Applied immunoinformatics: HLA peptidome analysis for cancer immunotherapy

Despite different therapeutic approaches, cancer is one of the leading causes of death worldwide. Therefore, new therapies, like immunotherapy, are being developed to cure cancer. All immunotherapies have in common that they need targets to recognize malignant cells. Both the malignant and the benign immunopeptidome have to be examined, to define these new targets. We herein present a large immunopeptidome dataset of benign tissues containing multiple tissue types from different individuals. Moreover, we introduce the HLA Ligand Atlas, a web-interface we developed to accompany the data. It provides user-friendly access to the data, a fast, interactive search option which can be used to search for tissue specific HLA-peptides, and provides common statistics to the user. Using the large dataset of benign samples, we were able to define general properties of the immunopeptidome. First, we showed that a short time storage of the samples at 8 °C does not alter the immunopeptidome in terms of the number of found peptides and their quality. Next, we performed quality control, in which we found an altered immunopeptidome in the samples of stomach tissue, which might be caused by pepsin in the samples. In addition, we analyzed both the inter- and the intra-individual variability of the immunopeptidome on protein and peptide level. This analysis revealed that sample variability was better explained by HLA type than by tissue-specific peptide presentation. Finally, the large dataset of benign samples allows us to describe properties like the length distribution of different HLA alleles and the nestedness of the peptides in the two HLA classes. In the last part of this thesis, we show how targets can be defined using immunopeptidome data. In this case, we investigated four different hematological malignancies. We describe entity-dividing lines by using a unsupervised hierarchical clustering of allotype-specific peptides, which showed that entity-specific analysis is recommended. Nevertheless, we found "panleukemia"- antigens shared across all four hematological malignancies, which were cancer exclusive.Trotz verschiedenster therapeutischen Behandlungsmethoden ist Krebs noch immer eine der häufigsten Todesursachen weltweit. Deshalb werden weiterhin neue Therapieansätze, wie zum Beispiel Immunotherapie, entwickelt, um Krebs zu heilen. Zur Entwicklung von Immunotherapien gegen Tumorzellen werden Angriffsziele benötigt, anhand derer Krebszellen erkannt werden können. Zur Bestimmung dieser ist es notwendig sowohl das Immunopeptidom von Krebszellen als auch das von gesundem Gewebe zu kennen. Wir präsentieren einen großen Immunopeptidomdatensatz von gesundem Gewebe, der sowohl verschiedene Organtypen eines Individuums, als auch verschiedene Individuen beinhaltet. Wir haben ein Webinterface - den HLA Ligand Atlas - entwickelt, um einen benutzerfreundlichen Zugriff auf die Daten zu ermöglichen. Dieses Webinterface erlaubt eine schnelle interaktive Suche im Datensatz, wie die Suche nach organspezifischen HLA Peptiden, und stellt zusätzliche Statisken bereit. Des Weiteren erlaubt es die Darstellung der Massenspektrometriespektren in einem interaktivem Spektrumviewer. Mit Hilfe des großen Datensatz an Normalgewebe konnten wir allgemeine Eigenschaften des Immunpeptidom bestimmen. Zuerst zeigen wir, dass das Immunopeptidom sich sowohl quantitativ als auch qualitativ nicht ändert, wenn die Probe kurzzeitig bei 8 °C gelagert wird. Als nächsten führten wir eine Qualitätskontrolle durch, die ein verändertes Immunopeptidom bei den Proben des Magengewebes aufzeigte, welches möglicherweise durch Pepsin in den Proben verursacht wurde. Zusätzlich untersuchten wir die inter- und intra-individuelle Variabilität des Immunopeptidom auf Protein- und Peptideebene. Die Analyse zeigte hier, dass der HLA-Typ einen größeren Einfluss auf die Variablität hat als die organspezifische Präsentation. Der große Datensatz von Normalgewebe erlaubte uns auch die Beschreibung weiterer Eigenschaften, wie die Peptidlängenverteilung für verschieden HLA Allele und die Beschreibung von Längenvarianten in den zwei HLA Klassen. Im letzten Teil dieser Doktorarbeit zeigen wir wie neue Angriffsziele mit Hilfe von Immunopeptidomdaten gefunden werden können. In unserem Fall untersuchten wir vier verschieden hämatologische Krebsarten. Durch eine unüberwachte hierarchische Clusteranalyse auf allotypspezifischen Peptide wurden hier klare, entitätsspezifische Cluster identifiziert. Dieser Befund spricht für die Notwendigkeit einer entitätsspezifischen Anaylse solcher Datenätze. Nichtsdestotrotz konnten wir auf allen vier hämatologischen Krebsarten „Pan-leukemia“ Antigene finden, die krebsexklusiv sind

