Accurately Identifying Neoantigens Utilizing Both Dna And Rna Somatic Variants In An Enhanced Platform

The identification of neoantigens is a crucial step in the development of neoantigen-based personalized cancer vaccines and other immunotherapies. Accurately predicting which neoantigens are likely to be immunogenic remains a key challenge owing to the complex processes involved in determining neoantigen immunogenicity including the antigen presenting machinery, likelihood of MHC class I and II binding, similarity to self, and ability to interact with the TCR. We have developed a neoantigen detection pipeline built upon our analytically validated Accuracy and Content Enhanced (ACE) Exome and Transcriptome sequencing platform and somatic variants calling pipeline through combined DNA and RNA analysis. The analytical performance of these pipelines is greater than u003e97% sensitivity for small variants (RNA and DNA) with a specificity of u003e98% (DNA) and a fusion sensitivity of u003e99% (RNA). Within our neoantigen pipeline, variants that are detected by our DNA and RNA cancer analysis pipelines are processed for antigen identification, including SNVs, indels, and fusion events. Importantly, both in-frame and out-of-frame events are accurately considered by transcript, allowing for detection of a wealth of candidate neoantigens. Our pipeline includes assessment of important immunologic components including HLA prediction, MHC binding (class I and II), immunogenicity, similarity to self, and similarity to known antigens. Additionally, peptides are evaluated for variant allele frequency in both the RNA and DNA of the tumor sample and gene expression level is considered. Collectively, our ImmunoID product provides a comprehensive assessment of features that may be used for identifying and ranking potentially immunogenic neoantigens. To assess the effectiveness of this pipeline in predicting immunogenic neoantigens, we assembled a gold-set of 23 known, previously experimentally-validated immunogenic neoantigens from the literature. We spiked in these neoepitopes into exome data and assessed the ability of our neoantigen pipeline to find and rank these immunogenic known neoantigens. Preliminary results show our neoantigen pipeline is able to accurately identify 22 out of 23 (~96%) of the spiked in neoantigens as being potentially immunogenic. Citation Format: Sean M. Boyle, Jason Harris, Gabor Bartha, Ravi Alla, Mirian Karbelashvili, Steve Chervitz, Aldrin Montana, Craig Rowell, Patrick Jonganeel, Scott Kirk, Rena McClory, John West, Rich Chen. Accurately identifying neoantigens utilizing both DNA and RNA somatic variants in an enhanced platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 554. doi:10.1158/1538-7445.AM2017-554