Genome Medicine (Aug 2017)

The neoepitope landscape in pediatric cancers

  • Ti-Cheng Chang,
  • Robert A. Carter,
  • Yongjin Li,
  • Yuxin Li,
  • Hong Wang,
  • Michael N. Edmonson,
  • Xiang Chen,
  • Paula Arnold,
  • Terrence L. Geiger,
  • Gang Wu,
  • Junmin Peng,
  • Michael Dyer,
  • James R. Downing,
  • Douglas R. Green,
  • Paul G. Thomas,
  • Jinghui Zhang

DOI
https://doi.org/10.1186/s13073-017-0468-3
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 12

Abstract

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Abstract Background Neoepitopes derived from tumor-specific somatic mutations are promising targets for immunotherapy in childhood cancers. However, the potential for such therapies in targeting these epitopes remains uncertain due to a lack of knowledge of the neoepitope landscape in childhood cancer. Studies to date have focused primarily on missense mutations without exploring gene fusions, which are a major class of oncogenic drivers in pediatric cancer. Methods We developed an analytical workflow for identification of putative neoepitopes based on somatic missense mutations and gene fusions using whole-genome sequencing data. Transcriptome sequencing data were incorporated to interrogate the expression status of the neoepitopes. Results We present the neoepitope landscape of somatic alterations including missense mutations and oncogenic gene fusions identified in 540 childhood cancer genomes and transcriptomes representing 23 cancer subtypes. We found that 88% of leukemias, 78% of central nervous system tumors, and 90% of solid tumors had at least one predicted neoepitope. Mutation hotspots in KRAS and histone H3 genes encode potential epitopes in multiple patients. Additionally, the ETV6-RUNX1 fusion was found to encode putative neoepitopes in a high proportion (69.6%) of the pediatric leukemia harboring this fusion. Conclusions Our study presents a comprehensive repertoire of potential neoepitopes in childhood cancers, and will facilitate the development of immunotherapeutic approaches designed to exploit them. The source code of the workflow is available at GitHub ( https://github.com/zhanglabstjude/neoepitope ).

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