Distinct transcriptional changes in non-small cell lung cancer patients associated with multi-antigenic RNActive® CV9201 immunotherapy

ABSTRACT We recently completed a phase I/IIa trial of RNActive® CV9201, a novel mRNA-based therapeutic vaccine targeting five tumor-associated antigens in non-small cell lung cancer (NSCLC) patients. The aim of the study presented here was to comprehensively analyze changes in peripheral blood during the vaccination period and to generate hypotheses facilitating the identification of potential biomarkers correlating with differential clinical outcomes post RNActive® immunotherapy. We performed whole-genome expression profiling in a subgroup of 22 stage IV NSCLC patients before and after initiation of treatment with CV9201. Utilizing an analytic approach based on blood transcriptional modules (BTMs), a previously described, sensitive tool for blood transcriptome data analysis, patients segregated into two major clusters based on transcriptional changes post RNActive® treatment. The first group of patients was characterized by the upregulation of an expression signature associated with myeloid cells and inflammation, whereas the other group exhibited an expression signature associated with T and NK cells. Patients with an enrichment of T and NK cell modules after treatment compared to baseline exhibited significantly longer progression-free and overall survival compared to patients with an upregulation of myeloid cell and inflammatory modules. Notably, these gene expression signatures were mutually exclusive and inversely correlated. Furthermore, our findings correlated with phenotypic data derived by flow cytometry as well as the neutrophil-to-lymphocyte ratio. Our study thus demonstrates non-overlapping, distinct transcriptional profiles correlating with survival warranting further validation for the development of biomarker candidates for mRNA-based immunotherapy

HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy

BACKGROUND The human leucocyte antigen (HLA) complex controls adaptive immunity by presenting defined fractions of the intracellular and extracellular protein content to immune cells. Understanding the benign HLA ligand repertoire is a prerequisite to define safe T-cell-based immunotherapies against cancer. Due to the poor availability of benign tissues, if available, normal tissue adjacent to the tumor has been used as a benign surrogate when defining tumor-associated antigens. However, this comparison has proven to be insufficient and even resulted in lethal outcomes. In order to match the tumor immunopeptidome with an equivalent counterpart, we created the HLA Ligand Atlas, the first extensive collection of paired HLA-I and HLA-II immunopeptidomes from 227 benign human tissue samples. This dataset facilitates a balanced comparison between tumor and benign tissues on HLA ligand level. METHODS Human tissue samples were obtained from 16 subjects at autopsy, five thymus samples and two ovary samples originating from living donors. HLA ligands were isolated via immunoaffinity purification and analyzed in over 1200 liquid chromatography mass spectrometry runs. Experimentally and computationally reproducible protocols were employed for data acquisition and processing. RESULTS The initial release covers 51 HLA-I and 86 HLA-II allotypes presenting 90,428 HLA-I- and 142,625 HLA-II ligands. The HLA allotypes are representative for the world population. We observe that immunopeptidomes differ considerably between tissues and individuals on source protein and HLA-ligand level. Moreover, we discover 1407 HLA-I ligands from non-canonical genomic regions. Such peptides were previously described in tumors, peripheral blood mononuclear cells (PBMCs), healthy lung tissues and cell lines. In a case study in glioblastoma, we show that potential on-target off-tumor adverse events in immunotherapy can be avoided by comparing tumor immunopeptidomes to the provided multi-tissue reference. CONCLUSION Given that T-cell-based immunotherapies, such as CAR-T cells, affinity-enhanced T cell transfer, cancer vaccines and immune checkpoint inhibition, have significant side effects, the HLA Ligand Atlas is the first step toward defining tumor-associated targets with an improved safety profile. The resource provides insights into basic and applied immune-associated questions in the context of cancer immunotherapy, infection, transplantation, allergy and autoimmunity. It is publicly available and can be browsed in an easy-to-use web interface at https://hla-ligand-atlas.org

