Abstract 176: Detecting neoepitopes from tumor RNA sequencing datasets

Abstract

Abstract Epitopes are peptides that present on the surface of the cell and can be recognized by immune cells to initiate the immune response. Identification of neoepitopes – tumor-specific, MHC-bound epitopes recognized specifically by T-cells – is valuable for predicting response to immunotherapies, including checkpoint blockade therapies. Tumors with more neoepitopes tend to be more responsive to immune checkpoint therapies compared to tumors with fewer neoepitopes. ProTECT is a previously published computational method that uses Illumina whole genome and transcriptome sequencing data from tumor and matched normal tissues to identify neoepitopes. Tumor and normal whole genome sequencing data are used to infer a patient's HLA haplotypes, as well as annotate variants as either somatic or germline. While whole genome sequencing is comprehensive, it is quite costly and not available for many samples. Here we adapt ProTECT to use only tumor RNA sequencing data and HLA haplotype information available to the clinician to identify neoepitopes in a tumor sample. Prior to running ProTECT, we use the computational tools Opossum and Platypus for variant calling instead of Radia (which is designed for variant calling using both RNA and DNA sequencing data as input). To determine which variants are somatic and therefore could represent tumor neoepitopes, variants found in RNA are compared to a panel of normals, for example the Genome Aggregation Database (gnomAD; containing variants from 125,748 exome sequences and 15,708 whole-genome sequences). With the resulting somatic variants and the HLA type, ProTECT proceeds as usual, with translation of variants into proteins, MHC:Peptide binding predictions and neoepitope ranking. We find that high quality neoepitopes are identifiable using an RNA-only approach, when genomic data is absent. Future work will validate the sensitivity of our method by benchmarking it against the original ProTECT predictions in the TCGA Prostate Adenocarcinoma cohort. Citation Format: Drew Thompson, Olena M. Vaske, Arjun Rao, Holly C. Beale. Detecting neoepitopes from tumor RNA sequencing datasets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 176.