field of MHC antigen presentation has benefited greatly from the availability of MS-immunopeptidomics data, and exemplify how optimal antigen discovery is best performed in a synergistic combination of MS experiments and such in silico models trained on large scale immunopeptidomics data.

COVID-19 Pandemic: Escape of Pathogenic Variants and MHC Evolution

We propose a new hypothesis that explains the maintenance and evolution of MHC polymorphism. It is based on two phenomena: the constitution of the repertoire of naive T lymphocytes and the evolution of the pathogen and its impact on the immune memory of T lymphocytes. Concerning the latter, pathogen evolution will have a different impact on reinfection depending on the MHC allomorph. If a mutation occurs in a given region, in the case of MHC allotypes, which do not recognize the peptide in this region, the mutation will have no impact on the memory repertoire. In the case where the MHC allomorph binds to the ancestral peptides and not to the mutated peptide, that individual will have a higher chance of being reinfected. This difference in fitness will lead to a variation of the allele frequency in the next generation. Data from the SARS-CoV-2 pandemic already support a significant part of this hypothesis and following up on these data may enable it to be confirmed. This hypothesis could explain why some individuals after vaccination respond less well than others to variants and leads to predict the probability of reinfection after a first infection depending upon the variant and the HLA allomorph.

Mechanistic diversity in MHC class I antigen recognition

Throughout its evolution, the human immune system has developed a plethora of strategies to diversify the antigenic peptide sequences that can be targeted by the CD8+ T cell response against pathogens and aberrations of self. Here we provide a general overview of the mechanisms that lead to the diversity of antigens presented by MHC class I complexes and their recognition by CD8+ T cells, together with a more detailed analysis of recent progress in two important areas that are highly controversial: the prevalence and immunological relevance of unconventional antigen peptides; and cross-recognition of antigenic peptides by the T cell receptors of CD8+ T cells.

Know thy immune self and non-self: Proteomics informs on the expanse of self and non-self, and how and where they arise

T cells play an important role in the adaptive immune response to a variety of infections and cancers. Initiation of a T cell mediated immune response requires antigen recognition in a process termed MHC (major histocompatibility complex) restri ction. A T cell antigen is a composite structure made up of a peptide fragment bound within the antigen-binding groove of an MHC-encoded class I or class II molecule. Insight into the precise composition and biology of self and non-self immunopeptidomes is essential to harness T cell mediated immunity to prevent, treat, or cure infectious diseases and cancers. T cell antigen discovery is an arduous task! The pioneering work in the early 1990s has made large-scale T cell antigen discovery possible. Thus, advancements in mass spectrometry coupled with proteomics and genomics technologies make possible T cell antigen discovery with ease, accuracy, and sensitivity. Yet we have only begun to understand the breadth and the depth of self and non-self immunopeptidomes because the molecular biology of the cell continues to surprise us with new secrets directly related to the source, and the processing and presentation of MHC ligands. Focused on MHC class I molecules, this review, therefore, provides a brief historic account of T cell antigen discovery and, against a backdrop of key advances in molecular cell biologic processes, elaborates on how proteogenomics approaches have revolutionised the field.

A Model of Minor Histocompatibility Antigens in Allogeneic Hematopoietic Cell Transplantation

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

Targeted minor histocompatibility antigen typing to estimate graft-versus-host disease after allogeneic haematopoietic stem cell transplantation

Graft-versus-host disease (GVHD) is a critical complication after allogeneic haematopoietic stem cell transplantation induced by genetic differences in donor-recipient pairs. Rigorous HLA matching has reduced GVHD, but severe GVHD still occurs. Minor histocompatibility antigens (mHAs) are another source of GVHD inducers. We designed a multi-mHA panel with 35 valid mHA loci and retrospectively analyzed 391 donor-recipient pairs with the anticipation of implementing mHA typing into clinical practice to optimize donor selection. Results showed the total mismatching in mHA loci in this panel, as well as mismatching in the GVH direction in unmatched-related recipients (UMRs) were 1.8 times and 1.3 times as those in matched-sibling recipients (MSRs) (p = 4.1e-4, p = 0.012, respectively). There was no significant association between mHA loci mismatching and grades II-IV acute GVHD (aGVHD), III-IV aGVHD, extensive chronic GVHD (cGVHD), or relapse in neither group. UMRs had an increased cumulative incidence of II-IV aGVHD (p = 0.002), but there was no statistical difference of the incidences in severe aGVHD or cGVHD (p = 0.093; p = 0.930). This is a preliminary study to explore GVHD risks brought by mHA loci mismatching in both unmatched-related recipients and matched-full-sibling recipients. Our results confirmed that stringent HLA matching is the key to reduce the risks for GVHD.

Major histocompatibility complex (MHC) class I and class II proteins: impact of polymorphism on antigen presentation

The major histocompatibility complex (MHC) loci are amongst the most polymorphic regions in the genomes of vertebrates. In the human population, thousands of MHC gene variants (alleles) exist that translate into distinct allotypes equipped with overlapping but unique peptide binding profiles. Understanding the differential structural and dynamic properties of MHC alleles and their interaction with critical regulators of peptide exchange bears the potential for more personalized strategies of immune modulation in the context of HLA-associated diseases.

