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A multiplex method for the detection of serum antibodies against in silico-predicted tumor antigens

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Abstract

Humoral immune responses against tumor antigens are studied as indirect markers of antigen exposure and in cancer vaccine studies. An increasing number of tumor antigens potentially translated from mutant genes is identified by advances in genomic sequencing. They represent an interesting source for yet unknown immunogenic epitopes. We here describe a multiplex method using the Luminex technology allowing for the detection of antibodies against multiple in silico-predicted linear neo-antigens in large sets of sera. The approach included 32 synthetic biotinylated peptides comprising a predicted set of frameshift mutation-induced neo-antigens. The antigens were fused to a FLAG epitope to ensure monitoring antigen binding to avidin-linked microspheres in the absence of monoclonal antibodies. Analytical specificity of measured serum antibody reactivity was proven by the detection of immune responses in immunized rabbits and a colorectal cancer patient vaccinated with peptides included in the assay. The measured antibody responses were comparable to peptide ELISA, and inter-assay reproducibility of the multiplex approach was excellent (R 2 > 0.98) for 20 sera tested against all antigens. Our methodic approach represents a valuable platform to monitor antibody responses against predicted antigens. It may be used in individualized cancer vaccine studies, thereby extending the relevance beyond the model system in the presented approach.

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Acknowledgments

The authors thank the sponsor of the Micoryx trial (ClinicalTrials.gov Identifier: NCT01461148) Oryx GmbH und Co KG, Marktplatz 1, 85598 Baldham, Germany, namely Dr. Dr. Michael W. Dahm, Dr. Ottheinz Krebs, and Dr. Bernard Huber. This work was funded by a Grant No. 109477 from the German Cancer Aid (Deutsche Krebshilfe).

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Correspondence to Miriam Reuschenbach.

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Reuschenbach, M., Dörre, J., Waterboer, T. et al. A multiplex method for the detection of serum antibodies against in silico-predicted tumor antigens. Cancer Immunol Immunother 63, 1251–1259 (2014). https://doi.org/10.1007/s00262-014-1595-y

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  • DOI: https://doi.org/10.1007/s00262-014-1595-y

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