First-in-Human Dose Escalation Trial To Evaluate the Clinical Safety and Efficacy of an Anti-MAGEA1 Autologous Tcr-Transgenic T Cell Therapy in Relapsed and Refractory Solid Tumors

RATIONALE OF THE TRIAL: Although the use of engineered T cells in cancer immunotherapy has greatly advanced the treatment of hematological malignancies, reaching meaningful clinical responses in the treatment of solid tumors is still challenging. We investigated the safety and tolerability of IMA202 in a first-in-human, dose escalation basket trial in human leucocyte antigen A*02:01 positive patients with melanoma-associated antigen A1 (MAGEA1)-positive advanced solid tumors. TRIAL DESIGN: The 2+2 trial design was an algorithmic design based on a maximally acceptable dose-limiting toxicity (DLT) rate of 25% and the sample size was driven by the algorithmic design with a maximum of 16 patients. IMA202 consists of autologous genetically modified cytotoxic CD8 CONCLUSION: In conclusion, IMA202 had a manageable safety profile, and it was associated with biological and potential clinical activity of MAGEA1-targeting genetically engineered TCR-T cells in a poor prognosis, multi-indication solid tumor cohort

ToxDBScan: Large-Scale Similarity Screening of Toxicological Databases for Drug Candidates

We present a new tool for hepatocarcinogenicity evaluation of drug candidates in rodents. ToxDBScan is a web tool offering quick and easy similarity screening of new drug candidates against two large-scale public databases, which contain expression profiles for substances with known carcinogenic profiles: TG-GATEs and DrugMatrix. ToxDBScan uses a set similarity score that computes the putative similarity based on similar expression of genes to identify chemicals with similar genotoxic and hepatocarcinogenic potential. We propose using a discretized representation of expression profiles, which use only information on up- or down-regulation of genes as relevant features. Therefore, only the deregulated genes are required as input. ToxDBScan provides an extensive report on similar compounds, which includes additional information on compounds, differential genes and pathway enrichments. We evaluated ToxDBScan with expression data from 15 chemicals with known hepatocarcinogenic potential and observed a sensitivity of 88 Based on the identified chemicals, we achieved perfect classification of the independent test set. ToxDBScan is publicly available from the ZBIT Bioinformatics Toolbox

Unveiling the Peptide Motifs of HLA-C and HLA-G from Naturally Presented Peptides and Generation of Binding Prediction Matrices

Abstract The classical HLA-C and the nonclassical HLA-E and HLA-G molecules play important roles both in the innate and adaptive immune system. Starting already during embryogenesis and continuing throughout our lives, these three Ags exert major functions in immune tolerance, defense against infections, and anticancer immune responses. Despite these important roles, identification and characterization of the peptides presented by these molecules has been lacking behind the more abundant HLA-A and HLA-B gene products. In this study, we elucidated the peptide specificities of these HLA molecules using a comprehensive analysis of naturally presented peptides. To that end, the 15 most frequently expressed HLA-C alleles as well as HLA-E*01:01 and HLA-G*01:01 were transfected into lymphoblastoid C1R cells expressing low endogenous HLA. Identification of naturally presented peptides was performed by immunoprecipitation of HLA and subsequent analysis of HLA-bound peptides by liquid chromatographic tandem mass spectrometry. Peptide motifs of HLA-C unveil anchors in position 2 or 3 with high variances between allotypes, and a less variable anchor at the C-terminal end. The previously reported small ligand repertoire of HLA-E was confirmed within our analysis, and we could show that HLA-G combines a large ligand repertoire with distinct features anchoring peptides at positions 3 and 9, supported by an auxiliary anchor in position 1 and preferred residues in positions 2 and 7. The wealth of HLA ligands resulted in prediction matrices for octa-, nona-, and decamers. Matrices were validated in terms of their binding prediction and compared with the latest NetMHC prediction algorithm NetMHCpan-3.0, which demonstrated their predictive power.</jats:p

