Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates

Abstract

AbstractSplicing is dysregulated in many tumors and may result in tumor-specific transcripts that can encode neoantigens, which are promising targets for cancer immunotherapy. Detecting tumor-specific splicing is challenging because many non-canonical splice junctions identified in tumor transcriptomes also appear in healthy tissues.Here, we developed splice2neo to integrate the predicted splice effects from somatic mutations with splice junctions detected in tumor RNA-seq for individual cancer patients. Splice2neo excludes splice junctions from healthy tissue samples, annotates resulting transcript and peptide sequences, and provides targeted re-quantification of supporting RNA-seq reads. We developed a stringent detection rule to predict splice junctions as mutation-derived targets and identified 1.7 target splice junctions per tumor with a false discovery rate below 5% in a melanoma cohort. We confirmed tumor-specificity using independent, healthy tissue samples. Furthermore, using tumor-derived RNA, we confirmed individual exon skipping events experimentally. Most target splice junctions encoded neoepitope candidates with predicted MHC-I or MHC-II binding. Compared to neoepitope candidates derived from non-synonymous point mutations, the splicing-derived MHC-I neoepitope candidates had a lower self-similarity to corresponding wild-type peptides.In conclusion, we demonstrate that identifying mutation-derived and tumor-specific splice junctions can lead to additional neoantigen candidates to expand the target repertoire for cancer immunotherapies.Key Pointssplice2neo is a versatile tool for identifying and analyzing of splice junctions as a source of neoantigen candidatesWe identified mutation-retrieved splice junctions supported by RNA-seq in melanoma samplesThe predicted target splice junctions exhibited a strong tumor-specificity as they were absent in healthy tissues.Target splice junctions often lead to frame-shift peptides and encode promising neoantigen candidates