ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer

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Abstract

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.

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Trincado, J. L., Reixachs-Solé, M., Pérez-Granado, J., Fugmann, T., Sanz, F., Yokota, J., & Eyras, E. (2021). ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer. PLoS Computational Biology, 17(9). https://doi.org/10.1371/journal.pcbi.1009411

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