Abstract 1678: Accurate detection of expressed variation in RNA-seq

Abstract Somatic variant detection has long been an area of great interest and critical importance in cancer research and treatment. DNA-Seq based somatic variant calling pipelines have been maturing over the last several years and although there is still room for improvement, several methods have been developed capable of accurately detecting somatic variants from matched tumor/normal DNA. RNA-Seq has become a widely used tool for measuring gene and isoform abundance, identifying alternative splicing, and detection of gene fusions. Detection of expressed variation is receiving growing interest, however computational methods to detect this variation have received far less attention than that of DNA-Seq. We have developed an optimized RNA-Seq pipeline based upon the ABRA2 realigner capable of accurately detecting expressed somatic variation in RNA-Seq. We applied this pipeline to the TCGA Breast Cancer dataset. To assess the impact of identification of expressed variation as an indicator of variant significance, we compared the expression state of the top 20 cohort wide significantly mutated genes (SMG) as identified by The Cancer Genome Atlas Network (2012) with all other genes. At the median for SMGs, 23 somatic variants are expressed with over 90% of variants detected in DNA being expressed. For non-SMGs, the median number of expressed variants is 1 and the median fraction of expressed variants is 50%. Among non-SMGs, a total of six genes exceed the median total number of expressed variants and fraction of expressed variants for SMGs (AHNAK, CHD4, ERBB2, FASN, FOXA1 and MYH9). All of these variants have been previously implicated in breast cancer, however none of these variants were among the cohort wide SMGs identified in the original study and only FOXA1 was identified as being a subtype specific SMG (ER+,ER+/HER2-). Notably, variants in the massive TTN gene are found to be coding 73% of the time, but expressed in only 8% of cases. This is substantially less than the 90% found in SMGs and a likely indicator that TTN mutations are passenger variants. The median and third quartile RNA variant allele frequency (VAF) for SMGs is .41 and .69 versus .32 and .46 for DNA. By comparison, the median and third quartile VAF for non-SMGS was 0 and .27 in RNA and .20 and .30 for DNA. The increased VAF for RNA SMGs is a likely indicator of selection and can potentially further be used to identify variants of significance. We believe these results demonstrate the utility of variant expression as a potentail tool to aid in assessment of variant significance. Citation Format: Lisle E. Mose, David Marron, Joel S. Parker. Accurate detection of expressed variation in RNA-seq [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 1678.