The most significant challenge in developing cancer therapies is to selectively kill cancer cells while leaving normal cells unharmed. One approach to specifically target tumors is to exploit gene expression changes specific to cancer cells. For example, synthetic dosage lethal (SDL) interactions occur when increased gene dosage is lethal only in combination with a specific gene disruption. Since cancer cells often specifically over-express a host of gene products, discovering SDL interactions could reveal new therapeutic targets for cancer treatment. In this situation, cancer cells over-expressing a particular gene would be killed when another gene's expression was silenced. Critically, normal cells would be unaffected because the gene whose expression is knocked down is not essential in normal cells.In this study, I describe the use of Saccharomyces cerevisiae as a model system to speed the discovery of cancer relevant SDL interactions. This approach is based on the observation that many genes that are over-expressed in human cancers are involved in essential functions, such as regulation of the cell cycle and DNA replication. Consequently, many of these genes are highly conserved from humans to Saccharomyces cerevisiae and therefore, any SDL discovered through theses screens with a mammalian ortholog is a potential therapeutic cancer target. Using Saccharomyces cerevisiae as a model has several advantages over performing similar screens in mammalian systems, including reduced costs and faster results. For example, a novel technique called Selective Ploidy Ablation (SPA) allows for the completion of a full genome-wide SDL screen in only 6 days. Using SPA to perform SDL screens produces tens of thousands of yeast colonies that must be analyzed appropriately to identify affected mutants. To aid in the data processing, I developed ScreenMill, a suite of software tools that allows the quantification and review of high-throughput screen data. As a companion to ScreenMill, I also developed a tool termed CLIK (Cutoff Linked to Interaction Knowledge), which uses the wealth of known yeast genetic and physical interactions instead of statistical models to inform screen cutoff and evaluate screen results. Together these tools aided in the completion and evaluation of 23 cancer relevant yeast SDL screens. From these screens I prioritized a list of validated SDLs that have human orthologs and thus, represent potential targets for cancer treatment.To understand the mechanism underlying the SDL interaction discovered in one of the screens performed, I analyzed the results from over-expressing NPL3 in more detail. The Npl3 protein plays a role in mRNA processing and translation and its human ortholog, SFRS1 (ASF), is involved in pre-mRNA splicing, mRNA nuclear export and translation and is also up-regulated in PTEN deficient breast cancer. In yeast, over 50 novel SDL interactions with NPL3 were discovered including several with deletions of lysine deactylases (KDACs). These are particularly interesting because KDACs are evolutionarily conserved and are currently being explored as potential anti-cancer drug targets. Furthermore, using several mutant alleles of NPL3, I show that most of the SDL interactions defined are due to its role in the nucleus and are linked to the acetylation state of the Npl3 protein. Thus, by performing SDL screens in yeast, I demonstrate their utility in defining potential cancer relevant drug targets, as well as uncovering novel gene functions.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D89029VH |
| Date | January 2013 |
| Creators | Dittmar, John |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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