Clinical and genomic predictors of adverse events in newly diagnosed glioblastoma.

BACKGROUND:Adverse clinical events cause significant morbidity in patients with glioblastoma (GBM). We examined whether genomic alterations were associated with adverse events (AEs) in GBM patients. METHODS:We identified adults with histologically confirmed IDH-wildtype GBM with targeted next-generation sequencing (OncoPanel) at Dana Farber Cancer Institute from 2013-2019. Seizure at presentation, lymphopenia, thromboembolic events, pseudoprogression, and early progression (within 6 months of diagnosis) were identified as AEs. The biologic function of genetic variants was categorized as loss-of-function (LoF), no change in function, or gain-of-function (GoF) using a somatic tumor mutation knowledge base (OncoKB) and consensus protein function predictions. Associations between functional genomic alterations and AEs were examined using univariate logistic regressions and multivariable regressions adjusted for additional clinical predictors. RESULTS:470 GBM patients met study criteria. 105 genes both had sequencing data available for ≥90% of patients and were altered in ≥10% of the cohort. Following false-discovery rate (FDR) correction and multivariable adjustment, the TP53, RB1, IGF1R, and DIS3 LoF alterations were associated with lower odds of seizures, while EGFR, SMARCA4, GNA11, BRD4, and TCF3 GoF and SETD2 LoF alterations were associated with higher odds of seizures. For all other AEs of interest, no significant associations were found with genomic alterations following FDR correction. CONCLUSION:Genomic biomarkers based on functional variant analysis of a routine clinical panel may help identify adverse events in GBM, particularly seizures. Identifying these risk factors could improve the management of patients through better supportive care and consideration of prophylactic therapies.