IMPROVE: a feature model to predict neoepitope immunogenicity through broad-scale validation of T-cell recognition

Background

Mutation-derived neoantigens are critical targets for tumor rejection in cancer immunotherapy, and better tools for neoepitope identification and prediction are needed to improve neoepitope targeting strategies. Computational tools have enabled the identification of patient-specific neoantigen candidates from sequencing data, but limited data availability has hindered their capacity to predict which of the many neoepitopes will most likely give rise to T cell recognition.

Method

To address this, we make use of experimentally validated T cell recognition towards 17,500 neoepitope candidates, with 467 being T cell recognized, across 70 cancer patients undergoing immunotherapy.

Results

We evaluated 27 neoepitope characteristics, and created a random forest model, IMPROVE, to predict neoepitope immunogenicity. The presence of hydrophobic and aromatic residues in the peptide binding core were the most important features for predicting neoepitope immunogenicity.

Conclusion

Overall, IMPROVE was found to significantly advance the identification of neoepitopes compared to other current methods.

MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer

Understanding the nature and extent of non-canonical human leukocyte antigen (HLA) presentation in tumour cells is a priority for target antigen discovery for the development of next generation immunotherapies in cancer. We here employ a de novo mass spectrometric sequencing approach with a refined, MHC-centric analysis strategy to detect non-canonical MHC-associated peptides specific to cancer without any prior knowledge of the target sequence from genomic or RNA sequencing data. Our strategy integrates MHC binding rank, Average local confidence scores, and peptide Retention time prediction for improved de novo candidate Selection; culminating in the machine learning model MARS. We benchmark our model on a large synthetic peptide library dataset and reanalysis of a published dataset of high-quality non-canonical MHC-associated peptide identifications in human cancer. We achieve almost 2-fold improvement for high quality spectral assignments in comparison to de novo sequencing alone with an estimated accuracy of above 85.7% when integrated with a stepwise peptide sequence mapping strategy. Finally, we utilize MARS to detect and validate lncRNA-derived peptides in human cervical tumour resections, demonstrating its suitability to discover novel, immunogenic, non-canonical peptide sequences in primary tumour tissue.

New light on the HLA-DR immunopeptidomic landscape

The set of peptides processed and presented by MHC class II molecules define the immunopeptidome, and its characterisation holds keys to understanding essential properties of the immune system. High-throughput mass spectrometry techniques enable interrogation of the diversity and complexity of the immunopeptidome at an unprecedented scale. Here, we analysed a large set of MS-immunopeptidomics data from 40 donors, 221 samples, covering 30 unique HLA-DR molecules. We identified likely co-immunoprecipitated HLA-DR irrelevant contaminants using state-of-the-art prediction methods and unveiled novel light on the properties of HLA antigen processing and presentation. The ligandome (HLA binders) was enriched in 15-mer peptides, and the contaminome (non-binders) in longer peptides. Classification of singletons and nested sets showed that the first were enriched in contaminants. Investigating the source protein location of ligands revealed that only contaminants shared a positional bias. Regarding subcellular localisation, nested peptides were found to predominantly be of endo-lysosomal whereas singletons shared an equal distribution between the cytosolic and endo-lysosomal origin. According to antigen processing signatures, no significant differences were observed between the cytosolic and endo-lysosomal ligands. Further, the sensitivity of MS-immunopeptidomics was investigated by analysing overlap and saturation between biological MS-replica, concluding that at least 5 replicas are needed to identify 80% of the immunopeptidome. Moreover, the overlap in immunopeptidome between donors was found to be very low both in terms of peptides and source proteins, the latter indicating a critical HLA bias in the antigen sampling in the HLA antigen presentation. Finally, the complementarity between MS and in-silico approaches for comprehensively sampling the immunopeptidome was demonstrated.

