ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer

PLoS Comput Biol. 2021 Sep 16;17(9):e1009411. doi: 10.1371/journal.pcbi.1009411. eCollection 2021 Sep.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alternative Splicing / genetics
  • Alternative Splicing / immunology
  • Breast Neoplasms / genetics
  • Breast Neoplasms / immunology
  • Carcinoma, Small Cell / genetics
  • Carcinoma, Small Cell / immunology
  • Cell Line, Tumor
  • Computational Biology
  • Epitopes / genetics*
  • Epitopes / immunology*
  • Female
  • Histocompatibility Antigens Class I / genetics
  • Histocompatibility Antigens Class I / immunology
  • Humans
  • Immunotherapy
  • Lung Neoplasms / genetics
  • Lung Neoplasms / immunology
  • Male
  • Melanoma / genetics
  • Melanoma / immunology
  • Models, Genetic
  • Models, Immunological
  • Mutation
  • Neoplasms / genetics*
  • Neoplasms / immunology*
  • Neoplasms / therapy
  • Protein Isoforms / genetics
  • Protein Isoforms / immunology
  • RNA Splicing / genetics
  • RNA Splicing / immunology
  • RNA-Seq

Substances

  • Epitopes
  • Histocompatibility Antigens Class I
  • Protein Isoforms

Grants and funding

This work was supported by the Agencia Estatal de Investigación (AEI), Spanish Government and European Regional Development Fund (FEDER) with grant BIO2017-85364-R (F.S., E.E.), by the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya) with grants SGR2017-1020 (E.E) and 2017 SGR 00519 (F.S), by the Instituto de Salud Carlos III (ISCIII and FEDER) with grants FI18/00034 (J.P-G) and PT17/0009/0014 (F.S), and by the AEI with CEX2018-000782-M (F.S). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB) supported by ISCIII and FEDER (PT17/0009/0014). The DCEXS is a ‘Unidad de Excelencia María de Maeztu’ supported by the AEI (CEX2018-000782-M). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.