HLA and proteasome expression body map

IFN-λ Enhances Constitutive Expression of MHC Class I Molecules on Thymic Epithelial Cells

Regulation of MHC class I (MHC I) expression has been studied almost exclusively in hematolymphoid cells. We report that thymic epithelial cells (TECs), particularly the medullary TECs, constitutively express up to 100-fold more cell surface MHC I proteins than epithelial cells (ECs) from the skin, colon, and lung. Differential abundance of cell surface MHC I in primary ECs is regulated via transcription of MHC I and of genes implicated in the generation of MHC I-binding peptides. Superior MHC I expression in TECs is unaffected by deletion of Ifnar1 or Ifngr1, but is lessened by deletion of Aire, Ifnlr1, Stat1, or Nlrc5, and is driven mainly by type III IFN produced by medullary TECs. Ifnlr1 ^-/- mice show impaired negative selection of CD8 thymocytes and, at 9 mo of age, present autoimmune manifestations. Our study shows unanticipated variation in MHC I expression by ECs from various sites and provides compelling evidence that superior expression of MHC I in TECs is crucial for proper thymocyte education.

Role of platelets and megakaryocytes in adaptive immunity

The immune system is comprised of two principal interconnected components called innate and adaptive immunity. While the innate immune system mounts a nonspecific response that provides protection against the spread of foreign pathogens, the adaptive immune system has developed to specifically recognize a given pathogen and lead to immunological memory. Platelets are small fragments produced from megakaryocytes in bone marrow and lungs. They circulate throughout the blood to monitor the integrity of the vasculature and to prevent bleeding. Given their large repertoire of immune receptors and inflammatory molecules, platelets and megakaryocytes can contribute to both innate and adaptive immunity. In adaptive immunity, platelets and megakaryocytes can process and present antigens to lymphocytes. Moreover, platelets, via FcγRIIA, rapidly respond to pathogens in an immune host when antibodies are present. This manuscript reviews the reported contributions of platelets and megakaryocytes with emphasis on antigen presentation and antibody response in adaptive immunity.

MHC Class I Regulation: The Origin Perspective

Viral-derived elements and non-coding RNAs that build up “junk DNA” allow for flexible and context-dependent gene expression. They are extremely dense in the MHC region, accounting for flexible expression of the MHC I, II, and III genes and adjusting the level of immune response to the environmental stimuli. This review brings forward the viral-mediated aspects of the origin and evolution of adaptive immunity and aims to link this perspective with the MHC class I regulation. The complex regulatory network behind MHC expression is largely controlled by virus-derived elements, both as binding sites for immune transcription factors and as sources of regulatory non-coding RNAs. These regulatory RNAs are imbalanced in cancer and associate with different tumor types, making them promising targets for diagnostic and therapeutic interventions.

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.

The unconventional role of HLA-E: The road less traveled

Histocompatibility Leukocyte Antigens, or HLAs, are one of the most polymorphic molecules in humans. This high degree of polymorphism endows HLA molecules with the ability to present a vast array of peptides, an essential trait for responding to ever-evolving pathogens. Unlike classical HLA molecules (HLA-Ia), some non-classical HLA-Ib molecules, including HLA-E, are almost monomorphic. Several studies show HLA-E can present self-peptides originating from the leader sequence of other HLA molecules, which signals to our immune system that the cell is healthy. Therefore, it was traditionally thought that the chief role of HLA-E in the body was in immune surveillance. However, there is emerging evidence that HLA-E is also able to present pathogen-derived peptides to the adaptive immune system, namely T cells, in a manner that is similar to classical HLA-Ia molecules. Here we describe the early findings of this less conventional role of HLA-E in the adaptive immune system and its importance for immunity.

GFAP IgG associated inflammatory polyneuropathy

BACKGROUND

GFAP (glial fibrillary acidic protein)-IgG is predominantly associated with meningoencephalomyelitis, and neuropathy presentations are rare.

METHODS

We reviewed clinical, electrodiagnostic and histopathological presentations of GFAP-IgG associated peripheral neuropathy.

RESULTS

We identified six cases, five of whom had peripheral neuropathy as the initial presentation. Acute/subacute polyradicluoneuropathy or proximal nerve involvement was a common presentation. Three had demyelinating neuropathies on electrophysiological studies. Nerve biopsies (n = 2) demonstrated T-cell predominant perivascular inflammatory collections, and all patients with clinical follow up responded favorably to immunotherapy.

CONCLUSION

GFAP neuropathy represents a potentially treatable immune-mediated neuropathy and can occur with or without co-existing meningoencephalomyelitis.