NetAllergen, a random forest model integrating MHC-II presentation propensity for improved allergenicity prediction

Motivation

Allergy is a pathological immune reaction towards innocuous protein antigens. Although only a narrow fraction of plant or animal proteins induce allergy, atopic disorders affect millions of children and adults and cost billions in healthcare systems worldwide. In silico predictors can aid in the development of more innocuous food sources. Previous allergenicity predictors used sequence similarity, common structural domains, and amino acid physicochemical features. However, these predictors strongly rely on sequence similarity to known allergens and fail to predict protein allergenicity accurately when similarity diminishes.

Results

To overcome these limitations, we collected allergens from AllergenOnline, a curated database of IgE-inducing allergens, carefully removed allergen redundancy with a novel protein partitioning pipeline, and developed a new allergen prediction method, introducing MHC presentation propensity as a novel feature. NetAllergen outperformed a sequence similarity-based BLAST baseline approach, and previous allergenicity predictor AlgPred 2 when similarity to known allergens is limited.

Availability and implementation

The web service NetAllergen and the datasets are available at https://services.healthtech.dtu.dk/services/NetAllergen-1.0/.

Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome

Human leukocyte antigen (HLA) class II antigen presentation is key for controlling and triggering T cell immune responses. HLA-DQ molecules, which are believed to play a major role in autoimmune diseases, are heterodimers that can be formed as both cis and trans variants depending on whether the α- and β-chains are encoded on the same (cis) or opposite (trans) chromosomes. So far, limited progress has been made for predicting HLA-DQ antigen presentation. In addition, the contribution of trans-only variants (i.e. variants not observed in the population as cis) in shaping the HLA-DQ immunopeptidome remains largely unresolved. Here, we seek to address these issues by integrating state-of-the-art immunoinformatics data mining models with large volumes of high-quality HLA-DQ specific mass spectrometry immunopeptidomics data. The analysis demonstrates highly improved predictive power and molecular coverage for models trained including these novel HLA-DQ data. More importantly, investigating the role of trans-only HLA-DQ variants reveals a limited to no contribution to the overall HLA-DQ immunopeptidome. In conclusion, this study furthers our understanding of HLA-DQ specificities and casts light on the relative role of cis versus trans-only HLA-DQ variants in the HLA class II antigen presentation space. The developed method, NetMHCIIpan-4.2, is available at https://services.healthtech.dtu.dk/services/NetMHCIIpan-4.2 .

Neoepitope load, T cell signatures and PD-L2 as combined biomarker strategy for response to checkpoint inhibition immunotherapy

Immune checkpoint inhibition for the treatment of cancer has provided a breakthrough in oncology, and several new checkpoint inhibition pathways are currently being investigated regarding their potential to provide additional clinical benefit. However, only a fraction of patients respond to such treatment modalities, and there is an urgent need to identify biomarkers to rationally select patients that will benefit from treatment. In this study, we explore different tumor associated characteristics for their association with favorable clinical outcome in a diverse cohort of cancer patients treated with checkpoint inhibitors. We studied 29 patients in a basket trial comprising 12 different tumor types, treated with 10 different checkpoint inhibition regimens. Our analysis revealed that even across this diverse cohort, patients achieving clinical benefit had significantly higher neoepitope load, higher expression of T cell signatures, and higher PD-L2 expression, which also correlated with improved progression-free and overall survival. Importantly, the combination of biomarkers serves as a better predictor than each of the biomarkers alone. Basket trials are frequently used in modern immunotherapy trial design, and here we identify a set of biomarkers of potential relevance across multiple cancer types, allowing for the selection of patients that most likely will benefit from immune checkpoint inhibition.

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.

Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome

Mass spectrometry (MS) based immunopeptidomics is used in several biomedical applications including neo-epitope discovery in oncology, next-generation vaccine development and protein-drug immunogenicity assessment. Immunopeptidome data are highly complex given the expression of multiple HLA alleles on the cell membrane and presence of co-immunoprecipitated contaminants. The absence of tools that deal with these challenges effectively and guide the analysis and interpretation of this complex type of data is currently a major bottleneck for the large-scale application of this technique. To resolve this, we here present the MHCMotifDecon that benefits from state-of-the-art HLA class-I and class-II predictions to accurately deconvolute immunopeptidome datasets and assign individual ligands to the most likely HLA molecule, allowing to identify and characterize HLA binding motifs while discarding co-purified contaminants. We have benchmarked the tool against other state-of-the-art methods and illustrated its application on experimental datasets for HLA-DR demonstrating a previously underappreciated role for HLA-DRB3/4/5 molecules in defining HLA class II immune repertoires. With its ease of use, MHCMotifDecon can efficiently guide interpretation of immunopeptidome datasets, serving the discovery of novel T cell targets. MHCMotifDecon is available at https://services.healthtech.dtu.dk/service.php?MHCMotifDecon-1.0.

Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins

Immunogenicity risk assessment is a critical element in protein drug development. Currently, the risk assessment is most often performed using MHC-associated peptide proteomics (MAPPs) and/or T-cell activation assays. However, this is a highly costly procedure that encompasses limited sensitivity imposed by sample sizes, the MHC repertoire of the tested donor cohort and the experimental procedures applied. Recent work has suggested that these techniques could be complemented by accurate, high-throughput and cost-effective prediction of in silico models. However, this work covered a very limited set of therapeutic proteins and eluted ligand (EL) data. Here, we resolved these limitations by showcasing, in a broader setting, the versatility of in silico models for assessment of protein drug immunogenicity. A method for prediction of MHC class II antigen presentation was developed on the hereto largest available mass spectrometry (MS) HLA-DR EL data set. Using independent test sets, the performance of the method for prediction of HLA-DR antigen presentation hotspots was benchmarked. In particular, the method was showcased on a set of protein sequences including four therapeutic proteins and demonstrated to accurately predict the experimental MS hotspot regions at a significantly lower false-positive rate compared with other methods. This gain in performance was particularly pronounced when compared to the NetMHCIIpan-3.2 method trained on binding affinity data. These results suggest that in silico methods trained on MS HLA EL data can effectively and accurately be used to complement MAPPs assays for the risk assessment of protein drugs.

Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction

Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adverse effects, including allergic reactions and compromised therapeutic efficacy. Production of ADAs is most often associated with activation of CD4 T cell responses resulting from proteolysis of the biotherapeutic and loading of drug-specific peptides into major histocompatibility complex (MHC) class II on professional antigen-presenting cells. Recently, readouts from MHC-associated peptide proteomics (MAPPs) assays have been shown to correlate with the presence of CD4 T cell epitopes. However, the limited sensitivity of MAPPs challenges its use as an immunogenicity biomarker. In this work, MAPPs data was used to construct an artificial neural network (ANN) model for MHC class II antigen presentation. Using Infliximab and Rituximab as showcase stories, the model demonstrated an unprecedented performance for predicting MAPPs and CD4 T cell epitopes in the context of protein-drug immunogenicity, complementing results from MAPPs assays and outperforming conventional prediction models trained on binding affinity data.

Improved Prediction of MHC II Antigen Presentation through Integration and Motif Deconvolution of Mass Spectrometry MHC Eluted Ligand Data