Potential Mimicry of Viral and Pancreatic β Cell Antigens Through Non-Spliced and cis-Spliced Zwitter Epitope Candidates in Type 1 Diabetes

Increasing evidence suggests that post-translational peptide splicing can play a role in the immune response under pathological conditions. This seems to be particularly relevant in Type 1 Diabetes (T1D) since post-translationally spliced epitopes derived from T1D-associated antigens have been identified among those peptides bound to Human Leucocyte Antigen (HLA) class I and II complexes. Their immunogenicity has been confirmed through CD4+ and CD8+ T cell-mediated responses in T1D patients. Spliced peptides theoretically have a large sequence variability. This might increase the frequency of viral-human zwitter peptides, i.e. peptides that share a complete sequence homology irrespective of whether they originate from human or viral antigens, thereby impinging upon the discrimination between self and non-self antigens by T cells. This might increase the risk of autoimmune responses triggered by viral infections. Since enteroviruses and other viral infections have historically been associated with T1D, we investigated whether cis-spliced peptides derived from selected viruses might be able to trigger CD8+ T cell-mediated autoimmunity. We computed in silico viral-human non-spliced and cis-spliced zwitter epitope candidates, and prioritized peptide candidates based on: (i) their binding affinity to HLA class I complexes, (ii) human pancreatic β cell and medullary thymic epithelial cell (mTEC) antigens' mRNA expression, (iii) antigen association with T1D, and (iv) potential hotspot regions in those antigens. Neglecting potential T cell receptor (TCR) degeneracy, no viral-human zwitter non-spliced peptide was found to be an optimal candidate to trigger a virus-induced CD8+ T cell response against human pancreatic β cells. Conversely, we identified some zwitter peptide candidates, which may be produced by proteasome-catalyzed peptide splicing, and might increase the likelihood of pancreatic β cells recognition by virus-specific CD8+ T cell clones, therefore promoting β cell destruction in the context of viral infections.

Isoginkgetin derivative IP2 enhances the adaptive immune response against tumor antigens

The success of cancer immunotherapy relies on the induction of an immunoprotective response targeting tumor antigens (TAs) presented on MHC-I molecules. We demonstrated that the splicing inhibitor isoginkgetin and its water-soluble and non-toxic derivative IP2 act at the production stage of the pioneer translation products (PTPs). We showed that IP2 increases PTP-derived antigen presentation in cancer cells in vitro and impairs tumor growth in vivo. IP2 action is long-lasting and dependent on the CD8+ T cell response against TAs. We observed that the antigen repertoire displayed on MHC-I molecules at the surface of MCA205 fibrosarcoma is modified upon treatment with IP2. In particular, IP2 enhances the presentation of an exon-derived epitope from the tumor suppressor nischarin. The combination of IP2 with a peptide vaccine targeting the nischarin-derived epitope showed a synergistic antitumor effect in vivo. These findings identify the spliceosome as a druggable target for the development of epitope-based immunotherapies.

Immune Reconstitution After Allogeneic Haematopoietic Cell Transplantation: From Observational Studies to Targeted Interventions

Immune reconstitution (IR) after allogeneic haematopoietic cell transplantation (HCT) represents a central determinant of the clinical post-transplant course, since the majority of transplant-related outcome parameters such as graft-vs.-host disease (GvHD), infectious complications, and relapse are related to the velocity, quantity and quality of immune cell recovery. Younger age at transplant has been identified as the most important positive prognostic factor for favourable IR post-transplant and, indeed, accelerated immune cell recovery in children is most likely the pivotal contributing factor to lower incidences of GvHD and infectious complications in paediatric allogeneic HCT. Although our knowledge about the mechanisms of IR has significantly increased over the recent years, strategies to influence IR are just evolving. In this review, we will discuss different patterns of IR during various time points post-transplant and their impact on outcome. Besides IR patterns and cellular phenotypes, recovery of antigen-specific immune cells, for example virus-specific T cells, has recently gained increasing interest, as certain threshold levels of antigen-specific T cells seem to confer protection against severe viral disease courses. In contrast, the association between IR and a possible graft-vs. leukaemia effect is less well-understood. Finally, we will present current concepts of how to improve IR and how this could change transplant procedures in the near future.

Acute Myeloid Leukemia: From Biology to Clinical Practices Through Development and Pre-Clinical Therapeutics

Recent studies have provided several insights into acute myeloid leukemia. Studies based on molecular biology have identified eight functional mutations involved in leukemogenesis, including driver and passenger mutations. Insight into Leukemia stem cells (LSCs) and assessment of cell surface markers have enabled characterization of LSCs from hematopoietic stem and progenitor cells. Clonal evolution has been described as having an effect similar to that of microenvironment alterations. Such biological findings have enabled the development of new targeted drugs, including drug inhibitors and monoclonal antibodies with blockage functions. Some recently approved targeted drugs have resulted in new therapeutic strategies that enhance standard intensive chemotherapy regimens as well as supportive care regimens. Besides the progress made in adoptive immunotherapy, since allogenic hematopoietic stem cell transplantation enabled the development of new T-cell transfer therapies, such as chimeric antigen receptor T-cell and transgenic TCR T-cell engineering, new promising strategies that are investigated.

