Research Project
7452375
DESCRIPTION (provided by applicant): One of the key features thought to be important in the development of brain tumors is the serial acquisition of mutations that affect critical tumor suppressor genes (TSGs). Although classical TSGs such as p53, RB1 and PTEN have been shown to be mutated in subsets of brain tumors, these genes have also been implicated in most human cancers and still relatively few brain tumor specific TSGs have been identified to date. Unfortunately, positional cloning methods and candidate gene approaches to find TSGs have been very labor intensive and unsuccessful. Clearly, an unbiased, robust and high-throughput method to detect these mutations would accelerate the discovery of these genes and promote a better understanding of brain tumorigenesis, as well as provide potential new targets for therapeutic intervention. Most TSGs are inactivated as a result of either nonsense or frameshift mutations in the coding region. Because this observation is so consistent, finding premature stop codons in candidate genes, therefore, has been the main way of identifying TSGs. Nonsense and frameshift mutations, however, frequently result in the rapid degradation of the mutant mRNA through the mechanism of nonsense mediated decay (NMD). Inhibition of NMD, e.g. by using emetine, results in increased levels of the mutant mRNA in the cell, and we have shown that these mRNAs can then be detected using gene expression arrays because they are present at higher levels than in untreated cells. Unfortunately, the drugs used to inhibit NMD also result in mRNA increases for a large number of transcripts due to stress responses. We have overcome this potential problem to a large extent by incorporating actinomycin D treatment into the protocol, which largely prevents induction of the stress response genes. We now propose to use inhibition of NMD to identify TSGs in gliomas and investigate their functional significance using a combination of cell and molecular biology approaches. These novel genes will significantly improve our understanding of the fundamental events that give rise to gliomas and through the identification of novel biomarkers may ultimately assist in the sub-classification of tumors and the identification of novel therapeutic targets.
