Class II MHC self-antigen presentation in human B and T lymphocytes

Human CD4(+) T cells process and present functional class II MHC-peptide complexes, but the endogenous peptide repertoire of these non-classical antigen presenting cells remains unknown. We eluted and sequenced HLA-DR-bound self-peptides presented by CD4(+) T cells in order to compare the T cell-derived peptide repertoire to sequences derived from genetically identical B cells. We identified several novel epitopes derived from the T cell-specific proteome, including fragments of CD4 and IL-2. While these data confirm that T cells can present peptides derived from the T-cell specific proteome, the vast majority of peptides sequenced after elution from MHC were derived from the common proteome. From this pool, we identified several identical peptide epitopes in the T and B cell repertoire derived from common endogenous proteins as well as novel endogenous epitopes with promiscuous binding. These findings indicate that the endogenous HLA-DR-bound peptide repertoire, regardless of APC type and across MHC isotype, is largely derived from the same pool of self-protein.     

The turnover kinetics of major histocompatibility complex peptides of human cancer cells

Peptides presented by the major histocompatibility complex (MHC) are derived from the degradation of cellular proteins. Thus, the repertoire of these peptides (the MHC peptidome) should correlate better with the cellular protein degradation scheme (the degradome) than with the cellular proteome. To test the validity of this statement and to determine whether the majority of MHC peptides are derived from short lived proteins, from defective ribosome products, or from regular long lived cellular proteins we analyzed in parallel the turnover kinetics of both MHC peptides and cellular proteins in the same cancer cells. The analysis was performed by pulse-chase experiments based on stable isotope labeling in tissue culture followed by capillary chromatography and tandem mass spectrometry. Indeed only a limited correlation was observed between the proteome and the MHC peptidome observed in the same cells. Moreover a detailed analysis of the turnover kinetics of the MHC peptides helped to assign their origin to normal, to short lived or long lived proteins, or to the defective ribosome products. Furthermore the analysis of the MHC peptides turnover kinetics helped to direct attention to abnormalities in the degradation schemes of their source proteins. These observations can be extended to search for cancer-related abnormalities in protein degradation, including those that lead to loss of tumor suppressors and cell cycle regulatory proteins.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

Mass spectrometry analysis and quantitation of peptides presented on the MHC II molecules of mouse spleen dendritic cells

Major histocompatibility complex class II (MHC II) molecules are expressed on the surface of antigen-presenting cells and display short bound peptide fragments derived from self- and nonself antigens. These peptide-MHC complexes function to maintain immunological tolerance in the case of self-antigens and initiate the CD4(+) T cell response in the case of foreign proteins. Here we report the application of LC-MS/MS analysis to identify MHC II peptides derived from endogenous proteins expressed in freshly isolated murine splenic DCs. The cell number was enriched in vivo upon treatment with Flt3L-B16 melanoma cells. In a typical experiment, starting with about 5 × 10(8) splenic DCs, we were able to reliably identify a repertoire of over 100 MHC II peptides originating from about 55 proteins localized in membrane (23%), intracellular (26%), endolysosomal (12%), nuclear (14%), and extracellular (25%) compartments. Using synthetic isotopically labeled peptides corresponding to the sequences of representative bound MHC II peptides, we quantified by LC-MS relative peptide abundance. In a single experiment, peptides were detected in a wide concentration range spanning from 2.5 fmol/μL to 12 pmol/μL or from approximately 13 to 2 × 10(5) copies per DC. These peptides were found in similar amounts on B cells where we detected about 80 peptides originating from 55 proteins distributed homogenously within the same cellular compartments as in DCs. About 90 different binding motifs predicted by the epitope prediction algorithm were found within the sequences of the identified MHC II peptides. These results set a foundation for future studies to quantitatively investigate the MHC II repertoire on DCs generated under different immunization conditions.     