Self-Peptidome Variation Shapes Individual Immune Responses

The relationship between human genetic variation and disease has not been fully elucidated. According to the present view on infectious diseases pathogen resistance is linked to human leukocyte antigen (HLA) class I/II variants and their individual capacity to present pathogen-derived peptides. Yet, T cell education in the thymus occurs through negative and positive selection, and both processes are controlled by a combination of HLA class I/II variants and peptides from the self. Therefore, the capacity of given HLA class I/II variants to bind pathogen-derived peptides is only one part of the selective process to generate effective immune responses. We thus propose that peptidome variation contributes to shaping T cell receptor (TCR) repertoires and hence individual immune responses, and that this variation represents inherent modulator epitopes.

TCR repertoires emerge in the thymus in each individual as T cells undergo positive and negative selection.

T cell education is controlled by the combination of HLA class I/II molecules and their peptide pools (peptidome).

HLA class I/II molecules are highly plastic in human populations but the peptidome is also a source of variation. Hence combined diversity of HLA class I/II molecules and of self-peptides shapes individual immune responses.

Self-peptide variants that affect T cell repertoires represent inherent modulator epitopes.

The Origin and Immune Recognition of Tumor-Specific Antigens

The dominant paradigm holds that spontaneous and therapeutically induced anti-tumor responses are mediated mainly by CD8 T cells and directed against tumor-specific antigens (TSAs). The presence of specific TSAs on cancer cells can only be proven by mass spectrometry analyses. Bioinformatic predictions and reverse immunology studies cannot provide this type of conclusive evidence. Most TSAs are coded by unmutated non-canonical transcripts that arise from cancer-specific epigenetic and splicing aberrations. When searching for TSAs, it is therefore important to perform mass spectrometry analyses that interrogate not only the canonical reading frame of annotated exome but all reading frames of the entire translatome. The majority of aberrantly expressed TSAs (aeTSAs) derive from unstable short-lived proteins that are good substrates for direct major histocompatibility complex (MHC) I presentation but poor substrates for cross-presentation. This is an important caveat, because cancer cells are poor antigen-presenting cells, and the immune system, therefore, depends on cross-presentation by dendritic cells (DCs) to detect the presence of TSAs. We, therefore, postulate that, in the untreated host, most aeTSAs are undetected by the immune system. We present evidence suggesting that vaccines inducing direct aeTSA presentation by DCs may represent an attractive strategy for cancer treatment.

The Connection Between Minor H Antigens and Neoantigens and the Missing Link in Their Prediction

For hundreds of thousands of years, the human genome has extensively evolved, resulting in genetic variations in almost every gene. Immunological reflections of these genetic variations become clearly visible after an allogeneic stem cell transplantation (allo-SCT) as minor Histocompatibility (H) antigens. Minor H antigens are peptides cleaved from genetically encoded variable protein regions after which they are presented at the cell surface by HLA molecules. After allo-SCT with minor H antigen mismatches between donor and recipient, donor T cells recognize the minor H antigens of the recipient as foreign, evoking strong alloreactive immune responses. Studies in the late eighties have discovered that a subset of minor H antigens are encoded by hematopoietic system-specific genes. After allo-SCT, this subset is strictly expressed on the hematopoietic malignant cells and was therefore the first well-defined highly immunogenic group of tumor-specific antigens. In the last decade, neoantigens derived from genetic mutations in tumors have been identified as another group of immunogenic tumor-specific antigens. Therefore, hematopoietic minor H antigens and neoantigens are therapeutic equivalents. This review will connect our current knowledge about the immune biology and identification of minor H antigens and neoantigens leading to novel conclusions on their prediction.

Widespread and tissue-specific expression of endogenous retroelements in human somatic tissues

BACKGROUND

Endogenous retroelements (EREs) constitute about 42% of the human genome and have been implicated in common human diseases such as autoimmunity and cancer. The dominant paradigm holds that EREs are expressed in embryonic stem cells (ESCs) and germline cells but are repressed in differentiated somatic cells. Despite evidence that some EREs can be expressed at the RNA and protein levels in specific contexts, a system-level evaluation of their expression in human tissues is lacking.

METHODS

Using RNA sequencing data, we analyzed ERE expression in 32 human tissues and cell types, including medullary thymic epithelial cells (mTECs). A tissue specificity index was computed to identify tissue-restricted ERE families. We also analyzed the transcriptome of mTECs in wild-type and autoimmune regulator (AIRE)-deficient mice. Finally, we developed a proteogenomic workflow combining RNA sequencing and mass spectrometry (MS) in order to evaluate whether EREs might be translated and generate MHC I-associated peptides (MAP) in B-lymphoblastoid cell lines (B-LCL) from 16 individuals.

