Large-scale detection of antigen-specific T cells using peptide-MHC-I multimers labeled with DNA barcodes

The immunocytokine L19-IL2: An interplay between radiotherapy and long-lasting systemic anti-tumour immune responses

Recently, we have shown that the administration of the tumour-targeted antibody-based immunocytokine L19-IL2 after radiotherapy (RT) resulted in synergistic anti-tumour effect. Here we show that RT and L19-IL2 can activate a curative abscopal effect, with a long-lasting immunological memory. Ionizing radiation (single dose of 15Gy, 5 × 2Gy or 5 × 5Gy) was delivered to primary C51 colon tumour-bearing immunocompetent mice in combination with L19-IL2 and response of secondary non-irradiated C51 or CT26 colon tumours was evaluated. 15Gy + L19-IL2 triggered a curative (20%) abscopal effect, which was T cell dependent. Moreover, 10Gy + L19-IL2 treated and cured mice were re-injected after 150 days with C51 tumour cells and tumour uptake was assessed. Age-matched controls (matrigel injected mice treated with 10Gy + L19-IL2, mice cured after treatment with surgery + L19-IL2 and mice cured after high dose RT 40Gy + vehicle) were included. Several immunological parameters in blood, tumours, lymph nodes and spleens were investigated. Treatment with 10Gy + L19-IL2 resulted in long-lasting immunological memory, associated with CD44⁺CD127⁺ expression on circulating T cells. This combination treatment can induce long-lasting curative abscopal responses, and therefore it has also great potential for treatment of metastatic disease. Preclinical findings have led to the initiation of a phase I clinical trial (NCT02086721) in our institute investigating stereotactic ablative radiotherapy with L19-IL2 in patients with oligometastatic solid tumours.

Neoantigen Targeting-Dawn of a New Era in Cancer Immunotherapy?

During their development and progression tumors acquire numerous mutations that, when translated into proteins give rise to neoantigens that can be recognized by T cells. Initially, neoantigens were not recognized as preferred targets for cancer immunotherapy due to their enormous diversity and the therefore limited options to develop “one fits all” pharmacologic solutions. In recent years, the experience obtained in clinical trials demonstrating a predictive role of neoantigens in checkpoint inhibition has changed our view on the clinical potential of neoantigens in cancer immunotherapy. Technological advances such as sequencing of whole cancer genomes, the development of reliable algorithms for epitope prediction, and an increasing number of immunotherapeutic options now facilitate the development of personalized tumor therapies directly targeting a patient’s neoantigenic burden. Preclinical studies in mice that support the excellent therapeutic potential of neoantigen-directed immunotherapies have provided blueprints on how this methodology can be translated into clinical applications in humans. Consistently, very recent clinical studies on personalized vaccinations targeting in silico predicted neoepitopes shed a first light on the therapeutic potential of personalized, neoantigen-directed immunotherapies. In our review, we discuss the various subtypes of tumor antigens with a focus on neoantigens and their potential in cancer immunotherapy. We will describe the current methods and techniques of detection as well as the structural requirements for neoantigens that are needed for their recognition by T cells and for tumor destruction. To assess the clinical potential of neoantigens, we will discuss their occurrence and functional relevance in spontaneous and hereditary cancers and their prognostic and predictive value. We will present in detail the existing immunotherapeutic options that exploit the neoantigen burden of tumors encompassing both preclinical efforts that provided convincing technological proof-of-concept and the current clinical studies confirming the potential of neoantigen-directed immunotherapies.

The Potential of Donor T-Cell Repertoires in Neoantigen-Targeted Cancer Immunotherapy

T cells can recognize peptides encoded by mutated genes, but analysis of tumor-infiltrating lymphocytes suggests that very few neoantigens spontaneously elicit T-cell responses. This may be an important reason why immune checkpoint inhibitors are mainly effective in tumors with a high mutational burden. Reasons for clinically insufficient responses to neoantigens might be inefficient priming, inhibition, or deletion of the cognate T cells. Responses can be dramatically improved by cancer immunotherapy such as checkpoint inhibition, but often with temporary effects. By contrast, T cells from human leukocyte antigen (HLA)-matched donors can cure diseases such as chronic myeloid leukemia. The therapeutic effect is mediated by donor T cells recognizing polymorphic peptides for which the donor and patient are disparate, presented on self-HLA. Donor T-cell repertoires are unbiased by the immunosuppressive environment of the tumor. A recent study demonstrated that T cells from healthy individuals are able to respond to neoantigens that are ignored by tumor-infiltrating T cells of melanoma patients. In this review, we discuss possible reasons why neoantigens escape host T cells and how these limitations may be overcome by utilization of donor-derived T-cell repertoires to facilitate rational design of neoantigen-targeted immunotherapy.