Contribution of mass spectrometry-based proteomics to immunology

Antigen processing forwards various information about the cellular status and the proteome to the cell surface for scrutiny by the cellular immune system. Thus the repertoire of major histocompatibility complex (MHC)-bound peptides and the MHC ligandome, indirectly mirrors the proteome in order to make alterations instantly detectable and, if necessary, to oppose them. Mass spectrometry is the core technology for analysis of both proteome and MHC ligandome and has evoked several strategies to gain qualitative and quantitative insight into the MHC-presented peptide repertoire. After immunoaffinity purification of detergent-solubilized peptide-MHC complexes followed by acid elution of peptides, liquid chromatography-mass spectrometry is applied to determine individual peptide sequences and, thus, allow qualitative characterization of the MHC-bound repertoire. Differential quantification based on stable isotope labeling enables the relative comparison of two samples, such as diseased and healthy tissue. Targeted searches for certain natural ligands, such as the 'predict-calibrate-detect' strategy, include motif-based epitope prediction and calibration with reference peptides. Thus, various approaches are now available for exposing and understanding the intricacies of the MHC ligand repertoire. Analysis of differences in the MHC ligandome under distinct conditions contributes to our understanding of basic cellular processes, but also enables the formulation of immunodiagnostic or immunotherapeutic strategies.     

Quantitative immunoproteomics analysis reveals novel MHC class I presented peptides in cisplatin-resistant ovarian cancer cells

Platinum-based chemotherapy is widely used to treat various cancers including ovarian cancer. However, the mortality rate for patients with ovarian cancer is extremely high, largely due to chemo-resistant progression in patients who respond initially to platinum based chemotherapy. Immunotherapy strategies, including antigen specific vaccines, are being tested to treat drug resistant ovarian cancer with variable results. The identification of drug resistant specific tumor antigens would potentially provide significant improvement in effectiveness when combined with current and emerging therapies. In this study, using an immunoproteomics method based on iTRAQ technology and an LC-MS platform, we identified 952 MHC class I presented peptides. Quantitative analysis of the iTRAQ labeled MHC peptides revealed that cisplatin-resistant ovarian cancer cells display increased levels of MHC peptides derived from proteins that are implicated in many important cancer pathways. In addition, selected differentially presented epitope specific CTL recognize cisplatin-resistant ovarian cancer cells significantly better than the sensitive cells. These over-presented, drug resistance specific MHC class I associated peptide antigens could be potential targets for the development of immunotherapeutic strategies for the treatment of ovarian cancer including the drug resistant phenotype.     

Enhanced recovery of lyophilized peptides in shotgun proteomics by using an LC‐ESI‐MS compatible surfactant

LC‐ESI/MS/MS‐based shotgun proteomics is currently the most commonly used approach for the identification and quantification of proteins in large‐scale studies of biomarker discovery. In the past several years, the shotgun proteomics technologies have been refined toward further enhancement of proteome coverage. In the complex series of protocols involved in shotgun proteomics, however, loss of proteolytic peptides during the lyophilization step prior to the LC/MS/MS injection has been relatively neglected despite the fact that the dissolution of the hydrophobic peptides in lyophilized samples is difficult in 0.05–0.1% TFA or formic acid, causing substantial loss of precious peptide samples. In order to prevent the loss of peptide samples during this step, we devised a new protocol using Invitrosol (IVS), a commercially available surfactant compatible with ESI‐MS; by dissolving the lyophilized peptides in IVS, we show improved recovery of hydrophobic peptides, leading to enhanced coverage of proteome. Thus, the use of IVS in the recovery step of lyophilized peptides will help the shotgun proteomics analysis by expanding the proteome coverage, which would significantly promote the discovery and development of new diagnostic markers and therapeutic targets.     

Ionizing Radiation Drives Key Regulators of Antigen Presentation and a Global Expansion of the Immunopeptidome

Little is known about the pathways regulating MHC antigen presentation and the identity of treatment-specific T cell antigens induced by ionizing radiation. For this reason, we investigated the radiation-specific changes in the colorectal tumor cell proteome. We found an increase in DDX58 and ZBP1 protein expression, two nucleic acid sensing molecules likely involved in induction of the dominant interferon response signature observed after genotoxic insult. We further observed treatment-induced changes in key regulators and effector proteins of the antigen processing and presentation machinery. Differential regulation of MHC allele expression was further driving the presentation of a significantly broader MHC-associated peptidome postirradiation, defining a radiation-specific peptide repertoire. Interestingly, treatment-induced peptides originated predominantly from proteins involved in catecholamine synthesis and metabolic pathways. A nuanced relationship between protein expression and antigen presentation was observed where radiation-induced changes in proteins do not correlate with increased presentation of associated peptides. Finally, we detected an increase in the presentation of a tumor-specific neoantigen derived from Mtch1. This study provides new insights into how radiation enhances antigen processing and presentation that could be suitable for the development of combinatorial therapies. Data are available via ProteomeXchange with identifier PXD032003.     