Insulin resistance in obese adolescents affects the expression of genes associated with immune response

OBJECTIVE

The development of obesity and its metabolic complications is associated with dysregulation of various intrinsic mechanisms, which control basic metabolic processes through changes in the expression of numerous regulatory genes.

METHODS

The expression level of HLA-DRA, HLA-DRB1, HLA-G, HLA-F, and NFX1 genes as well as miR-190b was measured in the blood of obese adolescents without signs of resistance to insulin and with insulin resistance in comparison with the group of relative healthy control individuals without signs of obesity.

RESULTS

It was shown that obesity without signs of insulin resistance is associated with upregulation of the expression level of HLA-DRA and HLA-DRB1 genes, but with down-regulation of HLA-G gene expression in the blood as compared to control group of relative healthy adolescents. At the same time, no significant changes were observed in the expression level of HLA-F and NFX1 genes in the blood of this group of obese adolescents. Development of insulin resistance in obese individuals leads to significant down-regulation of HLA-DRA, HLA-DRB1, HLA-G, and HLA-F gene expressions as well as to up-regulation of NFX1 gene as well as microRNA miR-190b in the blood as compared to obese patients without signs of insulin resistance.

CONCLUSIONS

Results of this study provide evidence that obesity affects the expression of the subset of genes related to immune response in the blood and that development of insulin resistance in obese adolescents is associated with strong down-regulation of the expressions of HLA-DRA, HLA-DRB1, HLA-F, and HLA-G genes, which may be contribute to the development of obesity complications. It is possible that transcription factor NFX1 and miR-190b participate in downregulation of HLA-DRA gene expression in the blood of obese adolescents with insulin resistance.

In vitro education of human natural killer cells by KIR3DL1

Using NK cells isolated from individuals who lack the Bw4 epitope on HLA-B, Pugh et al reveal that KIR3DL1⁺ NK cells can be educated in vitro by co-culturing them with target cells that display the missing epitope.

During development, NK cells are “educated” to respond aggressively to cells with low surface expression of HLA class I, a hallmark of malignant and infected cells. The mechanism of education involves interactions between inhibitory killer immunoglobulin–like receptors (KIRs) and specific HLA epitopes, but the details of this process are unknown. Because of the genetic diversity of HLA class I genes, most people have NK cells that are incompletely educated, representing an untapped source of human immunity. We demonstrate how mature peripheral KIR3DL1⁺ human NK cells can be educated in vitro. To accomplish this, we trained NK cells expressing the inhibitory KIR3DL1 receptor by co-culturing them with target cells that expressed its ligand, Bw4⁺HLA-B. After this training, KIR3DL1⁺ NK cells increased their inflammatory and lytic responses toward target cells lacking Bw4⁺HLA-B, as though they had been educated in vivo. By varying the conditions of this basic protocol, we provide mechanistic and translational insights into the process NK cell education.

Dimorphism of HLA-E and its Disease Association

HLA-E is a nonclassical member of the major histocompatibility complex class I gene locus. HLA-E protein shares a high level of homology with MHC Ia classical proteins: it has similar tertiary structure, associates with β2-microglobulin, and is able to present peptides to cytotoxic lymphocytes. The main function of HLA-E under normal conditions is to present peptides derived from the leader sequences of classical HLA class I proteins, thus serving for monitoring of expression of these molecules performed by cytotoxic lymphocytes. However, opposite to multiallelic classical MHC I genes, HLA-E in fact has only two alleles—HLA-E*01:01 and HLA-E*01:03—which differ by one nonsynonymous amino acid substitution at position 107, resulting in an arginine in HLA-E*01:01 (HLA-E^R) and glycine in HLA-E*01:03 (HLA-E^G). In contrast to HLA-E^R,HLA-E^G has higher affinity to peptide, higher surface expression, and higher thermal stability of the corresponding protein, and it is more ancient than HLA-E^R, though both alleles are presented in human populations in nearly equal frequencies. In the current review, we aimed to uncover the reason of the expansion of the younger allele, HLA-E^R, by analysis of associations of both HLA-E alleles with a number of diseases, including viral and bacterial infections, cancer, and autoimmune disorders.

