e14096 Background: Brain tumors are aggressive malignancies with substantial genetic heterogeneity, complicating prognosis and treatment. Comprehensive mutation profiling via next-generation sequencing enables robust molecular classification and identification of prognostic biomarkers and potential therapeutic targets, guiding precision medicine beyond conventional chemotherapy and radiotherapy. Methods: Retrospective analysis of 94 brain tumor samples from patients who opted for CGP with 4baseCare’s comprehensive gene panels. Results: Demographics: Predominantly male (62.7%); 67.0% aged ≥40 years. Histology: Glioblastoma constituted 55% of cases; remaining tumors encompassed diverse gliomas. Mutational landscape: TP53 mutations most frequent (42%), followed by TERT (26%) and PTEN (25%), with TERT/PTEN mutations co-occurring in 11% of samples. Recurrent mutations observed in EGFR , PIK3CA , NF1 , RB1 (each 14%). Additional mutations included MTHFR , POLE , ATM , and MSH6 (approximately 10% each). IDH1 mutations were present in 14% of the cohort, enriched in glioma subtypes; glioblastoma were largely IDH -wild type. Tumor mutational burden (TMB) was low (≤10 mutations/Mb) in majority (91.6%) of samples in a subset (n=48). Conclusions: Brain tumors remain challenging to treat, with targeted and biomarker-guided options currently limited and reliance on conventional chemotherapy for majority of patients. This study defines prognostic and predictive biomarkers that can refine risk stratification and guide therapy in selected patients. Key markers include: RB1 mutations associated with improved overall survival; TERT and PTEN alterations linked to worse prognosis; IDH1 mutations associated with better prognosis and potentially enhanced treatment response; POLE , ATM , and MSH6 alterations indicating potential resistance to temozolomide and implications for alternative strategies; and druggable pathways such as PI3K/AKT/mTOR for biomarker-defined subgroups. Overall, these genomic insights lay the groundwork for integrating CGP into routine brain oncologic care to optimize risk stratification, personalize treatment decisions, and identify candidates for biomarker-guided trials.
Patil et al. (Thu,) studied this question.