Immuno-oncology from the perspective of somatic evolution

The past years have witnessed significant success for cancer immunotherapies that activate a patient's immune system against their cancer cells. At the same time our understanding of the genetic changes driving tumor evolution have progressed dramatically. The study of cancer genomes has shown that tumors are best understood as cell populations governed by the rules of evolution, leading to the emergence and spread of cell lineages with pathogenic mutations. Moreover, somatic evolution can explain the acquisition of mutations conferring drug resistance in the ever-lasting battle for reaching even fitter cell states. Here, we review the current state of the art of somatic cancer evolution and mechanisms of immune control and escape. We also revisit the principles of immunotherapy from the perspective of somatic evolution and discuss the basic rules of resistance to immunotherapies as dictated by evolution.

Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis

CD4+ T cells have been long known to play an important role in the pathogenesis of rheumatoid arthritis (RA), but the specific cell populations and states that drive the disease have been challenging to identify with low dimensional single cell data and bulk assays. The advent of high dimensional single cell technologies-like single cell RNA-seq or mass cytometry-has offered promise to defining key populations, but brings new methodological and statistical challenges. Recent single cell profiling studies have revealed a broad diversity of cell types among CD4+ T cells, identifying novel populations that are expanded or altered in RA. Here, we will review recent findings on CD4+ T cell heterogeneity and RA that have come from single cell profiling studies and discuss the best practices for conducting these studies.

Informatics for cancer immunotherapy

The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.

Preclinical and clinical development of neoantigen vaccines

Cancer neoantigens are antigens that result from somatic mutations present in individual cancers. Neoantigens are considered important targets for cancer immunotherapy because of their immunogenicity and lack of expression in normal tissues. Next-generation sequencing technologies and computational analysis have recently made neoantigen discovery possible. Although neoantigens are important targets of checkpoint blockade therapy, neoantigen vaccines are currently being investigated in preclinical models and early-phase human clinical trials. Preliminary results from these clinical trials demonstrate that dendritic cell, synthetic long peptide, and RNA-based neoantigen vaccines are safe, and capable of inducing both CD8+ and CD4+ neoantigen-specific T-cell responses. We and others are testing neoantigen vaccines in melanoma, breast cancer, non-small-cell lung cancer and other cancer types. Since cancers have evolved mechanisms to escape immune control, it is particularly important to study the efficacy of neoantigen vaccines in combination with other immunotherapies including checkpoint blockade therapy, and immune therapies targeting the immunosuppressive tumor microenvironment.

Identification and Characterization of Neoantigens As Well As Respective Immune Responses in Cancer Patients

Cancer immunotherapy has recently emerged as a powerful tool for the treatment of diverse advanced malignancies. In particular, therapeutic application of immune checkpoint modulators, such as anti-CTLA4 or anti-PD-1/PD-L1 antibodies, have shown efficacy in a broad range of malignant diseases. Although pharmacodynamics of these immune modulators are complex, recent studies strongly support the notion that altered peptide ligands presented on tumor cells representing neoantigens may play an essential role in tumor rejection by T cells activated by anti-CTLA4 and anti-PD-1 antibodies. Neoantigens may have diverse sources as viral and mutated proteins. Moreover, posttranslational modifications and altered antigen processing may also contribute to the neoantigenic peptide ligand landscape. Different approaches of target identification are currently applied in combination with subsequent characterization of autologous and non-self T-cell responses against such neoantigens. Additional efforts are required to elucidate key characteristics and interdependences of neoantigens, immunodominance, respective T-cell responses, and the tumor microenvironment in order to define decisive determinants involved in effective T-cell-mediated tumor rejection. This review focuses on our current knowledge of identification and characterization of such neoantigens as well as respective T-cell responses. It closes with challenges to be addressed in future relevant for further improvement of immunotherapeutic strategies in malignant diseases.

