An efficient T-cell epitope discovery strategy using in silico prediction and the iTopia assay platform

Abstract

Functional T-cell epitope discovery is a key process for the development of novel immunotherapies, particularly for cancer immunology. In silico epitope prediction is a common strategy to try to achieve this objective. However, this approach suffers from a significant rate of false-negative results and epitope ranking lists that often are not validated by practical experience. A high-throughput platform for the identification and prioritization of potential T-cell epitopes is the iTopiaTM Epitope Discovery SystemTM, which allows measuring binding and stability of selected peptides to MHC Class I molecules. So far, the value of iTopia combined with in silico epitope prediction has not been investigated systematically. In this study, we have developed a novel in silico selection strategy based on three criteria: (1) predicted binding to one out of five common MHC Class I alleles; (2) uniqueness to the antigen of interest; and (3) increased likelihood of natural processing. We predicted in silico and characterized by iTopia 225 candidate T-cell epitopes and fixed-anchor analogs from three human tumor-associated antigens: CEA, HER2 and TERT. HLA-A2-restricted fragments were further screened for their ability to induce cell-mediated responses in HLA-A2 transgenic mice. The iTopia binding assay was only marginally informative while the stability assay proved to be a valuable experimental screening method complementary to in silico prediction. Thirteen novel T-cell epitopes and analogs were characterized and additional potential epitopes identified, providing the basis for novel anticancer immunotherapies. In conclusion, we show that combination of in silico prediction and an iTopia-based assay may be an accurate and efficient method for MHC Class I epitope discovery among tumor-associated antigens.

Current tools for predicting cancer-specific T cell immunity

“…63,64,94 Alternatively, MS immune-peptidome analysis may be combined with UV irradiation induced exchange of conditional MHC ligands with libraries of predicted peptides. 49,50,70 A powerful strategy of epitope discovery and T cell analysis consist in using peptide exchange combined with combinatorial multimer flow cytometry analysis of patient's TIL or PBMC. 5,52,53,87 For more accurate selection of MHC ligands, this analysis can be combined with MS immune-peptidome analysis.…”

“…2A). 49 (2) A peptide-rescuing assay in which pMHC complexes containing a photo-cleavable peptide are UV irradiated in the presence of test peptides, which depending on their MHC-binding strength can rescue the "empty" MHC molecule. 50,51 This method allows the generation of large numbers of different pMHC monomers and thus facilitates combinatorial multimer staining.…”

A novel minigene scaffold for therapeutic cancer vaccines

“…Peptide MHC binding and complex stability was characterized using the iTopia TM Epitope Discovery System (Beckman Coulter), as previously described 24 . Briefly, the assay utilizes avidin-coated microtiter plates containing biotinylated MHC-I monomers loaded with β2-microglobulin (β2M) and placeholder peptides.…”

“…We characterized 225 candidate T-cell epitopes (wild-type and fixed-anchor analogs) selected within CEA, HER2/ neu and hTERT by high-throughput stable binding to MHC using the iTopia epitope discovery assay 24 . On the basis of these results, we concluded that the combination of in silico prediction and a biochemical binding/stability assay represents an accurate prediction of novel TAA-derived epitopes.…”

Immunogenicity and Therapeutic Efficacy of a Dual-Component Genetic Cancer Vaccine Cotargeting Carcinoembryonic Antigen and HER2/neu in Preclinical Models

“…When loaded with CEA and HER2/neu peptides, JY cells were efficiently lysed by effectors. Similarly, HLA-A*0201-selected CEA peptides (Conforti et al, 2009;Fridman et al, 2012) were recognized and significant lytic activity was observed (Fig. 7B).…”