INTEGRATIVE ANALYSIS OF DIFFERENTIALLY REGULATED PROTEINS IN MENINGIOMA

Abstract

Abstract AIMS Meningiomas are common primary intracranial tumours that arise from meninges. loss of chromosome 22q is common genetic event observed in meningiomas. About 50% of meningiomas harbour mutations in NF2 gene that resides on chromosome 22. Moreover, frequent mutations have been observed in AKT1, KLF4, TRAF7, and SMO genes. Meningiomas are divided into different genomic subgroups that express unique proteomic profiles. This study aims to investigate genomic background of meningioma and to determine the impact of mutations on underlying protein expression to identify druggable targets. METHOD Total 96 meningioma samples were sequenced using Illumina TruSight Oncology 500 panel. The raw sequence data was analyzed using TSO500 App. The variant data was annotated using Cancer Genome Interpreter and ANNOVAR. Clinical enrichment analysis was performed to investigate common pathways. Genomic data was correlated with LC-MS based proteomic data to determine variants effect on downstream processes. RESULTS Results showed an average of 1083 total and 7 driver mutations per sample. NF2 gene was found among highly mutated genes in tumour samples. Almost all NF2 mutations were frameshift, splice site and nonsense mutations, previously reported to be associated with high rate of multiple and recurring meningiomas. Additionally, driver mutations were identified in known meningioma genes including AKT1, KLF4, and TRAF7 along with previously unpublished mutations in ERBB2, MET, ARID5B, etc. The results correlate with tumour location, grade, and histopathological subtype. CONCLUSIONS The study identified common as well as unique driver mutations in meningioma samples. After functional validation, novel driver mutations could further enhance personalized treatment for meningioma patients.