Abstract 566: Neoantigens from translated unannotated open reading frames in cancer
Authors: Tamara Ouspenskaia, Travis E. Law, Karl R. Clauser, Susan Klaeger, Derin B. Keskin, Bo Li, Elena Christian, Yuen Ting Chow, Phuong M. Le, Joshua Gould, Zhe Ji, Wandi Zhang, Pavan Bachireddy, Siranush Sarkizova, Nir Hacohen, Steven A. Carr, Catherine J. Wu, Aviv Regev
Journal: Cancer Research (2019)

Abstract Somatic mutations in cancer cells can generate neoantigens which can be recognized by immune cells and trigger an immune response. Patients vaccinated with neoantigen-based peptides display expanded neoantigen-specific T cells, suggesting that this could be a promising avenue for cancer treatment. Currently, neoantigen predictions are based on mutations detected by whole exome sequencing, which covers a pre-determined set of annotated exons, and often falls short for cancers with few somatic mutations. Ribosome profiling (Ribo-seq), which allows to monitor mRNA translation, has predicted a plethora of translated novel unannotated ORFs (nuORFs). Here we hypothesized that nuORFs can provide another source of neoantigens in cancer cells. In particular, we focused on nuORFs in the following categories: 1) nuORFs expressed in healthy and cancer cells, that have acquired tumor-specific somatic mutations; 2) nuORFs upregulated in or specific to cancer cells. To explore this hypothesis, we performed Ribo-seq on primary healthy and cancer cells and cell lines from melanoma, glioblastoma, colon carcinoma and chronic lymphocytic leukemia. Using this extensive dataset, we performed hierarchical ORF prediction analysis to build a database of highest confidence predicted translated nuORFs across healthy and cancer cell types. To determine if peptides from nuORFs can be a source of antigens, we searched our collection of mono-allelic MHC class I immunopeptidome mass spectrometry (MS) spectra from 94 common HLA alleles against our pan-tissue nuORF database. Additionally, we performed MHC class I immunoprecipitation followed by MS on the same cells used for Ribo-seq. We found HLA-presented unmutated peptides derived from thousands of nuORFs, found within, but out-of-frame with annotated protein-coding ORFs, within 5’ and 3’ untranslated regions of annotated protein-coding transcripts, long non-coding RNAs (lncRNAs), pseudogenes, and other RNA species. The HLA-binding motifs of peptides from nuORFs correspond to the expected motifs for given HLA types, indicating that 1) nuORFs are translated and 2) nuORF-derived peptides are presented on MHC I. To identify tumor-specific somatic mutations in nuORFs, we performed whole genome sequencing on patient-matched healthy and cancer cells and mapped somatic mutations to annotated ORFs and nuORFs. Finally, to identify nuORFs upregulated in or specific to cancer cells, we compared translation levels of nuORFs between healthy and cancer cells of the same origin. We found translated nuORFs with cancer-specific somatic mutations and nuORFs highly upregulated in and specific to cancer cells, suggesting that they can give rise to neoantigens. In conclusion, nuORFs are translated, contribute peptides to MHC I presentation, acquire somatic mutations, are expressed in tissue- and cancer-dependent manner and should be considered in the search for neoantigens in cancer. Citation Format: Tamara Ouspenskaia, Travis E. Law, Karl R. Clauser, Susan Klaeger, Derin B. Keskin, Bo Li, Elena Christian, Yuen Ting Chow, Phuong M. Le, Joshua Gould, Zhe Ji, Wandi Zhang, Pavan Bachireddy, Siranush Sarkizova, Nir Hacohen, Steven A. Carr, Catherine J. Wu, Aviv Regev. Neoantigens from translated unannotated open reading frames in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 566.