What Genes Can Tell: A Closer Look at Vestibular Schwannoma. Issue 4 (April 2020)

• Record Type: Journal Article
• Authors: Aaron, Ksenia A.; Manojlovic, Zarko; Tu, Nathan; Xu, Yili; Jin, Yuxin; Chang, Sharon; Kwok, Eric; Webb, Michelle; Hurth, Kyle; Friedman, Rick A.
• Is Part Of: Otology & neurotology. Volume 41:Issue 4(2020)
• Publication Date: 2020-04
• Subjects: Cystic vestibular schwannomas -- Radioresistant vestibular schwannomas -- Vestibular schwannoma -- Whole exome sequence -- Whole-transcriptomic sequencing; Otology -- Periodicals; Ear -- Diseases -- Periodicals; Skull base -- Surgery -- Periodicals; 617.8005
• DOI: 10.1097/MAO.0000000000002580
• Languages: English
• ISSNs: 1531-7129

Abstract

Abstract : Objective: Comprehensive molecular profiling of radioresistant and cystic vestibular schwannoma (VS) subtypes. Study Design: Our study utilized whole-exome sequencing (WES), RNA-sequencing (RNAseq), and correlated clinical data from 12 samples (2 samples of solid sporadic subtype, 8 with cystic changes, and 2 previously irradiated). Setting: Academic medical center. Patients: Patients diagnosed with VS who required surgical treatment. Inclusion: Cystic and radioresistant tumors matched to age and tumor volume, with solid sporadic VS samples as control; Exclusion: NF-2 patients. Intervention(s): WES using custom probes for copy number analysis. A modified version of the Agilent Human Whole Exome sequencing hybrid capture system was used to process samples. Recurrent variants were identified and compared between groups. Leukocyte-derived DNA was utilized as internal control to reduce false-positives. Main Outcome Measure(s): Analysis of genetic landscape of VS subtypes (naive solid VS, cystic VS, and previously irradiated VS) by performing deep next-generation sequencing. Results: WES data achieved a mean coverage of 202X and RNAseq generated an average of 74 million total reads. As a group, 25% of samples had 22q loss. Somatic analysis identified previously reported genes and multiple novel mutations across samples. Differential expression analysis of RNAseq data found significantly mutated genes such as COL6A3, CLMP, ART4, Lumican that were shared by both cystic VS and irradiated VS, but not seen in sporadic VS. Conclusions: Using WES we were able to demonstrate that cystic and irradiated samples are subtypes of VS with an increased mutation burden and a unique genetic fingerprint. We identified differences between the genomic and molecular profile of cystic VS and radioresistant VS. Our results help advance the understanding of the pathophysiology of these tumor subtypes and suggest possible molecular targets for novel treatment strategies. Abstract : Supplemental Digital Content is available in the text