HLA Ligandome Analysis of Primary Chronic Lymphocytic Leukemia (CLL) Cells Under In Vitro Lenalidomide Treatment Confirms Lenalidomide as a Suitable Combination Partner for T-Cell Based Immunotherapy

Abstract Several studies have proven the positive immunomodulatory effect of lenalidomide, a second-generation derivative of thalidomide, on T-cell responses in CLL, in particular regarding the repair of the immune synapse between CLL and T cells (e.g., Ramsay et al. J Clin Invest 2008), as well as the upregulation of costimulatory molecules on CLL cells (e.g., Aue et al. Haematologica 2009). Therefore, lenalidomide seems to be a promising combination partner for T-cell based immunotherapy approaches in CLL patients. We recently conducted a study which directly characterized the antigenic landscape of CLL by mass spectrometric analysis of naturally presented HLA ligands and identified a panel of CLL-specific CD4+ as well as CD8+ T-cell epitopes as suitable targets for T-cell based immunotherapy (Kowalewski et al. PNAS2015). As anti-cancer drugs can have marked effects on the HLA ligandome of tumor cells, it is of great importance to thoroughly characterize and take into account the effects of the immune modulator lenalidomide not only on the effector cells, but also on the antigenic landscape of the target cells. Here we present a mass spectrometry-based study which longitudinally maps the HLA-presented immunopeptidome and in particular the CLL-associated antigens of primary CLL cells under in vitro lenalidomide treatment. We quantified HLA surface expression on primary CLL cells and autologous B cells (n=4) at t0, t24h and t48h after incubation with 0.5 µM lenalidomide. With regard to HLA class I expression on CD19+CD5+ CLL cells, no significant impact of lenalidomide was observed (fold-change 0.92-1.02, t48h), whereas a slight but also not significant increase of HLA class II molecules after treatment was detectable (fold-change 1.25-1.43, t48h) with absolute molecule counts ranging from 40,000-125,000 class I and 30,000-200,000 class II molecules/cell. Furthermore, we could show that CD19+CD5+ CLL cells (n=4) showed a significantly increased expression of HLA class I molecules compared to normal CD19+CD5-B cells. Implementing label-free quantification, we then assessed HLA class I ligand presentation during in vitro lenalidomide incubation. We observed a higher plasticity of the HLA ligandome over time compared to treatment with lenalidomide. 2.5±3.0% of HLA class I ligands showed significant modulation (fold change ≥4, p≤0.01) after 24h of mock treatment, whereas only 0.9±1.2% of the ligands were modulated upon lenalidomide treatment. At t48hsimilar proportions of modulation were observed with 4.0±1.7% of HLA ligands significantly altered in their abundance over time (mock control), while lenalidomide treatment only resulted in 0.9±1.2% modulated ligands. Out of the 6,991 different HLA class I ligands representing 3,983 source proteins identified on primary CLL cells (n=3) by mass spectrometry, we were able to detect 36 (30.5%) of the HLA-matched CLL-associated epitopes described in previous studies on these three samples. Importantly, these CLL-associated antigens showed robust presentation on CLL cells under in vitro lenalidomide treatment. In order to investigate the impact of lenalidomide-treatment on HLA class I allotype distribution within the ligandome, we analyzed the overall frequencies of HLA allotype restrictions of ligands on treated versus untreated primary CLL cells. Thereby, no changes in the HLA allotype distribution were observed. Analysis of the HLA class II ligandome of primary CLL cells (n=3) revealed a total of 12,026 unique peptides representing 2,333 source proteins. We were able to detect 133 (28.5%) of CLL-associated class II epitopes described in previous studies. Notably, most of the CLL-associated antigens showed robust presentation under lenalidomide therapy. Exemplarily for one patient, we identified 7/66 (10.6%) CLL-associated antigens modulated after 24 h of in vitro lenalidomide treatment, but 10/66 (15.2%) antigens altered over time (mock control). Taken together our study provides direct insights into the impact of lenalidomide on the HLA ligandome of primary CLL cells. We were able to show that in vitro lenalidomide has no relevant influence on, and rather seems to stabilize the HLA-presented immunopeptidome of primary CLL cells. Importantly, CLL-associated epitopes are stably presented under lenalidomide treatment. Therefore, lenalidomide appears to be an ideal combination partner for T-cell based immunotherapy in CLL patients. Disclosures Kowalewski: Immatics Biotechnologies GmbH: Employment. Schuster:Immatics Biotechnologies GmbH: Employment. </jats:sec

