Site-specific epitope insertion into recombinant proteins using the MAP tag system

The MAP tag system comprises a 14-residue peptide derived from mouse podoplanin and its high-affinity monoclonal antibody PMab-1. We determined the crystal structure of PMab-1 complexed with the MAP tag peptide and found that the recognition required only the N-terminal 8 residues of MAP tag sequence, enabling the shortening of the tag length without losing the affinity for PMab-1. Furthermore, the structure illustrated that the MAP tag adopts a U-shaped conformation when bound by PMab-1, suggesting that loop-inserted MAP tag would assume conformation compatible with the PMab-1 binding. We inserted the 8-residue MAP tag into multiple loop regions in various proteins including fibronectin type III domain and G-protein-coupled receptors and tested if they maintain PMab-1 reactivity. Despite the conformational restraints forced by the insertion position, all MAP-inserted mutants were expressed well in mammalian cells at levels comparable to the non-tagged proteins. Furthermore, the binding by PMab-1 was fully maintained even for the mutant where MAP tag was inserted at a structurally restricted β-hairpin, indicating that the MAP tag system has unique feature that allows placement in the middle of protein domain at desired locations. Our results indicate the versatile utility of the MAP tag system in ‘site-specific epitope insertion’ application.

Benchmark datasets of immune receptor-epitope structural complexes

Background The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets. Results To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need. Conclusions SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre.

P12.08 Immunocytokines are a novel immunotherapeutic approach against glioblastoma

BACKGROUND Glioblastoma is the most common malignant primary brain tumor in adults with an urgent need for novel treatment options. The administration of pro-inflammatory cytokines could be a potent immunotherapeutic approach to shift the balance between tumor-associated immunosuppression and immune activation. However, the systemic administration of therapeutically active doses of pro-inflammatory cytokines is not feasible due to toxic side effects and there is a need for strategies that enable a targeted delivery of pro-inflammatory cytokines to the tumor site. METHODS We investigated different antibody-cytokine fusion products that enable a targeted delivery of interleukin (IL)-2, IL-12 or tumor necrosis factor (TNF)-α to the tumor site by binding to a tumor-specific epitope of fibronectin. We investigated the expression of this tumor-specific epitope ex vivo in tumor-bearing mouse brains and human glioblastoma samples. Subsequently, we assessed the anti-tumor activity of IL-2, IL-12 or TNF-α fused to an antibody targeting this tumor-specific epitope in orthotopic syngeneic mouse glioma models. RESULTS The tumor-specfic extra domain B of fibronectin is expressed in murine glioma models and human glioblastoma samples. A fluorochrome-labeled antibody targeting this tumor-specific epitope accumulated at the tumor site in the brain in vivo upon systemic administration. IL-2, IL-12, or TNF-α fused to this antibody conferred a survival benefit in orthotopic tumor-bearing mice and cured a fraction of tumor-bearing mice. Mechanistically, antibody-fused TNF-α induced tumor necrosis and increased the activation of tumor-infiltrating natural killer (NK) cells, whereas antibody-fused IL-12 mainly boosted an anti-tumor immune response mediated by NK cells and T cells. CONCLUSION We demonstrate the expression of a tumor-specific epitope of fibronectin in glioblastoma and exploit this for the targeted delivery of IL-2, IL-12 or TNF-α to the tumor site. Our preclinical assessments indicate potent anti-tumor activity in orthotopic, syngneic glioma mouse models and reveal the mode of action for the different immunocytokines. Based on these findings, we initiated a phase I/II clinical trial in patients with recurrent glioma to investigate the targeted delivery of TNF-α (ClinicalTrials.gov identifier NCT03779230).

Binding is not enough; autoantibodies do more to garner complements

Pathogenic autoantibodies in neuromyelitis optica require antigen array assembly and a specific epitope to initiate robust complement activation.

HIV peptidome-wide association study reveals patient-specific epitope repertoires associated with HIV control

Genetic variation in the peptide-binding groove of the highly polymorphic HLA class I molecules has repeatedly been associated with HIV-1 control and progression to AIDS, accounting for up to 12% of the variation in HIV-1 set point viral load (spVL). This suggests a key role in disease control for HLA presentation of HIV-1 epitopes to cytotoxic T cells. However, a comprehensive understanding of the relevant HLA-bound HIV epitopes is still elusive. Here we describe a peptidome-wide association study (PepWAS) approach that integrates HLA genotypes and spVL data from 6,311 HIV-infected patients to interrogate the entire HIV-1 proteome (3,252 unique peptides) for disease-relevant peptides. This PepWAS approach predicts a core set of epitopes associated with spVL, including known epitopes but also several previously uncharacterized disease-relevant peptides. More important, each patient presents only a small subset of these predicted core epitopes through their individual HLA-A and HLA-B variants. Eventually, the individual differences in these patient-specific epitope repertoires account for the variation in spVL that was previously associated with HLA genetic variation. PepWAS thus enables a comprehensive functional interpretation of the robust but little-understood association between HLA and HIV-1 control, prioritizing a short list of disease-associated epitopes for the development of targeted therapy.

TCRex: detection of enriched T cell epitope specificity in full T cell receptor sequence repertoires

ABSTRACTHigh-throughput T cell receptor (TCR) sequencing allows the characterization of an individual’s TCR repertoire and directly query their immune state. However, it remains a non-trivial task to couple these sequenced TCRs to their antigenic targets. In this paper, we present a novel strategy to annotate full TCR sequence repertoires. The strategy is based on a machine learning algorithm to learn the TCR patterns common to the recognition of a specific epitope. These results are then combined with a statistical analysis to evaluate the occurrence of specific epitope-reactive TCR sequences per epitope in repertoire data. In this manner, we can directly study the capacity of full TCR repertoires to target specific epitopes of the relevant vaccines or pathogens. We demonstrate the usability of this approach on three independent datasets related to vaccine monitoring and infectious disease diagnostics by independently identifying the epitopes that are targeted by the TCR repertoire. The developed method is freely available as a web tool for academic use at tcrex.biodatamining.be.