Major histocompatibility complex II (MHC II) molecules play a vital role in the onset and control of cellular immunity. In a highly selective process, MHC II presents peptides derived from exogenous antigens on the surface of antigen-presenting cells for T cell scrutiny. Understanding the rules defining this presentation holds critical insights into the regulation and potential manipulation of the cellular immune system. Here, we apply the NNAlign_MA machine learning framework to analyze and integrate large-scale eluted MHC II ligand mass spectrometry (MS) data sets to advance prediction of CD4+ epitopes. NNAlign_MA allows integration of mixed data types, handling ligands with multiple potential allele annotations, encoding of ligand context, leveraging information between data sets, and has pan-specific power allowing accurate predictions outside the set of molecules included in the training data. Applying this framework, we identified accurate binding motifs of more than 50 MHC class II molecules described by MS data, particularly expanding coverage for DP and DQ beyond that obtained using current MS motif deconvolution techniques. Furthermore, in large-scale benchmarking, the final model termed NetMHCIIpan-4.0 demonstrated improved performance beyond current state-of-the-art predictors for ligand and CD4+ T cell epitope prediction. These results suggest that NNAlign_MA and NetMHCIIpan-4.0 are powerful tools for analysis of immunopeptidome MS data, prediction of T cell epitopes, and development of personalized immunotherapies.

NNAlign_MA; MHC Peptidome Deconvolution for Accurate MHC Binding Motif Characterization and Improved T-cell Epitope Predictions

The set of peptides presented on a cell's surface by MHC molecules is known as the immunopeptidome. Current mass spectrometry technologies allow for identification of large peptidomes, and studies have proven these data to be a rich source of information for learning the rules of MHC-mediated antigen presentation. Immunopeptidomes are usually poly-specific, containing multiple sequence motifs matching the MHC molecules expressed in the system under investigation. Motif deconvolution -the process of associating each ligand to its presenting MHC molecule(s)- is therefore a critical and challenging step in the analysis of MS-eluted MHC ligand data. Here, we describe NNAlign_MA, a computational method designed to address this challenge and fully benefit from large, poly-specific data sets of MS-eluted ligands. NNAlign_MA simultaneously performs the tasks of (1) clustering peptides into individual specificities; (2) automatic annotation of each cluster to an MHC molecule; and (3) training of a prediction model covering all MHCs present in the training set. NNAlign_MA was benchmarked on large and diverse data sets, covering class I and class II data. In all cases, the method was demonstrated to outperform state-of-the-art methods, effectively expanding the coverage of alleles for which accurate predictions can be made, resulting in improved identification of both eluted ligands and T-cell epitopes. Given its high flexibility and ease of use, we expect NNAlign_MA to serve as an effective tool to increase our understanding of the rules of MHC antigen presentation and guide the development of novel T-cell-based therapeutics.

Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes

Recent advances in proteomics and mass-spectrometry have widely expanded the detectable peptide repertoire presented by major histocompatibility complex (MHC) molecules on the cell surface, collectively known as the immunopeptidome. Finely characterizing the immunopeptidome brings about important basic insights into the mechanisms of antigen presentation, but can also reveal promising targets for vaccine development and cancer immunotherapy. This report describes a number of practical and efficient approaches to analyze immunopeptidomics data, discussing the identification of meaningful sequence motifs in various scenarios and considering current limitations. Guidelines are provided for the filtering of false hits and contaminants, and to address the problem of motif deconvolution in cell lines expressing multiple MHC alleles, both for the MHC class I and class II systems. Finally, it is demonstrated how machine learning can be readily employed by non-expert users to generate accurate prediction models directly from mass-spectrometry eluted ligand data sets.

Splenic MAdCAM-1+ marginal reticular cells deliver antibody-inducing signals and confer gut-homing properties to human marginal zone B cells (IRC5P.622)

