Abstract 2136: RegTools: Integrative analysis of genomic and transcriptomic data to identify splice altering mutations across 35 cancer types

Abstract

Abstract The interpretation of variants in cancer is often focused on genomic alterations that have a known coding consequence. This analysis strategy excludes somatic mutations in non-coding regions of the genome and even exonic mutations may have unidentified non-coding consequences. To address this issue, we created RegTools, a free, open-source software package that integrates analysis of variant calls from genomic data with evidence of expressed splice junctions from transcriptomic data to efficiently identify variants that may cause aberrant splicing in tumors. To date, we have applied RegTools to over 9,000 samples from TCGA and the McDonnell Genome Institute in an effort to identify somatic variants that are associated with alternative splicing patterns within these tumors. For each mutation, we defined a set of control samples in the same cancer cohort that lacked the particular mutation. We then determined putative splicing-relevant mutations by identifying novel splice isoforms whose expression was significantly elevated in the presence of the associated mutation. To further characterize these somatic variants and their associated splice isoforms, we annotated them with the Variant Effect Predictor (VEP), SpliceAI, and Genotype-Tissue Expression (GTEx) junction counts. While some of these mutations would have been predicted by VEP or SpliceAI to be splicing relevant, our analysis provides additional detail by specifically associating a mutation with an altered junction or junctions, including ones not predicted by VEP/SpliceAI or observed within GTEx normal tissue data. RegTools is freely available and open source (www.regtools.org) and all analysis scripts are provided within the project's GitHub repo (https://github.com/griffithlab/regtools). Citation Format: Kelsy C. Cotto, Yang-Yang Feng, Zachary L. Skidmore, Avinash Ramu, Jason Kunisaki, Donald F. Conrad, Yiing Lin, William Chapman, Ravindra Uppaluri, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith. RegTools: Integrative analysis of genomic and transcriptomic data to identify splice altering mutations across 35 cancer types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2136.