Future perspectives in melanoma research "Melanoma Bridge", Napoli, November 30th-3rd December 2016

Major advances have been made in the treatment of cancer with targeted therapy and immunotherapy; several FDA-approved agents with associated improvement of 1-year survival rates became available for stage IV melanoma patients. Before 2010, the 1-year survival were quite low, at 30%; in 2011, the rise to nearly 50% in the setting of treatment with Ipilimumab, and rise to 70% with BRAF inhibitor monotherapy in 2013 was observed. Even more impressive are 1-year survival rates considering combination strategies with both targeted therapy and immunotherapy, now exceeding 80%. Can we improve response rates even further, and bring these therapies to more patients? In fact, despite these advances, responses are heterogeneous and are not always durable. There is a critical need to better understand who will benefit from therapy, as well as proper timing, sequence and combination of different therapeutic agents. How can we better understand responses to therapy and optimize treatment regimens? The key to better understanding therapy and to optimizing responses is with insights gained from responses to targeted therapy and immunotherapy through translational research in human samples. Combination therapies including chemotherapy, radiotherapy, targeted therapy, electrochemotherapy with immunotherapy agents such as Immune Checkpoint Blockers are under investigation but there is much room for improvement. Adoptive T cell therapy including tumor infiltrating lymphocytes and chimeric antigen receptor modified T cells therapy is also efficacious in metastatic melanoma and outcome enhancement seem likely by improved homing capacity of chemokine receptor transduced T cells. Tumor infiltrating lymphocytes therapy is also efficacious in metastatic melanoma and outcome enhancement seem likely by improved homing capacity of chemokine receptor transduced T cells. Understanding the mechanisms behind the development of acquired resistance and tests for biomarkers for treatment decisions are also under study and will offer new opportunities for more efficient combination therapies. Knowledge of immunologic features of the tumor microenvironment associated with response and resistance will improve the identification of patients who will derive the most benefit from monotherapy and might reveal additional immunologic determinants that could be targeted in combination with checkpoint blockade. The future of advanced melanoma needs to involve education and trials, biobanks with a focus on primary tumors, bioinformatics and empowerment of patients and clinicians.

An Analysis of Natural T Cell Responses to Predicted Tumor Neoepitopes

Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen) combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96%) shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.

Evolving Approaches in the Identification of Allograft-Reactive T and B Cells in Mice and Humans

Whether a transplanted allograft is stably accepted, rejected, or achieves immunological tolerance is dependent on the frequency and function of alloreactive lymphocytes, making the identification and analysis of alloreactive T and B cells in transplant recipients critical for understanding mechanisms, and the prediction of allograft outcome. In animal models, tracking the fate of graft-reactive T and B cells allows investigators to uncover their biology and develop new therapeutic strategies to protect the graft. In the clinic, identification and quantification of graft-reactive T and B cells allows for the early diagnosis of immune reactivity and therapeutic intervention to prevent graft loss. In addition to rejection, probing of T and B cell fate in vivo provides insights into the underlying mechanisms of alloimmunity or tolerance that may lead to biomarkers predicting graft fate. In this review, we discuss existing and developing approaches to track and analyze alloreactive T and B cells in mice and humans and provide examples of discoveries made utilizing these techniques. These approaches include mixed lymphocyte reactions, trans-vivo delayed-type hypersensitivity, enzyme-linked immunospot assays, the use of antigen receptor transgenic lymphocytes, and utilization of peptide-major histocompatibility multimers, along with imaging techniques for static multiparameter analysis or dynamic in vivo tracking. Such approaches have already refined our understanding of the alloimmune response and are pointing to new ways to improve allograft outcomes in the clinic.

Host genotype and time dependent antigen presentation of viral peptides: predictions from theory

The rate of progression of HIV infected individuals to AIDS is known to vary with the genotype of the host, and is linked to their allele of human leukocyte antigen (HLA) proteins, which present protein degradation products at the cell surface to circulating T-cells. HLA alleles are associated with Gag-specific T-cell responses that are protective against progression of the disease. While Pol is the most conserved HIV sequence, its association with immune control is not as strong. To gain a more thorough quantitative understanding of the factors that contribute to immunodominance, we have constructed a model of the recognition of HIV infection by the MHC class I pathway. Our model predicts surface presentation of HIV peptides over time, demonstrates the importance of viral protein kinetics, and provides evidence of the importance of Gag peptides in the long-term control of HIV infection. Furthermore, short-term dynamics are also predicted, with simulation of virion-derived peptides suggesting that efficient processing of Gag can lead to a 50% probability of presentation within 3 hours post-infection, as observed experimentally. In conjunction with epitope prediction algorithms, this modelling approach could be used to refine experimental targets for potential T-cell vaccines, both for HIV and other viruses.