The splenic marginal zone (MZ) generates prompt antibody responses to blood-borne antigens through a unique subset of innate-like B cells that closely interact with poorly characterized stromal cells. We found that human MZ contained fibroblast-like marginal reticular cells (MRCs) that expressed MAdCAM-1 along with the stromal molecules Thy-1, thrombomodulin, ICAM-1 and VCAM-1, but lacked the endothelial molecules CD31, CD34 and von Willebrand factor. Similar to stromal lymphoid tissue organizers, MRCs up-regulated the adhesion molecules ICAM-1 and VCAM-1 in response to LT and TNF. Moreover, MRCs exposed to microbial TLR ligands, released the B cell-stimulating factors BAFF, APRIL and IL-6, which delivered survival, proliferation, class switching and plasma cell differentiation signals to MZ B cells. Plasma cells emerging from this pathway showed either T cell-dependent or T cell-independent ontogenetic features, and released IgM antibodies to conserved carbohydrate and lipid antigens shared by commensal and pathogenic bacteria. These antibodies decreased in splenectomized individuals. Finally, TLR-primed MRCs produced retinoic acid, which elicited MZ B cell expression of the gut-homing receptors a4b7 and CCR9. These findings indicate that MRCs have unique B cell-helper properties that could be harnessed to enhance vaccine-induced antibody responses systemically and perhaps at mucosal sites of antigen entry.

Radiofrequency minimally invasive endovascular treatment of lower limbs varicose veins: clinical experience and literature review

AIM

Varicose veins of the legs are a common condition affecting 10-15% of men and 20-25% of women in the western world. This high prevalence is responsible of high medical and social costs. Most primary varices are associated with greater saphenous vein (GSV) incompetence. A new method, radiofrequency (RF) endovenous obliteration (VNUS-Closure'' procedure), recently has been described as a less invasive and cost-saving alternative to stripping for the treatment of refluxing GSV.

METHODS

Twenty-four patients with varicose veins underwent endovenous obliteration of the above knee GSV by VNUS Closure'' procedure. The vein diameters were from 5 to 10 mm. The RF catheter was inserted via percutaneous puncture or through a small skin incision. All operations were performed in local, tumescent anesthesia, under ultrasound guidance. All patients were discharged 2 h after operation. Clinical and ultrasound follow-up was performed at 1 week, and at 1, 6, 12, 24 months.

RESULTS

The complete or partial occlusion of the treated segment of the GSV has been achieved in 23 cases. In only one patient persisting patency of the GSV was immediately detected after the procedure. That was successfully treated by ultrasound guided foam sclerotherapy. All patients could resume all normal activities within 3-5 days. Every patient had reduction of varicosities, leg pain, fatigue and oedema. Adverse sequelae were minimal: 2 patients had transient thigh paresthesias. We didn't report deep venous thrombosis or pulmonary embolism (mean follow-up 26.7 months, range 15-33 months).

CONCLUSION

A literature review and the authors'experience reveal that, in absence of significant complications, such as deep vein thrombosis and pulmonary embolism, there are significant advantages in the RF endovascular obliteration of the GSV. In effect, the Closure'' procedure, in selected patients, offers reduced postoperative pain, shorter sick leaves, faster return to normal activities compared with vein stripping, and it appears to be cost-saving for society. The mid-term (36 months) recurrence rates after RF obliteration seem to be similar to the results of the conventional surgical management.

Contrasting interspecies efficacy and toxicology of 1,2-diethyl-3-hydroxypyridin-4-one, CP94, relates to differing metabolism of the iron chelating site

