BIOM-47. PREDICTORS OF SEIZURE AT ONSET USING A FUNCTIONAL VARIANT ANALYSIS OF TARGETED NEXT GENERATION SEQUENCING IN GBM

Abstract BACKGROUND Adverse events (AE) including seizures cause significant morbidity in patients with GBM. We propose a novel method for assessing genomic predictors of AEs using results from clinical targeted sequencing platform variant function analysis. METHODS identified 1,011 consecutive adult newly diagnosed, histologically confirmed IDH-wildtype GBM exome NGS (Oncopanel) at Dana-Farber Cancer Institute 2013-2019. Seizure presentation was retrospectively as an AE. Biologic (high loss, low neutral, gain and high gain) assigned to variants three-tiered approach leveraging genetic database (OncoKB), followed by analysis protein prediction tools (Sift, Polyphen2 Provean). Univariate logistic regression performed each relevant altered gene against the outcome interest false-discovery rate correction. Genes associated seizure were included iteratively multivariate model other outcome. RESULTS Our 470 107 genes 12 whole chromosome or arm level candidate covered all versions Oncopanel >10% alteration. occurred 143/463 (31%) EGFR amplification (OR: 2.76, 95% CI: 1.4-5.3, p = 0.04). In (including age, sex, preoperative tumor volume), remained statistically 1.5, 1.0-2.2, 0.03). CONCLUSION Genomic biomarkers based on functional routine panel may predict adverse independently amplification. ongoing will look myelosuppression, thromboembolism, pseudoprogression early progression similar approach. Identifying molecular risk factors could improve management through supportive care consideration prophylactic therapies.