Development of data-driven models for the flow cytometric crossmatch

HLA laboratories use virtual crossmatching (VXM) to predict recipient and donor compatibility using HLA antibody data and donor HLA type. Increasingly, transplant centers are utilizing VXM as the final compatibility determination prior to transplant. However, the VXM interpretation is based on HLA experience of individual transplant centers. This study developed data-driven algorithms that predicted flow cytometric crossmatch (FCXM) outcomes using HLA antibody mean fluorescent intensity (MFI) data and donor HLA typing without the need for human interpretation.Two algorithms were evaluated; an MFI Optimal-Threshold model and a Least-Squares-Fitting model. The Optimal-Threshold model correctly determined between 81.5% and 85.5% of T or B-cell responses. A class I antibody MFI threshold of 4670 was optimal for predicting T-cell response while an antibody MFI threshold of 6180 was optimal for predicting B-cell responses. HLA class I antibodies had a 1.47-fold greater influence on FCXM outcomes than class II antibodies. HLA-B antibodies influenced T and B-cell responses more than HLA-A or -C (-B > -A > -C). The Least-Squares-Fitting model increased accuracy to 94.1% and 88.8% for T and B-cell responses, respectively. The algorithms described here provide enhanced FCXM prediction and novel insights into the influence of specific HLA antibodies on the crossmatch outcome.

Genome based screening of epitope ensemble vaccine candidates against dreadful visceral leishmaniasis using immunoinformatics approach

Visceral leishmaniasis (VL) is a dreadful protozoan disease caused by Leishmania donovani that severely affects huge populations in tropical and sub-tropical regions. The present study reports an unbiased genome based screening of 4 potent vaccine antigens against 8023 L. donovani proteins by following the criteria of presence of signal peptides, GPI-anchors and ≤1 transmembrane helix using advanced bioinformatics tools viz. SignalP4.0, PredGPI and TMHMM2.0, respectively. They are designated as genome based predicted signal peptide antigens (GBPSPA). The antigenicity/immunogenicity of chosen vaccine antigens (GBPSPA) with 4 randomly selected known leishmanial antigens (RSKLA) was compared by simulation study employing C-ImmSim software for human immune responses. This revealed better immunological responses. These antigens were further evaluated for the presence of B- and T-cell epitopes using immune epitope database (IEDB) based recommended consensus method of MHC class I and II tools. It was found to forecast CD4⁺ and CD8⁺ T-cell responses in genetically diverse human population worldwide as well as different endemic regions through IEDB based predicted population coverage (PPC) analysis tool. The worldwide percent PPC value of combined (HLA class I and II) epitope ensemble forecast was found to be 99.98, 99.96 and 50.04, respectively for GBPSPA, RSKLA and experimentally known epitopes (EKE) of L. donovani. Therefore, these potential antigens/epitope ensembles could favor the design of prospective and novel vaccine constructs like self-assembled epitopes as nano vaccine formulations against VL. Overall, the present study will serve as a model framework that might improve the effectiveness of designed vaccine against L. donovani and other related pathogens.

Engineered Adoptive T-cell Therapy Prolongs Survival in a Preclinical Model of Advanced-Stage Ovarian Cancer

Adoptive T-cell therapy using high-affinity T-cell receptors (TCR) to target tumor antigens has potential for improving outcomes in high-grade serous ovarian cancer (HGSOC) patients. Ovarian tumors develop a hostile, multicomponent tumor microenvironment containing suppressive cells, inhibitory ligands, and soluble factors that facilitate evasion of antitumor immune responses. Developing and validating an immunocompetent mouse model of metastatic ovarian cancer that shares antigenic and immunosuppressive qualities of human disease would facilitate establishing effective T-cell therapies. We used deep transcriptome profiling and IHC analysis of human HGSOC tumors and disseminated mouse ID8_VEGF tumors to compare immunologic features. We then evaluated the ability of CD8 T cells engineered to express a high-affinity TCR specific for mesothelin, an ovarian cancer antigen, to infiltrate advanced ID8_VEGF murine ovarian tumors and control tumor growth. Human CD8 T cells engineered to target mesothelin were also evaluated for ability to kill HLA-A2⁺ HGSOC lines. IHC and gene-expression profiling revealed striking similarities between tumors of both species, including processing/presentation of a leading candidate target antigen, suppressive immune cell infiltration, and expression of molecules that inhibit T-cell function. Engineered T cells targeting mesothelin infiltrated mouse tumors but became progressively dysfunctional and failed to persist. Treatment with repeated doses of T cells maintained functional activity, significantly prolonging survival of mice harboring late-stage disease at treatment onset. Human CD8 T cells engineered to target mesothelin were tumoricidal for three HGSOC lines. Treatment with engineered T cells may have clinical applicability in patients with advanced-stage HGSOC.

Bioinformatic methods for cancer neoantigen prediction

Tumor cells accumulate aberrations not present in normal cells, leading to presentation of neoantigens on MHC molecules on their surface. These non-self neoantigens distinguish tumor cells from normal cells to the immune system and are thus targets for cancer immunotherapy. The rapid development of molecular profiling platforms, such as next-generation sequencing, has enabled the generation of large datasets characterizing tumor cells. The simultaneous development of algorithms has enabled rapid and accurate processing of these data. Bioinformatic software tools encoding the algorithms can be strung together in a workflow to identify neoantigens. Here, with a focus on high-throughput sequencing, we review state-of-the art bioinformatic tools along with the steps and challenges involved in neoantigen identification and recognition.