In order to define a predictive animal model for the effects of hydroxypyridinone (HPO) iron chelators in humans, we have compared the 28 d oral efficacy and toxicology of the HPO, 1,2-diethyl-3-hydroxypyridin-4-one (CP94) in rats and guinea-pigs and related the results to the contrasting metabolism of this compound in the two species. CP94 was highly effective at mobilizing liver iron in rats but showed toxicity at higher doses, whereas in the guinea-pig the compound lacked toxicity but was ineffective at mobilizing liver iron. These differences can be explained by the contrasting metabolism of the drug between the two species. In rats, at the top dose of 300 mg/kg intragastrically, all animals died before the end of the study, with no deaths or weight loss at lower doses. At 100 mg/kg, rat liver non-haem iron concentrations were reduced by 53% and 44% in females and males respectively (P < 0.001). At this dose, adrenal medullary cell vacuolation, increased mammary secretory activity, vacuolation of corpora luteal cells and single cell hepatocyte necrosis were seen. There were no reductions in the white cell count. At 50 mg/kg rat liver non-haem iron concentrations were decreased by 50% and 34% in females and males respectively (P < 0.02). In female rats this was associated with increased mammary secretory activity. In iron-overloaded rats given 100 mg/kg by gavage for 28 d, liver non-haem iron concentration was reduced by 39% (P < 0.01) and serum ferritin by 71% (P < 0.001). Ovarian and mammary changes were not influenced by iron loading. In guinea-pigs, CP94 was evaluated at 50 mg/kg, 100 mg/kg or 200 mg/kg by oral insufflation for 28 d. No reduction in liver iron was seen and no systematic dose related histological, biochemical or haematological effects were observed. Whereas in guinea-pigs 99% of urinary recovery following an oral dose of CP94 (100 mg/kg) was as the inactive glucuronide metabolite, in the rat only 23% of the dose was excreted in the urine as the glucuronide with remainder as the free drug or an iron binding metabolite. The lack of both efficacy and toxicity in the guinea-pig may therefore be explained by the rapid inactivation of CP94 by glucuronidation. This metabolism of CP94 in the guinea-pig is closer to humans than the rat, suggesting that both the efficacy and toxicity of this compound in humans may also be limited by glucuronidation.

Abrogation of H-2-restricted CTL responses and efficient recognition of HLA-A3 molecules in DBA/2 HLA/A24 responder mice

DBA/2 (H-2d) HLA-B7 x human beta 2-microglobulin transgenic and DBA/2 nontransgenic mice stimulated by DBA/2 HLA-A3 x human beta 2-microglobulin transgenic mouse spleen cells developed potent H-2Kd restricted cytolytic responses with recognition of a peptide from the second domain of the HLA-A3 H chain. These H-2Kd-restricted responses obliterated, as a rule, cytolytic responses with direct recognition of the HLA-A3 molecules, even in HLA-B7 transgenic mice. These immunodominant H-2Kd-restricted responses could be abrogated in DBA/2 HLA-A24 mice because of cross-tolerance, the HLA-A3 derived-H-2Kd presented peptide being shared by several (including A24) HLA class I H chain allelic variants. Under such experimental circumstances, strong CTL responses with exclusive direct recognition of HLA-A3 molecules constantly developed. Further analysis of these responses in six DBA/2 HLA-A24 responder mice indicated that a large fraction of the mouse V beta and V alpha genes could be used to mount such CTL responses. Thus, by combining classical HLA class I transgenesis and selective destruction of H-2K and H-2D genes, it should be possible to derive useful strains of mice for the study of HLA class I-restricted CTL responses.

Abrogation of H-2-restricted CTL responses and efficient recognition of HLA-A3 molecules in DBA/2 HLA/A24 responder mice

DBA/2 (H-2d) HLA-B7 x human beta 2-microglobulin transgenic and DBA/2 nontransgenic mice stimulated by DBA/2 HLA-A3 x human beta 2-microglobulin transgenic mouse spleen cells developed potent H-2Kd restricted cytolytic responses with recognition of a peptide from the second domain of the HLA-A3 H chain. These H-2Kd-restricted responses obliterated, as a rule, cytolytic responses with direct recognition of the HLA-A3 molecules, even in HLA-B7 transgenic mice. These immunodominant H-2Kd-restricted responses could be abrogated in DBA/2 HLA-A24 mice because of cross-tolerance, the HLA-A3 derived-H-2Kd presented peptide being shared by several (including A24) HLA class I H chain allelic variants. Under such experimental circumstances, strong CTL responses with exclusive direct recognition of HLA-A3 molecules constantly developed. Further analysis of these responses in six DBA/2 HLA-A24 responder mice indicated that a large fraction of the mouse V beta and V alpha genes could be used to mount such CTL responses. Thus, by combining classical HLA class I transgenesis and selective destruction of H-2K and H-2D genes, it should be possible to derive useful strains of mice for the study of HLA class I-restricted CTL responses.