RESULTS

We report that all human tissues express EREs, but the breadth and magnitude of ERE expression are very heterogeneous from one tissue to another. ERE expression was particularly high in two MHC I-deficient tissues (ESCs and testis) and one MHC I-expressing tissue, mTECs. In mutant mice, we report that the exceptional expression of EREs in mTECs was AIRE-independent. MS analyses identified 103 non-redundant ERE-derived MAPs (ereMAPs) in B-LCLs. These ereMAPs preferentially derived from sense translation of intronic EREs. Notably, detailed analyses of their amino acid composition revealed that ERE-derived MAPs presented homology to viral MAPs.

CONCLUSIONS

This study shows that ERE expression in somatic tissues is more pervasive and heterogeneous than anticipated. The high and diversified expression of EREs in mTECs and their ability to generate MAPs suggest that EREs may play an important role in the establishment of self-tolerance. The viral-like properties of ERE-derived MAPs suggest that those not expressed in mTECs can be highly immunogenic.

Optimized Whole Genome Association Scanning for Discovery of HLA Class I-Restricted Minor Histocompatibility Antigens

Patients undergoing allogeneic stem cell transplantation as treatment for hematological diseases face the risk of Graft-versus-Host Disease as well as relapse. Graft-versus-Host Disease and the favorable Graft-versus-Leukemia effect are mediated by donor T cells recognizing polymorphic peptides, which are presented on the cell surface by HLA molecules and result from single nucleotide polymorphism alleles that are disparate between patient and donor. Identification of polymorphic HLA-binding peptides, designated minor histocompatibility antigens, has been a laborious procedure, and the number and scope for broad clinical use of these antigens therefore remain limited. Here, we present an optimized whole genome association approach for discovery of HLA class I minor histocompatibility antigens. T cell clones isolated from patients who responded to donor lymphocyte infusions after HLA-matched allogeneic stem cell transplantation were tested against a panel of 191 EBV-transformed B cells, which have been sequenced by the 1000 Genomes Project and selected for expression of seven common HLA class I alleles (HLA-A^∗01:01, A^∗02:01, A^∗03:01, B^∗07:02, B^∗08:01, C^∗07:01, and C^∗07:02). By including all polymorphisms with minor allele frequencies above 0.01, we demonstrated that the new approach allows direct discovery of minor histocompatibility antigens as exemplified by seven new antigens in eight different HLA class I alleles including one antigen in HLA-A^∗24:02 and HLA-A^∗23:01, for which the method has not been originally designed. Our new whole genome association strategy is expected to rapidly augment the repertoire of HLA class I-restricted minor histocompatibility antigens that will become available for donor selection and clinical use to predict, follow or manipulate Graft-versus-Leukemia effect and Graft-versus-Host Disease after allogeneic stem cell transplantation.

MAPDP: A Cloud-Based Computational Platform for Immunopeptidomics Analyses

The immunopeptidome corresponds to the repertoire of peptides presented at the cell surface by the major histocompatibility complex (MHC) molecules. Cytotoxic T cells scan this repertoire to identify nonself antigens that can arise from tumors or infected cells. The identification of actionable antigenic targets is key to the development of therapeutic cancer vaccines, T-cell therapy, and other T-cell receptor-based biologics. The growing clinical interest for immunopeptidomics has accelerated the development of high throughput proteogenomic platforms that provide a system-level analysis of MHC-associated peptides. Improvement in sensitivity and throughput of mass spectrometers now allows the detection of a few thousands of peptides from less than 100 million cells. To manage the amount of data generated by these instruments, we have developed the MHC-associated peptide discovery platform (MAPDP), a novel open-source cloud-based computational platform for immunopeptidomic analyses. It provides convenient access from a web portal to immunopeptidomes stored in the database, filtering tools, various visualizations, annotations (e.g., IEDB, dbSNP, gnomAD), peptide-binding affinity prediction (mhcflurry, NetMHC), HLA genotyping, and the generation of personalized proteome databases. MAPDP functionalities are demonstrated here by the discovery of MHC peptides featuring new genetic variants identified in two previously published ovarian carcinoma data sets.

Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

T-Cell Immunotherapies Targeting Histocompatibility and Tumor Antigens in Hematological Malignancies

Over the last decades, T-cell immunotherapy has revealed itself as a powerful, and often curative, strategy to treat blood cancers. In hematopoietic cell transplantation, most of the so-called graft-vs.-leukemia (GVL) effect hinges on the recognition of histocompatibility antigens that reflect immunologically relevant genetic variants between donors and recipients. Whether other variants acquired during the neoplastic transformation, or the aberrant expression of gene products can yield antigenic targets of similar relevance as the minor histocompatibility antigens is actively being pursued. Modern genomics and proteomics have enabled the high throughput identification of candidate antigens for immunotherapy in both autologous and allogeneic settings. As such, these major histocompatibility complex-associated tumor-specific (TSA) and tumor-associated antigens (TAA) can allow for the targeting of multiple blood neoplasms, which is a limitation for other immunotherapeutic approaches, such as chimeric antigen receptor (CAR)-modified T cells. We review the current strategies taken to translate these discoveries into T-cell therapies and propose how these could be introduced in clinical practice. Specifically, we discuss the criteria that are used to select the antigens with the greatest therapeutic value and we review the various T-cell manufacturing approaches in place to either expand antigen-specific T cells from the native repertoire or genetically engineer T cells with minor histocompatibility antigen or TSA/TAA-specific recombinant T-cell receptors. Finally, we elaborate on the current and future incorporation of these therapeutic T-cell products into the treatment of hematological malignancies.

Proteogenomics Uncovers a Vast Repertoire of Shared Tumor-Specific Antigens in Ovarian Cancer

High-grade serous ovarian cancer (HGSC), the principal cause of death from gynecologic malignancies in the world, has not significantly benefited from advances in cancer immunotherapy. Although HGSC infiltration by lymphocytes correlates with superior survival, the nature of antigens that can elicit anti-HGSC immune responses is unknown. The goal of this study was to establish the global landscape of HGSC tumor-specific antigens (TSA) using a mass spectrometry pipeline that interrogated all reading frames of all genomic regions. In 23 HGSC tumors, we identified 103 TSAs. Classic TSA discovery approaches focusing only on mutated exonic sequences would have uncovered only three of these TSAs. Other mutated TSAs resulted from out-of-frame exonic translation (n = 2) or from noncoding sequences (n = 7). One group of TSAs (n = 91) derived from aberrantly expressed unmutated genomic sequences, which were not expressed in normal tissues. These aberrantly expressed TSAs (aeTSA) originated primarily from nonexonic sequences, in particular intronic (29%) and intergenic (22%) sequences. Their expression was regulated at the transcriptional level by variations in gene copy number and DNA methylation. Although mutated TSAs were unique to individual tumors, aeTSAs were shared by a large proportion of HGSCs. Taking into account the frequency of aeTSA expression and HLA allele frequencies, we calculated that, in Caucasians, the median number of aeTSAs per tumor would be five. We conclude that, in view of their number and the fact that they are shared by many tumors, aeTSAs may be the most attractive targets for HGSC immunotherapy.

Identification of Plasmodium falciparum proteoforms from liver stage models

BACKGROUND

Immunization with attenuated malaria sporozoites protects humans from experimental malaria challenge by mosquito bite. Protection in humans is strongly correlated with the production of T cells targeting a heterogeneous population of pre-erythrocyte antigen proteoforms, including liver stage antigens. Currently, few T cell epitopes derived from Plasmodium falciparum, the major aetiologic agent of malaria in humans are known.

METHODS

In this study both in vitro and in vivo malaria liver stage models were used to sequence host and pathogen proteoforms. Proteoforms from these diverse models were subjected to mild acid elution (of soluble forms), multi-dimensional fractionation, tandem mass spectrometry, and top-down bioinformatics analysis to identify proteoforms in their intact state.

RESULTS

These results identify a group of host and malaria liver stage proteoforms that meet a 5% false discovery rate threshold.

CONCLUSIONS

This work provides proof-of-concept for the validity of this mass spectrometry/bioinformatic approach for future studies seeking to reveal malaria liver stage antigens towards vaccine development.

A Peptide Link Between Human Cytomegalovirus Infection, Neuronal Migration, and Psychosis

Alongside biological, psychological, and social risk factors, psychotic syndromes may be related to disturbances of neuronal migration. This highly complex process characterizes the developing brain of the fetus, the early postnatal brain, and the adult brain, as reflected by changes within the subventricular zone and the dentate gyrus of the hippocampus, where neurogenesis persists throughout life. Psychosis also appears to be linked to human cytomegalovirus (HCMV) infection. However, little is known about the connection between psychosis, HCMV infection, and disruption of neuronal migration. The present study addresses the hypothesis that HCMV infection may lead to mental disorders through mechanisms of autoimmune cross-reactivity. Searching for common peptides that underlie immune cross-reactions, the analyses focus on HCMV and human proteins involved in neuronal migration. Results demonstrate a large overlap of viral peptides with human proteins associated with neuronal migration, such as ventral anterior homeobox 1 and cell adhesion molecule 1 implicated in GABAergic and glutamatergic neurotransmission. The present findings support the possibility of immune cross-reactivity between HCMV and human proteins that-when altered, mutated, or improperly functioning-may disrupt normal neuronal migration. In addition, these findings are consistent with a molecular and mechanistic framework for pathological sequences of events, beginning with HCMV infection, followed by immune activation, cross-reactivity, and neuronal protein variations that may ultimately contribute to the emergence of mental disorders, including psychosis.

