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Computational repositioning and preclinical validation of mifepristone for human vestibular schwannoma.


ABSTRACT: The computational repositioning of existing drugs represents an appealing avenue for identifying effective compounds to treat diseases with no FDA-approved pharmacotherapies. Here we present the largest meta-analysis to date of differential gene expression in human vestibular schwannoma (VS), a debilitating intracranial tumor, and use these data to inform the first application of algorithm-based drug repositioning for this tumor class. We apply an open-source computational drug repositioning platform to gene expression data from 80 patient tumors and identify eight promising FDA-approved drugs with potential for repurposing in VS. Of these eight, mifepristone, a progesterone and glucocorticoid receptor antagonist, consistently and adversely affects the morphology, metabolic activity, and proliferation of primary human VS cells and HEI-193 human schwannoma cells. Mifepristone treatment reduces VS cell viability more significantly than cells derived from patient meningiomas, while healthy human Schwann cells remain unaffected. Our data recommend a Phase II clinical trial of mifepristone in VS.

SUBMITTER: Sagers JE 

PROVIDER: S-EPMC5882888 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Computational repositioning and preclinical validation of mifepristone for human vestibular schwannoma.

Sagers Jessica E JE   Brown Adam S AS   Vasilijic Sasa S   Lewis Rebecca M RM   Sahin Mehmet I MI   Landegger Lukas D LD   Perlis Roy H RH   Kohane Isaac S IS   Welling D Bradley DB   Patel Chirag J CJ   Stankovic Konstantina M KM  

Scientific reports 20180403 1


The computational repositioning of existing drugs represents an appealing avenue for identifying effective compounds to treat diseases with no FDA-approved pharmacotherapies. Here we present the largest meta-analysis to date of differential gene expression in human vestibular schwannoma (VS), a debilitating intracranial tumor, and use these data to inform the first application of algorithm-based drug repositioning for this tumor class. We apply an open-source computational drug repositioning pla  ...[more]

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