T cell receptor selection by and recognition of two class I major histocompatibility complex-restricted antigenic peptides that differ at a single position

Peptides derived from HLA-Cw3 and HLA-A24 within region 170-179 differ by a single substitution, at position 173, and are both presented by the class I major histocompatibility complex molecule H-2Kd for recognition by murine cytolytic T lymphocytes (CTLs). As a first approach to understand the way T cell receptors (TCRs) intact with the HLA peptides, we have analyzed the TCR selection by, and recognition of, the two HLA antigenic sites. First, we have compared the TCR repertoires selected by HLA-Cw3 and HLA-A24, not only by sequencing the TCRs carried by CTL clones isolated and grown in vitro, but also by analyzing the TCRs expressed in vivo by peritoneal exudate lymphocytes from immune animals. Second, we have compared the TCR crossrecognition of HLA-A24 by CTLs selected by HLA-Cw3 with that of HLA-Cw3 by CTLs selected by HLA-A24. The combined analysis of TCR selection by and recognition of these two related HLA antigenic sites provides evidence that the TCR beta junctional regions interact with the amino-terminal part of the HLA peptides.

H-2-restricted cytolytic T lymphocytes specific for HLA display T cell receptors of limited diversity

We previously showed that H-2Kd-restricted cytotoxic T lymphocyte (CTL) clones specific for a single nonapeptide derived from the Plasmodium berghei circumsporozoite (PbCS) protein displayed T cell receptors (TCRs) of highly diverse primary structure. We have now analyzed the TCR repertoire of CTLs that recognize a peptide derived from the human class I major histocompatibility complex (MHC) molecule HLA-Cw3 in association with the same murine class I MHC molecule H-2Kd. We first sequenced the TCR alpha and beta genes of the CTL clone Cw3/1.1 and, based on this genomic analysis, the TCR alpha and beta cDNA junctional regions of 23 independent H-2Kd-restricted CTL clones specific for HLA-Cw3. The results show that the TCR chains display very limited heterogeneity, both in terms of V alpha, J alpha, V beta, and J beta segments, and in terms of length and sequence of the CDR3 alpha and beta loops. The TCR repertoire used in vivo was then analyzed by harvesting CTL populations from the peritoneal cavity of immune mice. The peritoneal exudate lymphocytes (PELs) displayed HLA-Cw3-specific cytolytic activity in the absence of any stimulation in vitro. Remarkably, most of these freshly isolated PELs expressed TCRs that shared the same structural features as those from HLA-Cw3-reactive CTL clones. Thus, our results show that a peptide from HLA-Cw3 presented by H-2Kd selects CTLs that bear TCRs of very limited diversity in vivo. When taken together with the high diversity of the TCRs specific for the PbCS peptide, these findings suggest that natural tolerance to self peptides presented by class I MHC molecules may substantially reduce the size of the TCR repertoire of CTLs specific for antigenic peptides homologous to self.

Analysis of the HLA-Cw3-specific cytotoxic T lymphocyte response of HLA-B7 X human beta 2m double transgenic mice

The cytolytic responses of either normal (non transgenic), HLA-B7 (single transgenic) or HLA-B7 x human beta 2 microglobulin (double transgenic) DBA/2 mice induced by transfected HLA-Cw3 P815 (H-2d) mouse mastocytoma cells were compared, to evaluate whether the expression of an HLA class I molecule in responder mice would favor the emergence of HLA-specific, H-2-unrestricted CTL. Only 8 of 300 HLA-Cw3-specific CTL clones tested could selectively lyse HLA-Cw3-transfected cells in an H-2-unrestricted manner, all having been isolated after hyperimmunization of double transgenic mice. These clones also lysed HLA-Cw3+ human cells. Unexpectedly, the lysis of the human but not that of the murine HLA-Cw3 cells was inhibited by Ly-2,3-specific mAb. Despite significant expression of HLA-B7 class I molecules on transgenic lymphoid cells, including thymic cells, limiting dilution analysis and comparative study of TCR-alpha and -beta gene rearrangements of the eight isolated clones (which suggested that they all derived from the same CTL precursor) indicated that the frequency of HLA-Cw3-specific H-2 unrestricted cytotoxic T lymphocytes remained low (even in HLA-B7 x human beta 2-microglobulin double transgenic mice). This suggests that coexpression of HLA class I H and L chain in transgenic mice is not the only requirement for significant positive selection of HLA class I-restricted cytotoxic mouse T lymphocytes.

