Abstract 5248: Expression of somatic alleles in TCGA data reveals allelic imbalance with implications for treatment and survival
Authors: Bailey Shannon T. , Lund Jim , Gulcher Jeffrey R. 
Published: August 2019

Abstract
Next-generation technologies, including whole-genome sequencing of DNA and RNA, have facilitated the identification of different cancer subclasses and genes responsible for tumor growth and progression, and guide the application of targeted therapies for personalized medicine. In this study, we employ a novel, combined approach for assessing cancer mutations.
As standard practice, our group inspects individual DNA sequencing reads underlying each somatic mutation call to assess quality and confirm calls made by variant calling algorithms. This approach provides confidence in identifying likely candidate driver genes while eliminating calls unsupported by aligned reads. We have recently expanded this method to include the assessment of RNA variants as well. In this approach, called DNA mutations are inspected in sequencing reads from both DNA and RNA.
In analysis of 850 tumors from the TCGA breast cancer dataset, we observed inconsistent levels of mutation expression i.e., RNA imbalance, where only less than half of the mutations identified have similar variant call ratios in both RNA and DNA. We observe three types of RNA allelic imbalance: higher RNA mutation call ratios compared to that in DNA, higher DNA mutation call ratios compared to that in RNA, and RNA expression where the DNA mutation is absent. We also observe sites where a mutation is present in DNA, but the RNA is not expressed. Notably, we found a patient with a E545K mutation in PIK3CA DNA that was not expressed in the RNA, suggesting that treatment with PI3 kinase inhibitors will be ineffective for this patient.
When analyzing the most commonly mutated genes in this cohort, we found that the mutation expression patterns are not random but specific to individual genes. For example, GATA3 mutations are almost always expressed with a higher RNA call ratio, BRCA1 and LRP6 mutations are rarely expressed, and PIK3CA mutations are almost always expressed with the same call ratio. We also noticed differences in survival patterns with the different categories of RNA expression for certain genes. We found that patients with higher RNA call ratios in GATA3 have better overall survival compared with patients that have lower RNA call ratios, which is consistent with reported better survival outcome for patients with GATA3 mutations. We also observed that patients with lower RNA mutation call ratios in TP53 had better survival, and those with higher MAP3K1 call ratios had better overall survival.
As DNA and RNA are commonly assayed in cancer studies such as TCGA, we present a novel, combined approach for better identifying mutations of interest. We believe this approach provides an improved methodology for assessing mutations in patients and providing insight into patient outcome. These results also suggest caution when evaluating DNA alone and the necessity for confirming the expression of mutations in RNA.
Citation Format: Shannon T. Bailey, Jim Lund, Jeffrey R. Gulcher. Expression of somatic alleles in TCGA data reveals allelic imbalance with implications for treatment and survival [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 5248.