The Genomic Landscape of Antigenic Targets for T Cell-Based Leukemia Immunotherapy

Intensive fundamental and clinical research in cancer immunotherapy has led to the emergence and evolution of two parallel universes with surprisingly little interactions: the realm of hematologic malignancies and that of solid tumors. Treatment of hematologic cancers using allogeneic hematopoietic cell transplantation (AHCT) serendipitously led to the discovery that T cells specific for minor histocompatibility antigens (MiHAs) could cure hematopoietic cancers. Besides, studies based on treatment of solid tumor with ex vivo-expanded tumor infiltrating lymphocytes or immune checkpoint therapy demonstrated that anti-tumor responses could be achieved by targeting tumor-specific antigens (TSAs). It is our contention that much insight can be gained by sharing the tremendous amount of data generated in the two-abovementioned universes. Our perspective article has two specific goals. First, to discuss the value of methods currently used for MiHA and TSA discovery and to explain the key role of mass spectrometry analyses in this process. Second, to demonstrate the importance of broadening the scope of TSA discovery efforts beyond classic annotated protein-coding genomic sequences.

An engineered antibody fragment targeting mutant β-catenin via major histocompatibility complex I neoantigen presentation

Mutations in CTNNB1, the gene encoding β-catenin, are common in colon and liver cancers, the most frequent mutation affecting Ser-45 in β-catenin. Peptides derived from WT β-catenin have previously been shown to be presented on the cell surface as part of major histocompatibility complex (MHC) class I, suggesting an opportunity for targeting this common driver gene mutation with antibody-based therapies. Here, crystal structures of both the WT and S45F mutant peptide bound to HLA-A*03:01 at 2.20 and 2.45 Å resolutions, respectively, confirmed the accessibility of the phenylalanine residue for antibody recognition. Phage display was then used to identify single-chain variable fragment clones that selectively bind the S45F mutant peptide presented in HLA-A*03:01 and have minimal WT or other off-target binding. Following the initial characterization of five clones, we selected a single clone, E10, for further investigation. We developed a computational model of the binding of E10 to the mutant peptide-bound HLA-A3, incorporating data from affinity maturation as initial validation. In the future, our model may be used to design clones with maintained specificity and higher affinity. Such derivatives could be adapted into either cell-based (CAR-T) or protein-based (bispecific T-cell engagers) therapies to target cancer cells harboring the S45F mutation in CTNNB1.

The Graft-Versus-Leukemia Effect in AML

Allogeneic hematopoietic stem cell transplantation (allo-SCT) is the most established and commonly used cellular immunotherapy in cancer care. It is the most potent anti-leukemic therapy in patients with acute myeloid leukemia (AML) and is routinely used with curative intent in patients with intermediate and poor risk disease. Donor T cells, and possibly other immune cells, eliminate residual leukemia cells after prior (radio)chemotherapy. This immune-mediated response is known as graft-versus-leukemia (GvL). Donor alloimmune responses can also be directed against healthy tissues, which is known as graft-versus-host disease (GvHD). GvHD and GvL often co-occur and, therefore, a major barrier to exploiting the full immunotherapeutic benefit of donor immune cells against patient leukemia is the immunosuppression required to treat GvHD. However, curative responses to allo-SCT and GvHD do not always occur together, suggesting that these two immune responses could be de-coupled in some patients. To make further progress in successfully promoting GvL without GvHD, we must transform our limited understanding of the cellular and molecular basis of GvL and GvHD. Specifically, in most patients we do not understand the antigenic basis of immune responses in GvL and GvHD. Identification of antigens important for GvL but not GvHD, and vice versa, could impact on donor selection, allow us to track GvL immune responses and begin to specifically harness and strengthen anti-leukemic immune responses against patient AML cells, whilst minimizing the toxicity of GvHD.

Application of mass spectrometry-based MHC immunopeptidome profiling in neoantigen identification for tumor immunotherapy

One of the challenges for cancer vaccine and adoptive T-cell-based immunotherapy is to identify the major histocompatibility complex (MHC)-associated non-self neoantigens recognized by T cells. T cell epitope in silico prediction algorithms have been widely used for neoantigen prediction; nonetheless, this platform lacks the experimental evidence of directly identification of the presented epitopes on cell surface. Currently, mass spectrometry (MS)-based proteomics is an advanced analytical technology for large-scale peptide sequencing, which has become a powerful tool for directly profiling the immunopeptidome presented by MHC molecules. Integrating with next-generation sequencing, proteogenomic analysis provides the "gold standard" for neoantigen identification at protein level. This method discovers the tumor-specific neoantigens derived from somatic mutations, proteasome splicing, noncoding RNA, and post-translational modified antigens. Herein, we review basis of antigen processing and presentation, tumor antigen classification, existing approaches for neoantigen discovery, quantitative proteomics, epitope prediction programs, and advantages and drawbacks of proteomics workflow for MHC immunopeptidome profiling. Furthermore, we summarize 40 recently published reports addressing the fundamental theory, breakthrough and most advanced updates for the mass spectrometry-based neoantigen discovery for cancer immunotherapy.

