Identification Of Recurrent Somatic Splice Site Variants Across Multiple Clear Cell Renal Cell Carcinoma Cohorts

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology I (MP39)1 Sep 2021MP39-14 IDENTIFICATION OF RECURRENT SOMATIC SPLICE SITE VARIANTS ACROSS MULTIPLE CLEAR CELL RENAL CELL CARCINOMA COHORTS Nicholas Chakiryan, Timothy Robinson, Dongliang Du, Ali Hajiran, Logan Zemp, Youngchul Kim, Jad Chahoud, Philippe Spiess, Liang Wang, James Mule, and Brandon Manley Nicholas ChakiryanNicholas Chakiryan More articles by this author , Timothy RobinsonTimothy Robinson More articles by this author , Dongliang DuDongliang Du More articles by this author , Ali HajiranAli Hajiran More articles by this author , Logan ZempLogan Zemp More articles by this author , Youngchul KimYoungchul Kim More articles by this author , Jad ChahoudJad Chahoud More articles by this author , Philippe SpiessPhilippe Spiess More articles by this author , Liang WangLiang Wang More articles by this author , James MuleJames Mule More articles by this author , and Brandon ManleyBrandon Manley More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002054.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Splice-site variants (SV) are DNA mutations that ultimately result in abnormal mRNA splicing and a dramatically altered protein-coding sequence. SVs in clear cell renal cell carcinoma (ccRCC) have been largely unexplored. Our primary objective was to identify the most prevalent SVs in ccRCC, and determine their prevalence in other malignancies and adjacent normal kidney tissue. METHODS: Specific SVs were identified in RCC cell lines from the Broad Institute Cancer Cell Line Encyclopedia. Patients with a diagnosis of ccRCC were then identified in the Moffitt Cancer Center Total Cancer Care (TCC) cohort and RNA-seq data was utilized in a bioinformatics pipeline to identify the SVs among the TCC cohort. SVs identified in the TCC ccRCC cohort were then identified in TCC patients with non-ccRCC malignancies. This process was then repeated for the ccRCC RNA-seq data from CPTAC and TCGA, as well as from adjacent normal kidney tissue from these data sets. The most prevalent SVs among the ccRCC were selected for analysis, using a minimum SV read count threshold of 10. RESULTS: Among the three ccRCC datasets, 756 patients with ccRCC tumor samples were identified (N: TCC 104, CPTAC 111, TCGA 541). Eight distinct SVs were found to have high ccRCC prevalence and low prevalence in adjacent normal kidney tissue and non-ccRCC malignancies (Figure 1A). Genes with multiple distinct SVs were classified separately. The GAL3ST1-a and GAL3ST1-b SVs had the highest prevalence in ccRCC, as well as the highest read count per patient (Figure 1B). In the TCC ccRCC cohort, low read counts of SVs from the GAL3ST1 gene were associated with stage cM1. CONCLUSIONS: We identified eight novel SVs that are highly prevalent in ccRCC tumors and minimally prevalent in adjacent normal kidney tissue and other malignancies. Particularly striking were four distinct SVs affecting the the GAL3ST1 gene. These novel SVs warrant further investigation as potential biomarkers in ccRCC. Source of Funding: N/A © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e709-e710 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nicholas Chakiryan More articles by this author Timothy Robinson More articles by this author Dongliang Du More articles by this author Ali Hajiran More articles by this author Logan Zemp More articles by this author Youngchul Kim More articles by this author Jad Chahoud More articles by this author Philippe Spiess More articles by this author Liang Wang More articles by this author James Mule More articles by this author Brandon Manley More articles by this author Expand All Advertisement PDF downloadLoading ...