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BACKGROUND GBM is characterized by intratumoral heterogeneity. Tumor heterogeneity, clonal diversity and mutation acquisition hamper the ability to tailor personalized therapy for GBM. Tumor sampling has limited ability to accurately capture the molecular landscape of the tumor and to disclose acquired molecular aberrations. Mutation analysis of cfDNA is a non-invasive procedure which may overcome these limitations as it may reflect the real composition of the tumor and track the molecular evolution. We sequenced cfDNA of GBM patients and assessed mutation patterns and fusion genes. METHODS We collected blood and respective tumor samples from 27 GBM patients and blood samples from 14 healthy controls. Tumor DNA, cfDNA and WBC DNA were sequenced using deep sequencing procedures. The data were analyzed for detection of single nucleotide polymorphism (SNPs) and gene-gene fusions. RESULTS GBM cfDNA concentrations were significantly elevated (median: 23.63 ng/mL; range 12.6–137) compared to healthy controls (median 2.06; range 1.68–7.62) (p < 0.0001). We identified unique SNPs in each glioma patient’s cfDNA and the corresponding tumor DNA including the top-10 most frequently mutated genes in GBM. For example, mutation of TP53 was detected in18.75%; EGFR in 37.5%; NF1-12.5%; LRP1B-25% and IRS4 in 25%. For gene-gene fusion we used the in-house fusion gene database, ChiTaRS 5.0, and identified fusions in cfDNA and tumor DNA. Thus, KMT2A-FLNA was the most frequent fusion found in 16.4% of samples. BCR-ABL1 in 8.82% and FGFR1-BCR in 2.94%. Other fusions included COL1A1-PDGFB (5.88%), NIN-PDGFRB (5.88%), KIF5B-RET (5.88%) and also TPM3-ROS1(2.94%), TFG-ALK(2.94%), MSN-ALK (2.94%) and NPM1-ALK (2.94%) which may be targeted by brain penetrating drugs that are ROS1 and ALK inhibitors. CONCLUSIONS Our study suggests that plasma cfDNA analysis may help to uncover real time mutational and gene fusion status of GBM by a non-invasive procedure. It may identify drug targets based on personalized gene-gene fusions.