Expression estimation and eQTL mapping for HLA genes with a personalized pipeline

The HLA (Human Leukocyte Antigens) genes are well-documented targets of balancing selection, and variation at these loci is associated with many disease phenotypes. Variation in expression levels also influences disease susceptibility and resistance, but little information exists about the regulation and population-level patterns of expression. This results from the difficulty in mapping short reads originated from these highly polymorphic loci, and in accounting for the existence of several paralogues. We developed a computational pipeline to accurately estimate expression for HLA genes based on RNA-seq, improving both locus-level and allele-level estimates. First, reads are aligned to all known HLA sequences in order to infer HLA genotypes, then quantification of expression is carried out using a personalized index. We use simulations to show that expression estimates obtained in this way are not biased due to divergence from the reference genome. We applied our pipeline to the GEUVADIS dataset, and compared the quantifications to those obtained with reference transcriptome. Although the personalized pipeline recovers more reads, we found that using the reference transcriptome produces estimates similar to the personalized pipeline (r ≥ 0.87) with the exception of HLA-DQA1. We describe the impact of the HLA-personalized approach on downstream analyses for nine classical HLA loci (HLA-A, HLA-C, HLA-B, HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). Although the influence of the HLA-personalized approach is modest for eQTL mapping, the p-values and the causality of the eQTLs obtained are better than when the reference transcriptome is used. We investigate how the eQTLs we identified explain variation in expression among lineages of HLA alleles. Finally, we discuss possible causes underlying differences between expression estimates obtained using RNA-seq, antibody-based approaches and qPCR.

Peptides as cancer vaccines

Cancer vaccines based on synthetic peptides are a safe, well-tolerated immunotherapy able to specifically stimulate tumor-reactive T cells. However, their clinical efficacy does not approach that achieved with other immunotherapies such as immune checkpoint blockade. Nevertheless, major advances have been made in selecting tumor antigens to target, identifying epitopes binding to classical and non-classical HLA molecules, and incorporating these into optimal sized peptides for formulation into a vaccine. Limited potency of currently used adjuvants and the immunosuppressive tumor microenvironment are now understood to be major impediments to vaccine efficacy that need to be overcome. Rationally designed combination therapies are now being tested and should ultimately enable peptide vaccination to be added to immuno-oncology treatment options.

Pathogen diversity drives the evolution of generalist MHC-II alleles in human populations

Central players of the adaptive immune system are the groups of proteins encoded in the major histocompatibility complex (MHC), which shape the immune response against pathogens and tolerance to self-peptides. The corresponding genomic region is of particular interest, as it harbors more disease associations than any other region in the human genome, including associations with infectious diseases, autoimmune disorders, cancers, and neuropsychiatric diseases. Certain MHC molecules can bind to a much wider range of epitopes than others, but the functional implication of such an elevated epitope-binding repertoire has remained largely unclear. It has been suggested that by recognizing more peptide segments, such promiscuous MHC molecules promote immune response against a broader range of pathogens. If so, the geographical distribution of MHC promiscuity level should be shaped by pathogen diversity. Three lines of evidence support the hypothesis. First, we found that in pathogen-rich geographical regions, humans are more likely to carry highly promiscuous MHC class II DRB1 alleles. Second, the switch between specialist and generalist antigen presentation has occurred repeatedly and in a rapid manner during human evolution. Third, molecular positions that define promiscuity level of MHC class II molecules are especially diverse and are under positive selection in human populations. Taken together, our work indicates that pathogen load maintains generalist adaptive immune recognition, with implications for medical genetics and epidemiology.

Whereas specialist major histocompatibility complex (MHC) molecules initiate immune response against only relatively few pathogens, generalists provide protection against a broad range. Accordingly, this study shows that the geographical distribution of generalist MHC alleles in human populations reflects exposure to diverse infectious diseases.

Variation in the human genome influences our susceptibility to infectious diseases, but the causal link between disease and underlying mutation often remains enigmatic. Major histocompatibility complex II (MHC class II) molecules shape both our immune response against pathogens and our tolerance of self-peptides. The genomic region that encodes MHC molecules is of particular interest, as it is home to more genetic disease associations than any other region in the human genome, including associations with infectious diseases, autoimmune disorders, cancers, and neuropsychiatric diseases. Here, we propose that MHC class II molecules can be categorized into two major types; specialists initiate effective immune response against only relatively few pathogens, while generalists provide protection against a broad range of pathogens. As support, we demonstrate that generalist MHC class II variants are more prevalent in human populations residing in pathogen-rich areas.