Translational validation of personalized treatment strategy based on genetic characteristics of glioblastoma

Young Taek Oh, Hee Jin Cho, Jinkuk Kim, Ji Hyun Lee, Kyoohyoung Rho, Yun Jee Seo, Yeon Sook Choi, Hye Jin Jung, Hyeon Suk Song, Doo Sik Kong, Ho Jun Seol, Jung Il Lee, Yeup Yoon, Sunghoon Kim, Do Hyun Nam, Kyeung Min Joo

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient's surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMTunmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtypespecific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated.

Original languageEnglish
Article number0103327
JournalPLoS ONE
Volume9
Issue number8
DOIs
StatePublished - 1 Aug 2014

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