Monoallelic point mutations of isocitrate dehydrogenase type 1 (IDH1) are an early and defining event in the development of a subgroup of gliomas and other types of tumour. They almost uniformly occur in the critical arginine residue (Arg 132) in the catalytic pocket, resulting in a neomorphic enzymatic function, production of the oncometabolite 2-hydroxyglutarate (2-HG), genomic hypermethylation, genetic instability and malignant transformation. More than 70% of diffuse grade II and grade III gliomas carry the most frequent mutation, IDH1(R132H) (ref. 3). From an immunological perspective, IDH1(R132H) represents a potential target for immunotherapy as it is a tumour-specific potential neoantigen with high uniformity and penetrance expressed in all tumour cells. Here we demonstrate that IDH1(R132H) contains an immunogenic epitope suitable for mutation-specific vaccination. Peptides encompassing the mutated region are presented on major histocompatibility complexes (MHC) class II and induce mutation-specific CD4(+) T-helper-1 (TH1) responses. CD4(+) TH1 cells and antibodies spontaneously occurring in patients with IDH1(R132H)-mutated gliomas specifically recognize IDH1(R132H). Peptide vaccination of mice devoid of mouse MHC and transgenic for human MHC class I and II with IDH1(R132H) p123-142 results in an effective MHC class II-restricted mutation-specific antitumour immune response and control of pre-established syngeneic IDH1(R132H)-expressing tumours in a CD4(+) T-cell-dependent manner. As IDH1(R132H) is present in all tumour cells of these slow-growing gliomas, a mutation-specific anti-IDH1(R132H) vaccine may represent a viable novel therapeutic strategy for IDH1(R132H)-mutated tumours.

Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their peptide ligands is important for vaccine design. We introduce an open-source package for MHC I binding prediction, MHCflurry. The software implements allele-specific neural networks that use a novel architecture and peptide encoding scheme. When trained on affinity measurements, MHCflurry outperformed the standard predictors NetMHC 4.0 and NetMHCpan 3.0 overall and particularly on non-9-mer peptides in a benchmark of ligands identified by mass spectrometry. The released predictor, MHCflurry 1.2.0, uses mass spectrometry datasets for model selection and showed competitive accuracy with standard tools, including the recently released NetMHCpan 4.0, on a small benchmark of affinity measurements. MHCflurry's prediction speed exceeded 7,000 predictions per second, 396 times faster than NetMHCpan 4.0. MHCflurry is freely available to use, retrain, or extend, includes Python library and command line interfaces, may be installed using package managers, and applies software development best practices.

Epidemiological studies have suggested inverse associations between allergic diseases and malignancies. As a proof of concept for the capability of immunoglobulin E (IgE) to destruct tumor cells, several experimental strategies have evolved to specifically target this antibody class towards relevant tumor antigens. It could be demonstrated that IgE antibodies specific to overexpressed tumor antigens have been superior to any other immunoglobulin class with respect to antibody-dependent cellular cytotoxicity (ADCC) and phagocytosis (ADCP) reactions. In an alternative approach, IgE nonspecifically attached to tumor cells proved to be a powerful adjuvant establishing tumor-specific immune memory. Active Th2 immunity could also be achieved by applying an oral immunization regimen using mimotopes, i.e. epitope mimics of tumor antigens. The induced IgE antibodies could be cross-linked by live tumor cells leading to tumoricidic mediator release. Thus, IgE antibodies may not only act in natural tumor surveillance, but could possibly also be exploited for tumor control in active and passive immunotherapy settings. Thereby, eosinophils, mast cells and macrophages can be armed with the cytophilic IgE and become potent anti-tumor effectors, able to trace viable tumor cells in the tissues. It is strongly suggested that the evolving new field AllergoOncology will give new insights into the role of IgE-mediated allergy in malignancies, possibly opening new avenues for tumor therapy.

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Recently, we have demonstrated that anti-ulcer drugs, such as H2-receptor blockers and proton pump inhibitors, promote the development of immediate type food allergy toward digestion-labile proteins in mice. The aim of this study was to examine the allergological relevance of these findings in humans. In an observational cohort study, we screened 152 adult patients from a gastroenterological outpatient clinic with negative case histories for atopy or allergy, who were medicated with H2-receptor blockers or proton pump inhibitors for 3 months. IgE reactivities to food allergens before and after 3 months of anti-acid treatment were compared serologically. Ten percent of the patients showed a boost of preexisting IgE antibodies and 15% de novo IgE formation toward numerous digestion-labile dietary compounds, like milk, potato, celery, carrots, apple, orange, wheat, and rye flour. Thus, the relative risk to develop food-specific IgE after anti-acid therapy was 10.5 (95% confidence interval: 1.44-76.48). The long-term effect was evaluated 5 months after therapy. Food-specific IgE could still be measured in 6% of the patients, as well as significantly elevated serum concentrations of ST2, a Th2-specific marker. An unspecific boost during the pollen season could be excluded, as 50 untreated control patients revealed no changes in their IgE pattern. In line with our previous animal experiments, our data strongly suggest that anti-ulcer treatment primes the development of IgE toward dietary compounds in long-term acid-suppressed patients.

