A molecular screening approach to identify and characterize inhibitors of glioblastoma stem cells.

Koppany Visnyei, Hideyuki Onodera, Robert Damoiseaux, Kuniyasu Saigusa, Syuzanna Petrosyan, David De Vries, Denise Ferrari, Jonathan Saxe, Eduard H Panosyan, Michael Masterman-Smith, Jack Mottahedeh, Kenneth A Bradley, Jing Huang, Chiara Sabatti, Ichiro Nakano, Harley I Kornblum

文献索引：Mol. Cancer Ther. 10(10) , 1818-28, (2011)

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摘要

Glioblastoma (GBM) is among the most lethal of all cancers. GBM consist of a heterogeneous population of tumor cells among which a tumor-initiating and treatment-resistant subpopulation, here termed GBM stem cells, have been identified as primary therapeutic targets. Here, we describe a high-throughput small molecule screening approach that enables the identification and characterization of chemical compounds that are effective against GBM stem cells. The paradigm uses a tissue culture model to enrich for GBM stem cells derived from human GBM resections and combines a phenotype-based screen with gene target-specific screens for compound identification. We used 31,624 small molecules from 7 chemical libraries that we characterized and ranked based on their effect on a panel of GBM stem cell-enriched cultures and their effect on the expression of a module of genes whose expression negatively correlates with clinical outcome: MELK, ASPM, TOP2A, and FOXM1b. Of the 11 compounds meeting criteria for exerting differential effects across cell types used, 4 compounds showed selectivity by inhibiting multiple GBM stem cells-enriched cultures compared with nonenriched cultures: emetine, n-arachidonoyl dopamine, n-oleoyldopamine (OLDA), and n-palmitoyl dopamine. ChemBridge compounds #5560509 and #5256360 inhibited the expression of the 4 mitotic module genes. OLDA, emetine, and compounds #5560509 and #5256360 were chosen for more detailed study and inhibited GBM stem cells in self-renewal assays in vitro and in a xenograft model in vivo. These studies show that our screening strategy provides potential candidates and a blueprint for lead compound identification in larger scale screens or screens involving other cancer types.