Intra-tumoral T cells in pediatric brain tumors display clonal expansion and effector properties.

Brain tumors in children are a devastating disease in a high proportion of patients. Owing to inconsistent results in clinical trials in unstratified patients, the role of immunotherapy remains unclear. We performed an in-depth survey of the single-cell transcriptomes and clonal relationship of intra-tumoral T cells from children with brain tumors. Our results demonstrate that a large fraction of T cells in the tumor tissue are clonally expanded with the potential to recognize tumor antigens. Such clonally expanded T cells display enrichment of transcripts linked to effector function, tissue residency, immune checkpoints and signatures of neoantigen-specific T cells and immunotherapy response. We identify neoantigens in pediatric brain tumors and show that neoantigen-specific T cell gene signatures are linked to better survival outcomes. Notably, among the patients in our cohort, we observe substantial heterogeneity in the degree of clonal expansion and magnitude of T cell response. Our findings suggest that characterization of intra-tumoral T cell responses may enable selection of patients for immunotherapy, an approach that requires prospective validation in clinical trials.

PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins.

BACKGROUND: Numerous tools exist for biological sequence comparisons and search. One case of particular interest for immunologists is finding matches for linear peptide T cell epitopes, typically between 8 and 15 residues in length, in a large set of protein sequences. Both to find exact matches or matches that account for residue substitutions. The utility of such tools is critical in applications ranging from identifying conservation across viral epitopes, identifying putative epitope targets for allergens, and finding matches for cancer-associated neoepitopes to examine the role of tolerance in tumor recognition. RESULTS: We defined a set of benchmarks that reflect the different practical applications of short peptide sequence matching. We evaluated a suite of existing methods for speed and recall and developed a new tool, PEPMatch. The tool uses a deterministic k-mer mapping algorithm that preprocesses proteomes before searching, achieving a 50-fold increase in speed over methods such as the Basic Local Alignment Search Tool (BLAST) without compromising recall. PEPMatch's code and benchmark datasets are publicly available. CONCLUSIONS: PEPMatch offers significant speed and recall advantages for peptide sequence matching. While it is of immediate utility for immunologists, the developed benchmarking framework also provides a standard against which future tools can be evaluated for improvements. The tool is available at https://nextgen-tools.iedb.org , and the source code can be found at https://github.com/IEDB/PEPMatch .

Linked CD4+/CD8+ T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression.

Therapeutic benefit to immune checkpoint blockade (ICB) is currently limited to the subset of cancers thought to possess a sufficient tumor mutational burden (TMB) to allow for the spontaneous recognition of neoantigens (NeoAg) by autologous T cells. We explored whether the response to ICB of an aggressive low-TMB squamous cell tumor could be improved through combination immunotherapy using functionally defined NeoAg as targets for endogenous CD4+ and CD8+ T cells. We found that, whereas vaccination with CD4+ or CD8+ NeoAg alone did not offer prophylactic or therapeutic immunity, vaccines containing NeoAg recognized by both subsets overcame ICB resistance and led to the eradication of large established tumors that contained a subset of PD-L1+ tumor-initiating cancer stem cells (tCSC), provided the relevant epitopes were physically linked. Therapeutic CD4+/CD8+ T cell NeoAg vaccination produced a modified tumor microenvironment (TME) with increased numbers of NeoAg-specific CD8+ T cells existing in progenitor and intermediate exhausted states enabled by combination ICB-mediated intermolecular epitope spreading. We believe that the concepts explored herein should be exploited for the development of more potent personalized cancer vaccines that can expand the range of tumors treatable with ICB.

Linked CD4 + /CD8 + T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression.

Therapeutic benefit to immune checkpoint blockade (ICB) is currently limited to the subset of cancers thought to possess a sufficient tumor mutational burden (TMB) to allow for the spontaneous recognition of neoantigens (NeoAg) by autologous T cells. We explored whether the response of an aggressive low TMB squamous cell tumor to ICB could be improved through combination immunotherapy using functionally defined NeoAg as targets for endogenous CD4 + and CD8 + T cells. We found that, whereas vaccination with CD4 + or CD8 + NeoAg alone did not offer prophylactic or therapeutic immunity, vaccines containing NeoAg recognized by both subsets overcame ICB resistance and led to the eradication of large established tumors that contained a subset of PD-L1 + tumor-initiating cancer stem cells (tCSC), provided the relevant epitopes were physically linked. Therapeutic CD4 + /CD8 + T cell NeoAg vaccination produced a modified tumor microenvironment (TME) with increased numbers of NeoAg-specific CD8 + T cells existing in progenitor and intermediate exhausted states enabled by combination ICB-mediated intermolecular epitope spreading. The concepts explored herein should be exploited for the development of more potent personalized cancer vaccines that can expand the range of tumors treatable with ICB.