Analysis of the HLA-Cw3-specific cytotoxic T lymphocyte response of HLA-B7 X human beta 2m double transgenic mice

The cytolytic responses of either normal (non transgenic), HLA-B7 (single transgenic) or HLA-B7 x human beta 2 microglobulin (double transgenic) DBA/2 mice induced by transfected HLA-Cw3 P815 (H-2d) mouse mastocytoma cells were compared, to evaluate whether the expression of an HLA class I molecule in responder mice would favor the emergence of HLA-specific, H-2-unrestricted CTL. Only 8 of 300 HLA-Cw3-specific CTL clones tested could selectively lyse HLA-Cw3-transfected cells in an H-2-unrestricted manner, all having been isolated after hyperimmunization of double transgenic mice. These clones also lysed HLA-Cw3+ human cells. Unexpectedly, the lysis of the human but not that of the murine HLA-Cw3 cells was inhibited by Ly-2,3-specific mAb. Despite significant expression of HLA-B7 class I molecules on transgenic lymphoid cells, including thymic cells, limiting dilution analysis and comparative study of TCR-alpha and -beta gene rearrangements of the eight isolated clones (which suggested that they all derived from the same CTL precursor) indicated that the frequency of HLA-Cw3-specific H-2 unrestricted cytotoxic T lymphocytes remained low (even in HLA-B7 x human beta 2-microglobulin double transgenic mice). This suggests that coexpression of HLA class I H and L chain in transgenic mice is not the only requirement for significant positive selection of HLA class I-restricted cytotoxic mouse T lymphocytes.

Cytotoxic T lymphocyte recognition of secreted HLA class I molecules

The cytolytic responses of DBA/2 mice against syngeneic transfected P815 mastocytoma cells expressing either membrane-associated (HLA-Cw3) or -secreted hybrid (HLA-Cw3 x H-2 Q10b) molecules were compared. In spite of the absence of serologically detectable hybrid molecules on their plasma membrane, cells secreting these molecules elicited a CTL response similar to that of cells expressing the membrane associated HLA-Cw3 molecules, in terms of both MHC-restriction and peptide specificity. Together with the observation that syngeneic mice were capable of rejecting the injected secreting cells, these results imply that secreted HLA class I molecules can function as minor histocompatibility Ag and suggest that processing of both the membrane-bound and the -secreted forms of a protein may follow common or overlapping pathways.

Cytotoxic T lymphocyte recognition of secreted HLA class I molecules

The cytolytic responses of DBA/2 mice against syngeneic transfected P815 mastocytoma cells expressing either membrane-associated (HLA-Cw3) or -secreted hybrid (HLA-Cw3 x H-2 Q10b) molecules were compared. In spite of the absence of serologically detectable hybrid molecules on their plasma membrane, cells secreting these molecules elicited a CTL response similar to that of cells expressing the membrane associated HLA-Cw3 molecules, in terms of both MHC-restriction and peptide specificity. Together with the observation that syngeneic mice were capable of rejecting the injected secreting cells, these results imply that secreted HLA class I molecules can function as minor histocompatibility Ag and suggest that processing of both the membrane-bound and the -secreted forms of a protein may follow common or overlapping pathways.