Computational Analysis of HLA-presentation of Non-synonymous Recipient Mismatches Indicates Effect on the Risk of Chronic Graft-vs.-Host Disease After Allogeneic HSCT

Genetic mismatches in protein coding genes between allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipient and donor can elicit an alloimmunity response via peptides presented by the recipient HLA receptors as minor histocompatibility antigens (mHAs). While the impact of individual mHAs on allo-HSCT outcome such as graft-vs.-host and graft-vs.-leukemia effects has been demonstrated, it is likely that established mHAs constitute only a small fraction of all immunogenic non-synonymous variants. In the present study, we have analyzed the genetic mismatching in 157 exome-sequenced sibling allo-HSCT pairs to evaluate the significance of polymorphic HLA class I associated peptides on clinical outcome. We applied computational mismatch estimation approaches based on experimentally verified HLA ligands available in public repositories, published mHAs, and predicted HLA-peptide affinites, and analyzed their associations with chronic graft-vs.-host disease (cGvHD) grades. We found that higher estimated recipient mismatching consistently increased the risk of severe cGvHD, suggesting that HLA-presented mismatching influences the likelihood of long-term complications in the patient. Furthermore, computational approaches focusing on estimation of HLA-presentation instead of all non-synonymous mismatches indiscriminately may be beneficial for analysis sensitivity and could help identify novel mHAs.

Computational modeling and confirmation of leukemia-associated minor histocompatibility antigens

T-cell responses to minor histocompatibility antigens (mHAs) mediate both antitumor immunity (graft-versus-leukemia [GVL]) and graft-versus-host disease (GVHD) in allogeneic stem cell transplant. Identifying mHAs with high allele frequency, tight binding affinity to common HLA molecules, and narrow tissue restriction could enhance immunotherapy against leukemia. Genotyping and HLA allele data from 101 HLA-matched donor-recipient pairs (DRPs) were computationally analyzed to predict both class I and class II mHAs likely to induce either GVL or GVHD. Roughly twice as many mHAs were predicted in HLA-matched unrelated donor (MUD) stem cell transplantation (SCT) compared with HLA-matched related transplants, an expected result given greater genetic disparity in MUD SCT. Computational analysis predicted 14 of 18 previously identified mHAs, with 2 minor antigen mismatches not being contained in the patient cohort, 1 missed mHA resulting from a noncanonical translation of the peptide antigen, and 1 case of poor binding prediction. A predicted peptide epitope derived from GRK4, a protein expressed in acute myeloid leukemia and testis, was confirmed by targeted differential ion mobility spectrometry-tandem mass spectrometry. T cells specific to UNC-GRK4-V were identified by tetramer analysis both in DRPs where a minor antigen mismatch was predicted and in DRPs where the donor contained the allele encoding UNC-GRK4-V, suggesting that this antigen could be both an mHA and a cancer-testis antigen. Computational analysis of genomic and transcriptomic data can reliably predict leukemia-associated mHA and can be used to guide targeted mHA discovery.

Contribution of non-HLA incompatibility between donor and recipient to kidney allograft survival: genome-wide analysis in a prospective cohort

BACKGROUND

The introduction of HLA matching of donors and recipients was a breakthrough in kidney transplantation. However, half of all transplanted kidneys still fail within 15 years after transplantation. Epidemiological data suggest a fundamental role of non-HLA alloimmunity.

METHODS

We genotyped 477 pairs of deceased donors and first kidney transplant recipients with stable graft function at three months that were transplanted between Dec 1, 2005, and April 30, 2015. Genome-wide genetic mismatches in non-synonymous single nucleotide polymorphisms (nsSNPs) were calculated to identify incompatibilities in transmembrane and secreted proteins. We estimated the association between nsSNP mismatch and graft loss in a Cox proportional hazard model, adjusting for HLA mismatch and clinical covariates. Customised peptide arrays were generated to screen for antibodies against genotype-derived mismatched epitopes in 25 patients with biopsy-confirmed chronic antibody-mediated rejection.

FINDINGS

59 268 nsSNPs affecting a transmembrane or secreted protein were analysed. The median number of nsSNP mismatches in immune-accessible transmembrane and secreted proteins between donors and recipients was 1892 (IQR 1850-1936). The degree of nsSNP mismatch was independently associated with graft loss in a multivariable model adjusted for HLA eplet mismatch (HLA-A, HLA-B, HLA-C, HLA-DP, HLA-DQ, and HLA-DR). Each increase by a unit of one IQR had an HR of 1·68 (95% CI 1·17-2·41, p=0·005). 5-year death censored graft survival was 98% in the quartile with the lowest mismatch, 91% in the second quartile, 89% in the third quartile, and 82% in the highest quartile (p=0·003, log-rank test). Customised peptide arrays verified a donor-specific alloimmune response to genetically predicted mismatched epitopes.

INTERPRETATION

Genetic mismatch of non-HLA haplotypes coding for transmembrane or secreted proteins is associated with an increased risk of functional graft loss independently of HLA incompatibility. As in HLA alloimmunity, donor-specific alloantibodies can be identified against genotype derived non-HLA epitopes.

