More importantly, GBM was sub-classified into 4 different subtypes by integrating multi-dimensional data; gene expression, somatic mutations, and DNA copy number, which had differential clinical responses to chemo-radiation therapy. In order to find out optimal drugs that target 4 different GBM subtypes-specific genes, an integrated pharmacological network database called PharmDB was used. Previously, we developed the patientspecific orthotopic GBM xenograft Phenacetin animal models that predict and mimic patients molecular/histopathological phenotypes and clinical treatment responses. When these mouse platforms maintain the molecular subtypes of parent GBMs, the personalized treatments based on genomic characteristics could be examined translationally. In this study, we performed preclinical validation of personalized treatments for each GBM subtype with the drugs suggested by PharmDB using the patient-derived orthotopic xenograft models representing GBM subtypes. In this study, we translationally tried experimental personalized treatment based on the molecular characteristics against several patient-derived GBM cells and found that the personalized treatment could show significant inhibition effects on the in vitro clonogenicity and reverse the resistance to TMZ chemotherapy. Genomic signature-based classification and differential clinical outcome of TCGA GBMs have provoked personalized Sulisobenzone treatment of GBMs based on their genomic characteristics.The experimental personalized treatment was composed of 1) determination of molecular subtype of GBM patients 2) specific drug combinations that are associated with molecular subtyperelated genes, and 3) translational platforms that mimic genetic and functional phenotype of parental patient tumors. For the determination of molecular subtypes of parental GBMs and corresponding orthotopic xenograft tumors, we have adopted and validated a multiple classification, NTP method.If we use the NTP method, we could identify consistent subtype of not only TCGA but also our institutios GBMs. In addition, we further proved that the NTP method is compatible with classifying different types of orthotopic xenograft GBM tumors derived from GBM patients surgical samples.