Human papillomavirus (HPV) is the most frequently sexually transmitted agent in the world. It can cause cervical and other anogenital malignancies, and oropharyngeal cancer. HPV has the unique ability to persist in the host's epithelium for a long time-longer than most viruses do-which is necessary to complete its replication cycle. To this end, HPV has developed a variety of immune evasion mechanisms, which unfortunately also favor the progression of the disease from infection to chronic dysplasia and eventually to cancer. This article summarizes the current knowledge about HPV immune evasion strategies. A special emphasis lies in HPV-mediated changes of the antigen processing machinery, which is generating epitopes for T cells and contributes to the detectability of infected cells.

Human Papillomavirus 16 (HPV-16) has been identified as the causative agent of 50% of cervical cancers and many other HPV-associated tumors. The transforming potential/tumor maintenance capacity of this high risk HPV is mediated by two viral oncoproteins, E6 and E7, making them attractive targets for therapeutic vaccines. Of 21 E6 and E7 peptides computed to bind HLA-A*0201, 10 were confirmed through TAP-deficient T2 cell HLA stabilization assay. Those scoring positive were investigated to ascertain which were naturally processed and presented by surface HLA molecules for CTL recognition. Because IFN␥ ELISpot frequencies from healthy HPV-exposed blood donors against HLA-A*0201-binding peptides were unable to identify specificities for tumor targeting, their physical presence among peptides eluted from HPV-16-transformed epithelial tumor HLA-A*0201 immunoprecipitates was analyzed by MS 3 Poisson detection mass spectrometry. Only one epitope (E7 11-19 ) highly conserved among HPV-16 strains was detected. This 9-mer serves to direct cytolysis by T cell lines, whereas a related 10-mer (E7 11-20 ), previously used as a vaccine candidate, was neither detected by MS 3 on HPV-transformed tumor cells nor effectively recognized by 9-mer specific CTL. These data underscore the importance of precisely defining CTL epitopes on tumor cells and offer a paradigm for T cellbased vaccine design.The transforming potential of human Papillomavirus (HPV), 4 first suspected in the 1970s, has now been firmly established both biologically and epidemiologically (1-3). The single most important variable linked to malignant transformation is persistent infection with one of the high-risk HPV types. The E6 and E7 proteins encoded by high-risk HPVs have transforming activities and functionally inactivate the p53 and retinoblastoma (Rb) tumor suppressor proteins, respectively (3, 4). HPV-16 is the most abundant high risk HPV and has been detected in Ͼ50% of cervical cancer cases and in most other HPV-induced tumors, such as carcinomas of the vagina, anus, vulva, penis, and oropharynx (3, 5, 6). Worldwide, high risk HPVs are thought to be responsible for Ͼ500,000 malignancies per year, representing more than 5% of human cancers (7).A major breakthrough in combating HPV-induced disease was the development of prophylactic vaccines to prevent HPV infection in previously unexposed individuals. These vaccines are based on virus-like particles consisting of the L1 capsid protein (8, 9). Virus-like particles resemble natural virions and are able to induce high titers of L1-neutralizing antibodies. Two vaccines, one against HPV-16, -18, -6, and -11 and another against HPV-16 and -18, were approved for clinical use in 2006 (10 -12). Although the impact of prophylactic HPV vaccination on the incidence of vaccine type HPV-associated disease and cancer is unquestionable over time, these vaccines have no therapeutic efficacy for established HPV infections. Antibodies neutralize virus particles only before infection. Moreover, as HPV capsid proteins are exc...

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low predictive value for actual peptide presentation, inadequate support for rare MHC alleles, and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method that predicts peptide-MHC binding. MHCnuggets can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is faster than other methods. When compared with methods that integrate binding affinity and MHC-bound peptide (HLAp) data from mass spectrometry, MHCnuggets yields a 4-fold increase in positive predictive value on independent HLAp data. We applied MHCnuggets to 26 cancer types in The Cancer Genome Atlas, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique predicted immunogenic missense mutations (IMM). Predicted IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted IMM load was significantly associated with increased immune cell infiltration (P < 2 Â 10 À16), including CD8 þ T cells. Only 0.16% of predicted IMMs were observed in more than 2 patients, with 61.7% of these derived from driver mutations. Thus, we describe a method for neoantigen prediction and its performance characteristics and demonstrate its utility in data sets representing multiple human cancers.