'Hotspots' of Antigen Presentation Revealed by Human Leukocyte Antigen Ligandomics for Neoantigen Prioritization

The remarkable clinical efficacy of the immune checkpoint blockade therapies has motivated researchers to discover immunogenic epitopes and exploit them for personalized vaccines. Human leukocyte antigen (HLA)-binding peptides derived from processing and presentation of mutated proteins are one of the leading targets for T-cell recognition of cancer cells. Currently, most studies attempt to identify neoantigens based on predicted affinity to HLA molecules, but the performance of such prediction algorithms is rather poor for rare HLA class I alleles and for HLA class II. Direct identification of neoantigens by mass spectrometry (MS) is becoming feasible; however, it is not yet applicable to most patients and lacks sensitivity. In an attempt to capitalize on existing immunopeptidomics data and extract information that could complement HLA-binding prediction, we first compiled a large HLA class I and class II immunopeptidomics database across dozens of cell types and HLA allotypes and detected hotspots that are subsequences of proteins frequently presented. About 3% of the peptidome was detected in both class I and class II. Based on the gene ontology of their source proteins and the peptide's length, we propose that their processing may partake by the cellular class II presentation machinery. Our database captures the global nature of the in vivo peptidome averaged over many HLA alleles, and therefore, reflects the propensity of peptides to be presented on HLA complexes, which is complementary to the existing neoantigen prediction features such as binding affinity and stability or RNA abundance. We further introduce two immunopeptidomics MS-based features to guide prioritization of neoantigens: the number of peptides matching a protein in our database and the overlap of the predicted wild-type peptide with other peptides in our database. We show as a proof of concept that our immunopeptidomics MS-based features improved neoantigen prioritization by up to 50%. Overall, our work shows that, in addition to providing huge training data to improve the HLA binding prediction, immunopeptidomics also captures other aspects of the natural in vivo presentation that significantly improve prediction of clinically relevant neoantigens.

Identification and correction of spatial bias are essential for obtaining quality data in high-throughput screening technologies

Spatial bias continues to be a major challenge in high-throughput screening technologies. Its successful detection and elimination are critical for identifying the most promising drug candidates. Here, we examine experimental small molecule assays from the popular ChemBank database and show that screening data are widely affected by both assay-specific and plate-specific spatial biases. Importantly, the bias affecting screening data can fit an additive or multiplicative model. We show that the use of appropriate statistical methods is essential for improving the quality of experimental screening data. The presented methodology can be recommended for the analysis of current and next-generation screening data.

The Potential and Challenges of Exploiting the Vast But Dynamic Neoepitope Landscape for Immunotherapy

Somatic non-synonymous mutations in the DNA of tumor cells may result in the presentation of tumor-specific peptides to T cells. The recognition of these so-called neoepitopes now has been firmly linked to the clinical success of checkpoint blockade and adoptive T cell therapy. Following proof-of-principle studies in preclinical models there was a surge of strategies to identify and exploit genetically defined clonally expressed neoepitopes. These approaches assume that neoepitope availability remains stable during tumor progression but tumor genetics has taught us otherwise. Under the pressure of the immune system, neoepitope expression dynamically evolves rendering neoepitope specific T cells ineffective. This implies that the immunotherapeutic strategy applied should be flexible in order to cope with these changes and/or aiming at a broad range of epitopes to prevent the development of escape variants. Here, we will address the heterogeneous and dynamic expression of neoepitopes and describe our perspective and demonstrate possibilities how to further exploit the clinical potential of the neoepitope repertoire.

MuPeXI: prediction of neo-epitopes from tumor sequencing data

Personalization of immunotherapies such as cancer vaccines and adoptive T cell therapy depends on identification of patient-specific neo-epitopes that can be specifically targeted. MuPeXI, the mutant peptide extractor and informer, is a program to identify tumor-specific peptides and assess their potential to be neo-epitopes. The program input is a file with somatic mutation calls, a list of HLA types, and optionally a gene expression profile. The output is a table with all tumor-specific peptides derived from nucleotide substitutions, insertions, and deletions, along with comprehensive annotation, including HLA binding and similarity to normal peptides. The peptides are sorted according to a priority score which is intended to roughly predict immunogenicity. We applied MuPeXI to three tumors for which predicted MHC-binding peptides had been screened for T cell reactivity, and found that MuPeXI was able to prioritize immunogenic peptides with an area under the curve of 0.63. Compared to other available tools, MuPeXI provides more information and is easier to use. MuPeXI is available as stand-alone software and as a web server at http://www.cbs.dtu.dk/services/MuPeXI .

Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity

The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for in silico predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal distant modulation of the binding specificity at P2 for some HLA-I alleles by residues in the HLA-I binding site but outside of the B-pocket and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and in vitro binding assays.

Predicting the differences between cancer and normal cells that are visible to the immune system is of central importance for cancer immunotherapy. Here we introduce a novel computational framework to harness the wealth of data from in-depth HLA peptidomics studies, including ten novel high quality (<1% FDR) datasets generated for this work, to improve predictions of peptides displayed on HLA-I molecules. These high-throughput and unbiased data enable us to refine models of HLA-I binding specificity for many alleles (including some that had no ligand until this study) and improve predictions of neo-antigens from exome sequencing data in melanoma and lung cancer samples. Moreover, the refined description of HLA-I binding specificity reveals cases of allosteric modulation of HLA-I binding specificity at the second amino acid position (P2) of their ligands by residues that are part of the HLA-I binding site but outside of the B pocket.

Non-Invasive Monitoring of CNS MHC-I Molecules in Ischemic Stroke Mice

Ischemic stroke is one of the leading causes of morbidity and mortality worldwide. The expression of major histocompatibility complex class I (MHC-I) molecules in the central nervous system, which are silenced under normal physiological conditions, have been reported to be induced by injury stimulation. The purpose of this study was to determine whether MHC-I molecules could serve as molecular targets for the acute phase of ischemic stroke and to assess whether a high-affinity peptide specific for MHC-I molecules could be applied in the near-infrared imaging of cerebral ischemic mice. Quantitative real-time PCR and Western blotting were used to detect the expression of MHC-I molecules in two mouse models of cerebral ischemic stroke and an in vitro model of ischemia. The NetMHC 4.0 server was used to screen a high-affinity peptide specific for mouse MHC-I molecules. The Rosetta program was used to identify the specificity and affinity of the screened peptide (histocompatibility-2 binding peptide, H2BP). The results demonstrated that MHC-I molecules could serve as molecular targets for the acute phase of ischemic stroke. Cy5.5-H2BP molecular probes could be applied in the near-infrared imaging of cerebral ischemic mice. Research on the expression of MHC-I molecules in the acute phase after ischemia and MHC-I-targeted imaging may not only be helpful for understanding the mechanism of ischemic and hypoxic brain injury and repair but also has potential application value in the imaging of ischemic stroke.

Identification of Immunogenic Epitopes by MS/MS

The interrogation of cell surface-presented immunogenic epitopes is of great importance to differentiate diseased cells in consequence to malignant transformation or viral infections. On the basis of this knowledge, next-generation immunotherapies against cancers, autoimmunity, or infectious diseases can be developed. The identification of altered peptide repertoires of transformed cells renders mass spectrometry-based analysis indispensable. This is evident considering the low correlation of gene or protein expression alterations, respectively, with changes in the peptide repertoire rendering those analyses less informative. Nevertheless, immunogenicity of peptides appearing to be exclusively found on diseased cells has to be finally proven in T cell-based assays. This review highlights the capabilities and limitations of mass spectrometry in the identification of entire immunopeptidomes, as well as individual potential immunogenic epitopes with a strong focus on cancer. Furthermore, an overview of state-of-the-art immunogenicity screens is presented.

Combining radiotherapy with immunotherapy: the past, the present and the future

The advent of immunotherapy is currently revolutionizing the field of oncology, where different drugs are used to stimulate different steps in a failing cancer immune response chain. This review gives a basic overview of the immune response against cancer, as well as the historical and current evidence on the interaction of radiotherapy with the immune system and the different forms of immunotherapy. Furthermore the review elaborates on the many open questions on how to exploit this interaction to the full extent in clinical practice.

