期刊论文详细信息
BMC Genomics
Towards precision medicine-based therapies for glioblastoma: interrogating human disease genomics and mouse phenotypes
Research
Zhen Gao1  Rong Xu1  Yang Chen1  Bingcheng Wang2 
[1] Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA;Department of Pharmacology, Case Western Reserve University, Cleveland, Ohio, USA;
关键词: Glioblastoma;    Drug repositioning;    Cancer genomics;    Mouse phenotype;   
DOI  :  10.1186/s12864-016-2908-7
来源: Springer
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【 摘 要 】

BackgroundGlioblastoma (GBM) is the most common and aggressive brain tumors. It has poor prognosis even with optimal radio- and chemo-therapies. Since GBM is highly heterogeneous, drugs that target on specific molecular profiles of individual tumors may achieve maximized efficacy. Currently, the Cancer Genome Atlas (TCGA) projects have identified hundreds of GBM-associated genes. We develop a drug repositioning approach combining disease genomics and mouse phenotype data towards predicting targeted therapies for GBM.MethodsWe first identified disease specific mouse phenotypes using the most recently discovered GBM genes. Then we systematically searched all FDA-approved drugs for candidates that share similar mouse phenotype profiles with GBM. We evaluated the ranks for approved and novel GBM drugs, and compared with an existing approach, which also use the mouse phenotype data but not the disease genomics data.ResultsWe achieved significantly higher ranks for the approved and novel GBM drugs than the earlier approach. For all positive examples of GBM drugs, we achieved a median rank of 9.2 45.6 of the top predictions have been demonstrated effective in inhibiting the growth of human GBM cells.ConclusionWe developed a computational drug repositioning approach based on both genomic and phenotypic data. Our approach prioritized existing GBM drugs and outperformed a recent approach. Overall, our approach shows potential in discovering new targeted therapies for GBM.

【 授权许可】

CC BY   
© The Author(s) 2016

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