Estimating tissue-specific peptide abundance from public RNA-Seq data.

Several novel MHC class I epitope prediction tools additionally incorporate the abundance levels of the peptides' source antigens and have shown improved performance for predicting immunogenicity. Such tools require the user to input the MHC alleles and peptide sequences of interest, as well as the abundance levels of the peptides' source proteins. However, such expression data is often not directly available to users, and retrieving the expression level of a peptide's source antigen from public databases is not trivial. We have developed the Peptide eXpression annotator (pepX), which takes a peptide as input, identifies from which proteins the peptide can be derived, and returns an estimate of the expression level of those source proteins from selected public databases. We have also investigated how the abundance level of a peptide can be best estimated in cases when it can originate from multiple transcripts and proteins and found that summing up transcript-level expression values performs best in distinguishing ligands from decoy peptides.

Tumor cells fail to present MHC-II-restricted epitopes derived from oncogenes to CD4+ T cells.

CD4+ T cells play a critical role in antitumor immunity via recognition of peptide antigens presented on MHC class II (MHC-II). Although some solid cancers can be induced to express MHC-II, the extent to which this enables direct recognition by tumor-specific CD4+ T cells is unclear. We isolated and characterized T cell antigen receptors (TCRs) from naturally primed CD4+ T cells specific for 2 oncoproteins, HPV-16 E6 and the activating KRASG12V mutation, from patients with head and neck squamous cell carcinoma and pancreatic ductal adenocarcinoma, respectively, and determined their ability to recognize autologous or human leukocyte antigen-matched antigen-expressing tumor cells. We found in both cases that the TCRs were capable of recognizing peptide-loaded target cells expressing the relevant MHC-II or B cell antigen-presenting cells (APCs) when the antigens were endogenously expressed and directed to the endosomal pathway but failed to recognize tumor cells expressing the source protein even after induction of surface MHC-II expression by IFN-γ or transduction with CIITA. These results suggest that priming and functional recognition of both a nuclear (E6) and a membrane-associated (KRAS) oncoprotein are predominantly confined to crosspresenting APCs rather than via direct recognition of tumor cells induced to express MHC-II.

Towards the prediction of non-peptidic epitopes.

In-silico methods for the prediction of epitopes can support and improve workflows for vaccine design, antibody production, and disease therapy. So far, the scope of B cell and T cell epitope prediction has been directed exclusively towards peptidic antigens. Nevertheless, various non-peptidic molecular classes can be recognized by immune cells. These compounds have not been systematically studied yet, and prediction approaches are lacking. The ability to predict the epitope activity of non-peptidic compounds could have vast implications; for example, for immunogenic risk assessment of the vast number of drugs and other xenobiotics. Here we present the first general attempt to predict the epitope activity of non-peptidic compounds using the Immune Epitope Database (IEDB) as a source for positive samples. The molecules stored in the Chemical Entities of Biological Interest (ChEBI) database were chosen as background samples. The molecules were clustered into eight homogeneous molecular groups, and classifiers were built for each cluster with the aim of separating the epitopes from the background. Different molecular feature encoding schemes and machine learning models were compared against each other. For those models where a high performance could be achieved based on simple decision rules, the molecular features were then further investigated. Additionally, the findings were used to build a web server that allows for the immunogenic investigation of non-peptidic molecules (http://tools-staging.iedb.org/np_epitope_predictor). The prediction quality was tested with samples from independent evaluation datasets, and the implemented method received noteworthy Receiver Operating Characteristic-Area Under Curve (ROC-AUC) values, ranging from 0.69-0.96 depending on the molecule cluster.

TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors.

The adaptive immune system in vertebrates has evolved to recognize non-self antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared seven metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR ß-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA.

The expression of CD45RA is generally associated with naive T cells. However, a subset of effector memory T cells re-expresses CD45RA (termed TEMRA) after antigenic stimulation with unknown molecular characteristics and functions. CD4 TEMRA cells have been implicated in protective immunity against pathogens such as dengue virus (DENV). Here we show that not only the frequency but also the phenotype of CD4 TEMRA cells are heterogeneous between individuals. These cells can be subdivided into two major subsets based on the expression of the adhesion G protein-coupled receptor GPR56, and GPR56+ TEMRA cells display a transcriptional and proteomic program with cytotoxic features that is distinct from effector memory T cells. Moreover, GPR56+ TEMRA cells have higher levels of clonal expansion and contain the majority of virus-specific TEMRA cells. Overall, this study reveals the heterogeneity of CD4 TEMRA cells and provides insights into T-cell responses against DENV and other viral pathogens.

