Daniel J. Kowalewski

HLA ligandome analysis identifies the underlying specificities of spontaneous antileukemia immune responses in chronic lymphocytic leukemia (CLL)

Significance Effective cancer immunotherapy relies on specific immune recognition of tumor-associated and tumor-specific antigens. In chronic lymphocytic leukemia (CLL), the highly variable course of disease implicates an underlying mechanism of tumor control by the immune system. In this study, we directly analyzed the landscape of naturally presented CLL antigens and identified targets conveying immune protection. These novel antigens might be valuable both for patient stratification and for inducing therapeutic antitumor immunity. Taken together, we demonstrate that CLL is subject to spontaneous T-cell responses targeting nonmutated antigens, which are associated with improved patient survival and provide novel options for the immunotherapy of CLL. The breakthrough development of clinically effective immune checkpoint inhibitors illustrates the potential of T-cell–based immunotherapy to effectively treat malignancies. A remaining challenge is to increase and guide the specificities of anticancer immune responses, e.g., by therapeutic vaccination or by adoptive T-cell transfer. By analyzing the landscape of naturally presented HLA class I and II ligands of primary chronic lymphocytic leukemia (CLL), we delineated a novel category of tumor-associated T-cell antigens based on their exclusive and frequent representation in the HLA ligandome of leukemic cells. These antigens were validated across different stages and mutational subtypes of CLL and found to be robustly represented in HLA ligandomes of patients undergoing standard chemo-/immunotherapy. We demonstrate specific immune recognition of these antigens exclusively in CLL patients, with the frequencies of representation in CLL ligandomes correlating with the frequencies of immune recognition by patient T cells. Moreover, retrospective survival analysis revealed survival benefits for patients displaying immune responses to these antigens. These results directly imply these nonmutant self-peptides as pathophysiologically relevant tumor antigens and encourages their implementation for cancer immunotherapy.

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry

The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field.

An open-source computational and data resource to analyze digital maps of immunopeptidomes.

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies. DOI: http://dx.doi.org/10.7554/eLife.07661.001

The antigenic landscape of multiple myeloma: mass spectrometry (re-)defines targets for T-cell based immunotherapy

Direct analysis of HLA-presented antigens by mass spectrometry provides a comprehensive view on the antigenic landscape of different tissues/malignancies and enables the identification of novel, pathophysiologically relevant T-cell epitopes. Here, we present a systematic and comparative study of the HLA class I and II presented, nonmutant antigenome of multiple myeloma (MM). Quantification of HLA surface expression revealed elevated HLA molecule counts on malignant plasma cells compared with normal B cells, excluding relevant HLA downregulation in MM. Analyzing the presentation of established myeloma-associated T-cell antigens on the HLA ligandome level, we found a substantial proportion of antigens to be only infrequently presented on primary myelomas or to display suboptimal degrees of myeloma specificity. However, unsupervised analysis of our extensive HLA ligand data set delineated a panel of 58 highly specific myeloma-associated antigens (including multiple myeloma SET domain containing protein) which are characterized by frequent and exclusive presentation on myeloma samples. Functional characterization of these target antigens revealed peptide-specific, preexisting CD8(+) T-cell responses exclusively in myeloma patients, which is indicative of pathophysiological relevance. Furthermore, in vitro priming experiments revealed that peptide-specific T-cell responses can be induced in response-naive myeloma patients. Together, our results serve to guide antigen selection for T-cell-based immunotherapy of MM.

Biochemical large-scale identification of MHC class I ligands.

The large-scale identification of MHC class I presented peptides is indispensable for gaining insight into the fundamental rules of immune recognition as well as it is an invaluable tool in identifying potential targets for the immunotherapy of disease. In this chapter we briefly review the existing strategies for the analysis of MHC ligandomes and provide an in-depth protocol for the immunoaffinity purification of MHC class I presented peptides from primary tissues or cells.

The immunopeptidomic landscape of ovarian carcinomas

Significance Despite the revolution in cancer therapy initiated by checkpoint inhibitors, durable clinical responses remain sporadic in many types of cancer, including ovarian cancer. Understanding which antigens are essentially presented by tumor cells and further able to be recognized by T cells provides a major step toward novel effective targeted immunotherapies. In this study, we comprehensively analyzed the immunopeptidomic landscape of ovarian carcinoma and compared it to variety of benign sources to identify antigens exclusively presented on tumor cells. With personalized therapies moving into the focus of clinical cancer therapy, we further present insights on how gene-expression analysis and immunohistochemistry can support antigen selection for individualized immunotherapy. Immunotherapies, particularly checkpoint inhibitors, have set off a revolution in cancer therapy by releasing the power of the immune system. However, only little is known about the antigens that are essentially presented on cancer cells, capable of exposing them to immune cells. Large-scale HLA ligandome analysis has enabled us to exhaustively characterize the immunopeptidomic landscape of epithelial ovarian cancers (EOCs). Additional comparative profiling with the immunopeptidome of a variety of benign sources has unveiled a multitude of ovarian cancer antigens (MUC16, MSLN, LGALS1, IDO1, KLK10) to be presented by HLA class I and class II molecules exclusively on ovarian cancer cells. Most strikingly, ligands derived from mucin 16 and mesothelin, a molecular axis of prognostic importance in EOC, are prominent in a majority of patients. Differential gene-expression analysis has allowed us to confirm the relevance of these targets for EOC and further provided important insights into the relationship between gene transcript levels and HLA ligand presentation.

Personalized peptide vaccine-induced immune response associated with long-term survival of a metastatic cholangiocarcinoma patient

Graphical abstract

The SysteMHC Atlas project

Abstract Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

Antileukemia T-cell responses in CLL – We don't need no aberration

Effective antigen-specific cancer immunotherapy requires exact knowledge of tumor-associated epitopes that can act as rejection antigens. Although the current paradigm views mutation-derived neoantigens as the most promising targets, we have recently demonstrated that leukemia-specific T-cell responses associated with survival benefit in CLL patients target a panel of non-mutated tumor-associated antigens.

A natural tapasin isoform lacking exon 3 modifies peptide loading complex function

To assure efficient MHC class I (MHC‐I) peptide loading, the peptide loading complex (PLC) recruits the peptide‐receptive form of MHC‐I, and in this process, tapasin (tpn) connects MHC‐I with the peptide transporter TAP and forms a stable disulfide bond with ERp57. Here, we describe an alternatively spliced tpn transcript lacking exon 3, observed in cells infected with human cytomegalovirus. Recognition of exon 3 was regulated via G‐runs, suggesting that members of the hnRNP (heterogeneous nuclear ribonucleoprotein)‐family regulate expression of the ΔExon3 variant of tpn. Exon 3 includes Cys‐95, which is responsible for the disulfide bond formation with ERp57 and, consequently, interaction of the ΔExon3 variant with ERp57 was strongly impaired. Although the ΔExon3 variant specifically stabilized TAP expression but not MHC‐I in tpn‐deficient cells, in tpn‐proficient cells, the ΔExon3 tpn reduced cell surface expression of the tpn‐dependent HLA‐B*44:02 allele; the stability of the tpn‐independent HLA‐B*44:05 was not affected. Most importantly, detailed analysis of the PLC revealed a simultaneous binding of the ΔExon3 variant and tpn to TAP, suggesting modification of PLC functions. Indeed, an altered MHC‐I ligandome was observed in HeLa cells overexpressing the ΔExon3 variant, highlighting the potential of the alternatively spliced tpn variant to impact CD8+ T‐cell responses.