PATH-54. UTILITY OF NEXT GENERATION SEQUENCING IN ADULT PRIMARY BRAIN TUMORS: IMPACT ON DIAGNOSIS AND PERSONALIZED THERAPY. (5th November 2018) - Smith-Cohn, Matthew; Colman, Howard; Cohen, Adam
Abstract: BACKGROUND: Historically, the molecular characterization of gliomas and other brain tumors has been controversial. A diagnosis was primarily made by histological analysis alone, despite concordance among neuropathologists being as low as 52% in some cases. Based on the 2016 World Health Organization guideline update, molecular profiling of brain tumors is now considered best practice for central nervous system tumors. In addition to providing a more accurate diagnosis, next generation sequencing of brain tumors can identify molecular alterations amenable to targeted therapy. METHODS: A retrospective chart review of 251 adult primary brain tumor patients with next generation sequencing performed was conducted at a single institution. Comparison of histological and molecular diagnosis, identification of potentially actionable alterations, and treatment choice based on alterations was analyzed. RESULTS: Clarification of diagnoses was observed in gliomas, but sequencing did not alter diagnosis in ependymomas, meningiomas, or medulloblastomas. Excluding ependymomas, there were 220 gliomas, of which 33 cases (15%) had clarification of the diagnosis. Of these 33 cases, 18 instances had clarification of IDH mutation status and the remaining 15 had a different or narrowed diagnosis based on the molecular features. Potentially actionable molecular alterations were found in 60% (150/251) of patients including CDKN2A/B, CDK4, EGFRvIII, BRAF, BRCA2, SMO, PTCH1, hypermutator genes ( MSH2, MSK6, PMS2, MLH1 ), and increased mutation burden. Patients were treated with therapies targeting at least one actionable alteration in 9% of all cases (22/251). CONCLUSIONS: This study validates next generation sequencing as a clinical tool to obtain an accurate diagnosis and identify targetable alterations in brain tumor patients which have an impact on treatment decisions. These data support that integration of this technology will be essential in clinical trials exploring personalized therapy in neuro-oncology patients.