Immunodominance in allergic T-cell reactivity to Japanese cedar in different geographic cohorts.

BACKGROUND: Japanese cedar (JC) pollen is a common trigger for allergic rhinitis in Japan. Pollen proteins targeted by IgE, including Cry j 1 and Cry j 2, and isoflavone reductase (IFR) have been identified. OBJECTIVE: To compare antigen-specific IgE titers and T-cell responses to JC pollen-derived extract and peptides in cohorts with high and low pollen exposure. METHODS: Peripheral blood mononuclear cells from JC pollen allergic or nonallergic patients who have lived in Japan for at least 1 year and JC pollen allergic patients who have never been to Japan were tested for T-cell responses against JC pollen extract and peptide pools derived from Cry j 1, Cry j 2, or IFR. T-cell reactivity was assessed by interleukin 5 and interferon γ production by ELISPOT. RESULTS: JC pollen-specific T-cell reactivity and IgE titers were significantly higher in the allergic compared with the nonallergic Japanese cohort, which was also associated with different patterns of polysensitization. Interestingly, a significant overlap was observed in the hierarchy of the T-cell epitopes in the allergic Japanese cohort compared with the allergic non-Japanese cohort. In all 3 cohorts, T-cell reactivity was dominantly directed against peptides from the major allergens Cry j 1 and 2, with few T-cell responses detected against IFR. CONCLUSION: Our studies identify common denominators of T-cell reactivity in patient populations with different sensitization patterns, suggesting that generally applicable immunotherapeutic approaches might be developed irrespective of exposure modality.

IL-10-producing intestinal macrophages prevent excessive antibacterial innate immunity by limiting IL-23 synthesis.

Innate immune responses are regulated in the intestine to prevent excessive inflammation. Here we show that a subset of mouse colonic macrophages constitutively produce the anti-inflammatory cytokine IL-10. In mice infected with Citrobacter rodentium, a model for enteropathogenic Escherichia coli infection in humans, these macrophages are required to prevent intestinal pathology. IL-23 is significantly increased in infected mice with a myeloid cell-specific deletion of IL-10, and the addition of IL-10 reduces IL-23 production by intestinal macrophages. Furthermore, blockade of IL-23 leads to reduced mortality in the context of macrophage IL-10 deficiency. Transcriptome and other analyses indicate that IL-10-expressing macrophages receive an autocrine IL-10 signal. Interestingly, only transfer of the IL-10 positive macrophages could rescue IL-10-deficient infected mice. Therefore, these data indicate a pivotal role for intestinal macrophages that constitutively produce IL-10, in controlling excessive innate immune activation and preventing tissue damage after an acute bacterial infection.

Properties of MHC class I presented peptides that enhance immunogenicity.

T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4-6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.

Comprehensive analysis of dengue virus-specific responses supports an HLA-linked protective role for CD8+ T cells.

The role of CD8(+) T cells in dengue virus infection and subsequent disease manifestations is not fully understood. According to the original antigenic sin theory, skewing of T-cell responses induced by primary infection with one serotype causes less effective response upon secondary infection with a different serotype, predisposing individuals to severe disease. A comprehensive analysis of CD8(+) responses in the general population from the Sri Lankan hyperendemic area, involving the measurement of ex vivo IFNγ responses associated with more than 400 epitopes, challenges the original antigenic sin theory. Although skewing of responses toward primary infecting viruses was detected, this was not associated with impairment of responses either qualitatively or quantitatively. Furthermore, we demonstrate higher magnitude and more polyfunctional responses for HLA alleles associated with decreased susceptibility to severe disease, suggesting that a vigorous response by multifunctional CD8(+) T cells is associated with protection from dengue virus disease.

The immune epitope database 2.0.

The Immune Epitope Database (IEDB, www.iedb.org) provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments. The database represents the molecular structures recognized by adaptive immune receptors and the experimental contexts in which these molecules were determined to be immune epitopes. Epitopes recognized in humans, nonhuman primates, rodents, pigs, cats and all other tested species are included. Both positive and negative experimental results are captured. Over the course of 4 years, the data from 180,978 experiments were curated manually from the literature, which covers approximately 99% of all publicly available information on peptide epitopes mapped in infectious agents (excluding HIV) and 93% of those mapped in allergens. In addition, data that would otherwise be unavailable to the public from 129,186 experiments were submitted directly by investigators. The curation of epitopes related to autoimmunity is expected to be completed by the end of 2010. The database can be queried by epitope structure, source organism, MHC restriction, assay type or host organism, among other criteria. The database structure, as well as its querying, browsing and reporting interfaces, was completely redesigned for the IEDB 2.0 release, which became publicly available in early 2009.