Candidate epitope identification using peptide property models: application to cancer immunotherapy

Peptides derived from pathogens or tumors are selectively presented by the major histocompatibility complex proteins (MHC) to the T lymphocytes. Antigenic peptide-MHC complexes on the cell surface are specifically recognized by T cells and, in conjunction with co-factor interactions, can activate the T cells to initiate the necessary immune response against the target cells. Peptides that are capable of binding to multiple MHC molecules are potential T cell epitopes for diverse human populations that may be useful in vaccine design. Bioinformatical approaches to predict MHC binding peptides can facilitate the resource-consuming effort of T cell epitope identification. We describe a new method for predicting MHC binding based on peptide property models constructed using biophysical parameters of the constituent amino acids and a training set of known binders. The models can be applied to development of anti-tumor vaccines by scanning proteins over-expressed in cancer cells for peptides that bind to a variety of MHC molecules. The complete algorithm is described and illustrated in the context of identifying candidate T cell epitopes for melanomas and breast cancers. We analyzed MART-1, S-100, MBP, and CD63 for melanoma and p53, MUC1, cyclin B1, HER-2/neu, and CEA for breast cancer. In general, proteins over-expressed in cancer cells may be identified using DNA microarray expression profiling. Comparisons of model predictions with available experimental data were assessed. The candidate epitopes identified by such a computational approach must be evaluated experimentally but the approach can provide an efficient and focused strategy for anti-cancer immunotherapy development.     

Large-scale analysis of HLA peptides presented by HLA-Cw4

A large number of HLA-Cw4 (Cw *0402) peptides were purified, sequenced, and identified from breast and ovarian carcinoma cell lines. HLA-Cw4 molecules were expressed in these cells as soluble, secreted HLA (sHLA) and recovered from the growth medium. The peptides were separated by capillary reversed-phase HPLC and analyzed by tandem mass-spectrometry. The resulting peptides fit to some extent, but not completely, the known consensus of the Cw4 peptide-binding motif. Among the identified peptides, there are a few that originate from proteins of possible interest for cancer immunotherapy or diagnostics, including mucin-5B, ART-1, fatty acid synthase, putative prostate cancer tumor suppressor, DNA topoisomerase-1, and Rac1. This work demonstrates that large-scale identification of HLA peptides recovered from sHLA is an advantageous approach for establishing the HLA peptide consensus of different haplotypes and the identification of useful peptides for treatment of diseases such as cancer, viral, and autoimmune diseases.     

Toward a definition of self: proteomic evaluation of the class I peptide repertoire

MHC class I molecules present host- and pathogen-derived peptides for immune surveillance. Much attention is given to the search for viral and tumor nonself peptide epitopes, yet the question remains, "What is self?" Analyses of Edman motifs and of small sets of individual peptides suggest that the class I self repertoire consists of thousands of different peptides. However, there exists no systematic characterization of this self-peptide backdrop, causing the definition of class I-presented self to remain largely hypothetical. To better understand the breadth and nature of self proteins sampled by class I HLA, we sequenced >200 endogenously loaded HLA-B*1801 peptides from a human B cell line. Peptide-source proteins, ranging from actin-related protein 6 to zinc finger protein 147, possessed an assortment of biological and molecular functions. Major categories included binding proteins, catalytic proteins, and proteins involved in cell metabolism, growth, and maintenance. Genetically, peptides encoded by all chromosomes were presented. Statistical comparison of proteins presented by class I vs the human proteome provides empiric evidence that the range of proteins sampled by class I is relatively unbiased, with the exception of RNA-binding proteins that are over-represented in the class I peptide repertoire. These data show that, in this cell line, class I-presented self peptides represent a comprehensive and balanced summary of the proteomic content of the cell. Importantly, virus- and tumor-induced changes in virtually any cellular compartment or to any chromosome can be expected to be presented by class I molecules for immune recognition.     

