Abstract B079: Evaluation of tools for predicting mutated tumor antigens from exome and RNA sequencing

Neoantigen vaccination is an emerging modality of cancer immunotherapy with many ongoing trials. One central question of neoantigen vaccination is the method for selecting which mutated tumor-specific antigens to include in a patient’s vaccine. Many in-silico pipelines for neoantigen selection have been published in the past few years, but no comprehensive evaluation has compared them directly on the same tumor/normal sequencing data. We evaluate several publicly available commonly used neoantigen pipelines (pVACtools [1], MuPeXI [2], TIminer [3], OpenVax [4]) on both murine and human cancer samples. Our evaluation highlights the salient differences between these pipelines and shows the divergent results they achieve. References: 1. Kiwala S, Hundal J, …, Griffith M. pVACtools: Computational selection and visualization of neoantigens for personalized cancer vaccine design. Cancer Genetics 2018. 2. Bjerregaard A-M, Nielsen M, ..., Eklund AC. MuPeXI: Prediction of neo-epitopes from tumor sequencing data. Cancer Immunology Immunotherapy 2018. 3. Tappeiner E, Finotello F, ..., Trajanoski Z. TIminer: NGS data mining pipeline for cancer immunology and immunotherapy. Bioinformatics 2017. 4. Rubinsteyn A, Kodysh J, …, Hammerbacher J. Computational pipeline for the PGV-001 Neoantigen Vaccine Trial. Frontiers in Immunology 2018. Citation Format: Julia Kodysh, John P. Finnigan, Alex Rubinsteyn. Evaluation of tools for predicting mutated tumor antigens from exome and RNA sequencing [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B079.