LAUSR

Current annotation methods typically classify mutations as disruptors of splicing if they fall on either the consensus intronic dinucleotide splice donor, GT, or the splice acceptor, AG. As a group, splice site mutations have been presumed to be invariably deleterious because of their disruption of the conserved sequences that are used to identify exon-intron boundaries. While this classification method has been useful, increasing evidence suggests that mutations outside of the canonical splice site can lead to transcriptional changes beyond disruption of the nearest junction. In this study, we have developed the MiSplice pipeline to determine the local and global effects of genomic mutations on splicing across 33 cancer types. To evaluate the local effects of mutations on splicing, we applied MiSplice to identify splice-disrupting mutations (SDMs) and splice-creating mutations (SCMs), genome-wide. We identified 1,964 novel SCMs, of which 26% and 11% were mis-annotated as missense and silent mutations and validated 10 of 11 genes in a mini-gene splicing assay. SDM identification predicted complex splicing patterns associated with canonical splice site mutations and identified a handful of mutations in proximity to the canonical junction that disrupt splicing factor binding sites. Interestingly, further investigation of the novel neoantigens produced by SCMs and SDMs are likely several folds more immunogenic than missense mutations. To explore the global impact of mutations on splicing we focused on recurrent and adjacent mutations disrupting the spliceosomal complex and related splicing factor genes from over 400 curated splice related genes. In addition, we applied HotSpot3D to identify splice-factor mutations (SFMs) that are significantly proximal to one another. Our analysis has identified novel SFMs that disrupt the spliceosomal complex and globally impact downstream splicing targets creating novel peptide sequences and alter key cancer genes. The current study has greatly extended the insight into the transcriptional ramifications of genomic alterations by integrating DNA and RNA sequencing data and painting the portrait of alternative splicing across cancer genomes. Citation Format: Reyka G. Jayasinghe, Song Cao, Qingsong Gao, Matthew A. Wyczalkowski, Sohini Sengupta, Matthew J. Walter, Christopher Maher, Michael C. Wendl, Feng Chen, Eduardo Eyras, Alexander J. Lazar, Ken Chen, Ilya Shmulevich, Li Ding, The Splicing Analysis Working Group. Comprehensive portrait of canonical and non-canonical splicing in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2362.