Relative quantitation of proteins in expressed prostatic secretion with a stable isotope labeled secretome standard

Expressed prostatic secretion (EPS) is a proximal fluid directly derived from the prostate and, in the case of prostate cancer (PCa), is hypothesized to contain a repertoire of cancer-relevant proteins. Quantitative analysis of the EPS proteome may enable identification of proteins with utility for PCa diagnosis and prognosis. The present investigation demonstrates selective quantitation of proteins in EPS samples from PCa patients using a stable isotope labeled proteome standard (SILAP) generated through the selective harvest of the "secretome" from the PC3 prostate cancer cell line grown in stable isotope labeled cell culture medium. This stable isotope labeled secretome was digested with trypsin and equivalently added to each EPS digest, after which the resultant mixtures were analyzed by liquid chromatography-tandem mass spectrometry for peptide identification and quantification. Relative quantification of endogenous EPS peptides was accomplished by comparison of reconstructed mass chromatograms to those of the chemically identical SILAP peptides. A total of 86 proteins were quantified from 263 peptides in all of the EPS samples, 38 of which were found to be relevant to PCa. This work demonstrates the feasibility of using a SILAP secretome standard to simultaneously quantify many PCa-relevant proteins in EPS samples.     

Dissection of the HLA-DR4 peptide repertoire in endocrine epithelial cells: strong influence of invariant chain and HLA-DM expression on the nature of ligands

Class II MHC (MHC II) expression is restricted to professional APCs and thymic epithelium but it also occurs in the epithelial cells of autoimmune organs which are the unique targets of the CD4 autoreactive T cells in endocrine autoimmune diseases. This specificity is presumably conditioned by an epithelium-specific peptide repertoire associated to MHC II at the cell surface. MHC II expression and function is dependent on the action of two main chaperones, invariant chain (Ii) and DM, whose expression is coregulated with MHC II. However, there is limited information about the in vivo expression levels of these molecules and uncoordinated expression has been demonstrated in class II-positive epithelial cells that may influence the MHC-associated peptide repertoires and the outcome of the autoimmune response. We have examined the pool of peptides associated to DR4 molecules expressed by a neuroendocrine epithelial cell and the consequences of Ii and DM coexpression. The RINm5F rat insulinoma cell line was transfected with HLA-DRB1*0401, Ii, and DM molecules in four different combinations: RIN-DR4, -DR4Ii, -DR4DM, and -DR4IiDM. The analysis of the peptide repertoire and the identification of the DR4 naturally processed ligands in each transfected cell were achieved by mass spectrometry. The results demonstrate that 1) the expression of Ii and DM affected the DR4 peptide repertoires by producing important variations in their content and in the origin of peptides; 2) these restrictions affected the stability and sequence of the peptides of each repertoire; and 3) Ii and DM had both independent and coordinate effects on these repertoires.     

The Dendritic Cell Major Histocompatibility Complex II (MHC II) Peptidome Derives from a Variety of Processing Pathways and Includes Peptides with a Broad Spectrum of HLA-DM Sensitivity

The repertoire of peptides displayed in vivo by MHC II molecules derives from a wide spectrum of proteins produced by different cell types. Although intracellular endosomal processing in dendritic cells and B cells has been characterized for a few antigens, the overall range of processing pathways responsible for generating the MHC II peptidome are currently unclear. To determine the contribution of non-endosomal processing pathways, we eluted and sequenced over 3000 HLA-DR1-bound peptides presented in vivo by dendritic cells. The processing enzymes were identified by reference to a database of experimentally determined cleavage sites and experimentally validated for four epitopes derived from complement 3, collagen II, thymosin β4, and gelsolin. We determined that self-antigens processed by tissue-specific proteases, including complement, matrix metalloproteases, caspases, and granzymes, and carried by lymph, contribute significantly to the MHC II self-peptidome presented by conventional dendritic cells in vivo. Additionally, the presented peptides exhibited a wide spectrum of binding affinity and HLA-DM susceptibility. The results indicate that the HLA-DR1-restricted self-peptidome presented under physiological conditions derives from a variety of processing pathways. Non-endosomal processing enzymes add to the number of epitopes cleaved by cathepsins, altogether generating a wider peptide repertoire. Taken together with HLA-DM-dependent and-independent loading pathways, this ensures that a broad self-peptidome is presented by dendritic cells. This work brings attention to the role of “self-recognition” as a dynamic interaction between dendritic cells and the metabolic/catabolic activities ongoing in every parenchymal organ as part of tissue growth, remodeling, and physiological apoptosis.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

