CSIG-03INTEGRATING COMPUTATIONAL AND EXPERIMENTAL APPROACHES TO UNDERSTAND THE SMG1 KINASE NETWORK IN GLIOBLASTOMA STEM CELLS

Abstract

The SMG1 kinase was identified and validated from an RNAi screen as a gene that can preferentially inhibit the growth of selected glioblastoma stem cell lines under hypoxia (1% oxygen). In addition, we have found that SMG1 knockdown can substantially enhance the inhibitory effects of the DNA damaging drug, temozolomide (TMZ), both in vitro and in mouse xenografts. In order to evaluate the relative contributions of nonsense mediated decay, the DNA damage response (DDR), and autophagy in the cellular response to SMG1 inhibition, we have used the Cell Collective software platform (BMC Systems Biology, 6, 96) to model the SMG1 signaling network. To do this, we integrating our data with results in the literature in order to simulate the cell growth and survival of GBM stem cells under hypoxia and TMZ induced DNA damage. Our model initially predicted that the preferential growth inhibition of SMG1 inhibition in GS7-2 cells under hypoxia specifically was likely due to the role of NMD pathway in regulating autophagy. We tested the model-generated hypothesis and found induction of the autophagy marker, LC3-II, when SMG1 is knocked down under hypoxia. However, either inhibition of autophagy-related protein, ATG7, or inhibition of NMD pathway does not fully account for the preferential growth inhibition by loss of SMG1 under hypoxia. We have refined the model based on these results and are currently testing the prediction that a defect in the DDR pathway accounts for growth inhibition when SMG1 is knocked down under hypoxia. Our preliminary results indicate greater DNA damage, possibly leading to cell cycle block, when SMG1 is knocked down under hypoxia. The long-term goal of this study will be to develop therapeutic predictions for targeting SMG1 and other kinase targets in a given tumor and in order to develop personalized therapies for GBM.