FUNDING

Austrian Science Fund, WWTF (Vienna Science and Technology Fund), and Ministry of Health of the Czech Republic.

Cellular immunotherapy for acute myeloid leukemia: How specific should it be?

Significant improvements in the survival of patients with hematological cancers following hematopoietic stem cell transplantation provide evidence supporting the potency of immune cell-mediated anti-leukemic effects. Studies focusing on immune cell-based cancer therapies have made significant breakthroughs in the last few years. Adoptive cellular therapy (ACT), and chimeric antigen receptor (CAR) T cell therapy, in particular, has significantly increased the survival of patients with B cell acute lymphoblastic leukemia and aggressive B cell lymphoma. Despite antigen-negative relapses and severe toxicities such as cytokine release syndrome after treatment, CAR-T cell therapies have been approved by the FDA in some conditions. Although a number of studies have tried to achieve similar results for acute myeloid leukemia (AML), clinical outcomes have not been as promising. In this review, we summarize recent and ongoing studies on cellular therapies for AML patients, with a focus on antigen-specific versus -nonspecific approaches.

Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome

BACKGROUND

To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their reliance upon chemical affinity data, which is less biologically relevant than sampling by mass spectrometry, and other tools are limited by incomplete exploration of machine learning approaches. Herein, we assemble publicly available data describing human peptides discovered by sampling the MHC-I immunopeptidome with mass spectrometry and use this database to train random forest classifiers (ForestMHC) to predict presentation by MHC-I.

RESULTS

As measured by precision in the top 1% of predictions, our method outperforms NetMHC and NetMHCpan on test sets, and it outperforms both these methods and MixMHCpred on new data from an ovarian carcinoma cell line. We also find that random forest scores correlate monotonically, but not linearly, with known chemical binding affinities, and an information-based analysis of classifier features shows the importance of anchor positions for our classification. The random-forest approach also outperforms a deep neural network and a convolutional neural network trained on identical data. Finally, we use our large database to confirm that gene expression partially determines peptide presentation.

CONCLUSIONS

ForestMHC is a promising method to identify peptides bound by MHC-I. We have demonstrated the utility of random forest-based approaches in predicting peptide presentation by MHC-I, assembled the largest known database of MS binding data, and mined this database to show the effect of gene expression on peptide presentation. ForestMHC has potential applicability to basic immunology, rational vaccine design, and neoantigen binding prediction for cancer immunotherapy. This method is publicly available for applications and further validation.

The role of proteomics in the age of immunotherapies

The antigenic landscape of the adaptive immune response is determined by the peptides presented by immune cells. In recent years, a number of immune-based cancer therapies have been shown to induce remarkable clinical responses through the activation of the patient's immune system. As a result, there is a need to identify immune biomarkers capable of predicting clinical response. Recent advances in proteomics have led to considerable developments in the more comprehensive profiling of the immune response. "Immunoproteomics" utilises a rapidly increasing collection of technologies in order to identify and quantify antigenic peptides or proteins. This includes gel-based, array-based, mass spectrometry (MS), DNA-based, or computer-based (in silico) approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers to a depth not before understood. This review gives an overview of the emerging role of proteomics in improving personalisation of immunotherapy treatment.

How ERAP1 and ERAP2 Shape the Peptidomes of Disease-Associated MHC-I Proteins

Four inflammatory diseases are strongly associated with Major Histocompatibility Complex class I (MHC-I) molecules: birdshot chorioretinopathy (HLA-A^*29:02), ankylosing spondylitis (HLA-B^*27), Behçet's disease (HLA-B^*51), and psoriasis (HLA-C^*06:02). The endoplasmic reticulum aminopeptidases (ERAP) 1 and 2 are also risk factors for these diseases. Since both enzymes are involved in the final processing steps of MHC-I ligands it is reasonable to assume that MHC-I-bound peptides play a significant pathogenetic role. This review will mainly focus on recent studies concerning the effects of ERAP1 and ERAP2 polymorphism and expression on shaping the peptidome of disease-associated MHC-I molecules in live cells. These studies will be discussed in the context of the distinct mechanisms and substrate preferences of both enzymes, their different patterns of genetic association with various diseases, the role of polymorphisms determining changes in enzymatic activity or expression levels, and the distinct peptidomes of disease-associated MHC-I allotypes. ERAP1 and ERAP2 polymorphism and expression induce significant changes in multiple MHC-I-bound peptidomes. These changes are MHC allotype-specific and, without excluding a degree of functional inter-dependence between both enzymes, reflect largely separate roles in their processing of MHC-I ligands. The studies reviewed here provide a molecular basis for the distinct patterns of genetic association of ERAP1 and ERAP2 with disease and for the pathogenetic role of peptides. The allotype-dependent alterations induced on distinct peptidomes may explain that the joint association of both enzymes and unrelated MHC-I alleles influence different pathological outcomes.