Immunotherapy for the treatment of breast cancer

INTRODUCTION

Breast cancer is the most common cancer as well as the first cause of death by cancer in women worldwide. Although routine treatment improves the outcome of early stage breast cancer patients, there is no effective therapy for the disseminated disease. Immunotherapy has emerged as a powerful therapeutic strategy for the treatment of many cancers. Although traditionally conceived as a non-immunogenic tumor, breast cancer is now considered a potential target for immunotherapy. Areas covered: In this review, the authors discuss different immunotherapeutic strategies that are currently being tested for the treatment of breast cancer: These strategies include: (i) blockade of immunological checkpoints, (ii) antitumor vaccines, (iii) regulatory T cell blockade, (iv) adoptive T cell transfer therapy, (iv) adoptive immunotherapy with monoclonal antibodies, and (v) combination of immunotherapy with chemotherapy. Expert opinion: A growing body of evidence indicates that immunotherapeutic strategies can benefit a larger cohort of breast cancer patients than hitherto anticipated. Since breast tumors entail multiple mechanisms to impair antitumor immunity, the immunological characterization of individual tumors and the selection of suitable combinations of chemotherapeutic and immunotherapeutic approaches are required to achieve significant clinical benefit in these patients.

Evolution of MHC-based technologies used for detection of antigen-responsive T cells

T cell-mediated recognition of peptide-major histocompatibility complex (pMHC) class I and II molecules is crucial for the control of intracellular pathogens and cancer, as well as for stimulation and maintenance of efficient cytotoxic responses. Such interactions may also play a role in the development of autoimmune diseases. Novel insights into this mechanism are crucial to understanding disease development and establishing new treatment strategies. MHC multimers have been used for detection of antigen-responsive T cells since the first report by Altman et al. showed that tetramerization of pMHC class I molecules provided sufficient stability to T cell receptor (TCR)-pMHC interactions, allowing detection of MHC multimer-binding T cells using flow cytometry. Since this breakthrough the scientific community has aimed for expanding the capacity of MHC multimer-based detection technologies to facilitate large-scale epitope discovery and immune monitoring in limited biological material. Screening of T cell specificity using large libraries of pMHC molecules is suitable for analyses of T cell recognition potentially at genome-wide levels rather than analyses restricted to a selection of model antigens. Such strategies provide novel insights into the immune specificities involved in disease development and response to immunotherapy, and extend fundamental knowledge related to T cell recognition patterns and cross-recognition by TCRs. MHC multimer-based technologies have now evolved from detection of 1-2 different T cell specificities per cell sample, to include more than 1000 evaluable pMHC molecules using novel technologies. Here, we provide an overview of MHC multimer-based detection technologies developed over two decades, focusing primarily on MHC class I interactions.

Systematic evaluation of immune regulation and modulation

Cancer immunotherapies are showing promising clinical results in a variety of malignancies. Monitoring the immune as well as the tumor response following these therapies has led to significant advancements in the field. Moreover, the identification and assessment of both predictive and prognostic biomarkers has become a key component to advancing these therapies. Thus, it is critical to develop systematic approaches to monitor the immune response and to interpret the data obtained from these assays. In order to address these issues and make recommendations to the field, the Society for Immunotherapy of Cancer reconvened the Immune Biomarkers Task Force. As a part of this Task Force, Working Group 3 (WG3) consisting of multidisciplinary experts from industry, academia, and government focused on the systematic assessment of immune regulation and modulation. In this review, the tumor microenvironment, microbiome, bone marrow, and adoptively transferred T cells will be used as examples to discuss the type and timing of sample collection. In addition, potential types of measurements, assays, and analyses will be discussed for each sample. Specifically, these recommendations will focus on the unique collection and assay requirements for the analysis of various samples as well as the high-throughput assays to evaluate potential biomarkers.

T cell receptor repertoire usage in cancer as a surrogate marker for immune responses

Characterizing the interaction of cancer cells with the host adaptive immune system is critical for understanding tumor immunology and the modus operandi of immunotherapeutic interventions to treat cancer. As the key cellular effectors of adaptive immunity, T cells are endowed with specialized receptors (the T cell receptor; TCR), to recognize and to eliminate cancer cells. The diversity of the TCR repertoire results from specialized genetic diversification mechanisms that generate an incredible variability allowing recognizing extensive collections of antigens. Based on the attainment and function of the TCR, the TCR repertoire is a mirror of the human immune response, and the dynamic changes of its usage can be assumed as a promising biomarker to monitor immunomodulatory therapies. Recent advances in multiplexed PCR amplification and massive parallel sequencing technologies have facilitated the characterization of TCR repertoires at high resolution even when only biomaterial of limited quantity and quality, such as formalin-fixed paraffin-embedded (FFPE) archived tissues, is available. Here, we review the concept framework and current experimental approaches to characterize the TCR repertoire usage in cancer including inherent technical and biological challenges.