Direct discovery and validation of a peptide/MHC epitope expressed in primary human breast cancer cells using a TCRm monoclonal antibody with profound antitumor properties

The identification and validation of new cancer-specific T cell epitopes continues to be a major area of research interest. Nevertheless, challenges remain to develop strategies that can easily discover and validate epitopes expressed in primary cancer cells. Regarded as targets for T cells, peptides presented in the context of the major histocompatibility complex (MHC) are recognized by monoclonal antibodies (mAbs). These mAbs are of special importance as they lend themselves to the detection of epitopes expressed in primary tumor cells. Here, we use an approach that has been successfully utilized in two different infectious disease applications (WNV and influenza). A direct peptide-epitope discovery strategy involving mass spectrometric analysis led to the identification of peptide YLLPAIVHI in the context of MHC A*02 allele (YLL/A2) from human breast carcinoma cell lines. We then generated and characterized an anti-YLL/A2 mAb designated as RL6A TCRm. Subsequently, the TCRm mAb was used to directly validate YLL/A2 epitope expression in human breast cancer tissue, but not in normal control breast tissue. Moreover, mice implanted with human breast cancer cells grew tumors, yet when treated with RL6A TCRm showed a marked reduction in tumor size. These data demonstrate for the first time a coordinated direct discovery and validation strategy that identified a peptide/MHC complex on primary tumor cells for antibody targeting and provide a novel approach to cancer immunotherapy.     

热休克蛋白-多肽复合物在肿瘤和传染性疾病免疫中的作用

热休克蛋白家族中的许多成员如gp96\,HSP90\,HSP70等具有排斥和治疗肿瘤及传染性疾病的免疫原性,进一步研究发现热休克蛋白作为分子伴侣可结合细胞中的肽库,它本身没有抗原性,抗原性由结合的短肽所决定。热休克蛋白将结合的短肽呈递给I类MHC分子,进而激活特异性CTL和记忆性T细胞,引发机体细胞免疫反应。据最新发现gp96还可能有与MHC一样的功能,可直接将结合的多肽抗原呈递给T细胞。近年来对哺乳动物的二种主要热休克蛋白gp96和HSP70的免疫机制和作为治疗性疫苗的优越性进行了详细研究,这为乙型肝炎和乙肝继发性肝癌的免疫治疗提供了新思路。     

Unbiased identification of target antigens of CD8+ T cells with combinatorial libraries coding for short peptides

Cytotoxic CD8(+) T cells recognize the antigenic peptides presented by class I major histocompatibility complex (MHC) molecules. These T cells have key roles in infectious diseases, autoimmunity and tumor immunology, but there is currently no unbiased method for the reliable identification of their target antigens. This is because of the low affinities of antigen-specific T cell receptors (TCR) to their target MHC-peptide complexes, the polyspecificity of these TCRs and the requirement that these TCRs recognize protein antigens that have been processed by antigen-presenting cells (APCs). Here we describe a technology for the unbiased identification of the antigenic peptides presented by MHC class I molecules. The technology uses plasmid-encoded combinatorial peptide libraries and a single-cell detection system. We validated this approach using a well-characterized influenza-virus–specific TCR, MHC and peptide combination. Single APCs carrying antigenic peptides can be detected among several million APCs that carry irrelevant peptides. The identified peptide sequences showed a converging pattern of mimotopes that revealed the parent influenza antigen. This technique should be generally applicable to the identification of disease-relevant T cell antigens.     

Heat shock protein–peptide complexes as immunotherapy for human cancer

Heat shock proteins (Hsps), ubiquitous in nature, act as chaperones for peptides and other proteins. They have been implicated in loading immunogenic peptides onto major histocompatibility complex molecules for presentation to T cells. When isolated from tumor cells, Hsps are complexed with a wide array of peptides, some of which serve as tumor-specific antigens. Animal studies have demonstrated that heat shock protein–peptide complexes (HSPPCs) from tumor cells can act as vaccines to prevent or treat tumors. Potent and specific tumor antigens have long been the holy grail in cancer immunotherapy; HSPPCs from tumor cells could become a safe and reliable source of tumor-specific antigens for clinical application.