Abstract A112: Mapping the impact of proteasome inhibitor therapy on the antigenic landscape of multiple myeloma: Identifying robust targets for T cell immunotherapy

Abstract Recent studies underscore that multiple myeloma is an immunogenic disease and suggest that it can be effectively treated by T cell based immunotherapy via immunomodulation. Unspecific immune checkpoint inhibition might be synergistically complemented by therapeutic vaccination, which may help induce and guide specific anti-cancer T cell responses. We have recently conducted a study which directly characterized the antigenic landscape of myeloma by mass spectrometric analysis of naturally presented HLA ligands and identified a panel of T cell epitopes characterized by exquisite myeloma-specificity. As novel immunotherapeutic interventions will have to be implemented as 2nd line treatments, it is of great importance to thoroughly characterize and take into account the effects of previous therapies on the antigenic landscape of target cells. Here we present a longitudinal study of the HLA-presented immunopeptidome of myeloma cells under treatment with the 2nd generation proteasome inhibitor carfilzomib. We characterize and quantify the plasticity of the antigenic landscape and identify targets characterized by robust presentation. We quantified HLA surface expression on 4 human myeloma cell lines (MM.1s, U266, RPMI8226 &amp; JJN3) at t0, t24h and t48h after incubation with carfilzomib. Strikingly, we detected elevated levels of HLA class I post treatment for 3/4 cell lines, with absolute molecule counts ranging from 50,000-400,000 molecules/cell. Out of the &amp;gt;5,000 different HLA ligands we could identify on MM.1s and U266 by mass spectrometry, we were able to detect and longitudinally quantify 38 and 54 myeloma-associated epitopes described in previous studies, respectively. Importantly, the vast majority of these antigens (88.2%) showed robust presentation on myeloma cells under therapy. Around 12% of HLA ligands showed significant changes in abundance after carfilzomib treatment. Strikingly, we observed a significant reduction in aromatic residues at the C-terminal anchor position, which directly reflects the mechanism of action of carfilzomib on the HLA ligand level. Our study provides direct insights into the plasticity of T cell antigen presentation on myeloma cells in a model of proteasome inhibitor therapy. We were able to characterize general changes in the immunopeptidome composition and identify robustly presented myeloma-associated epitopes. Our findings may help guide future clinical trials for 2nd line T cell immunotherapy of multiple myeloma. Citation Format: Daniel J. Kowalewski, Simon Walz, Linus Backert, Heiko Schuster, Oliver Kohlbacher, Lothar Kanz, Helmut R. Salih, Hans-Georg Rammensee, Stefan Stevanovic, Juliane S. Stickel. Mapping the impact of proteasome inhibitor therapy on the antigenic landscape of multiple myeloma: Identifying robust targets for T cell immunotherapy. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A112.</jats:p