Using synthetic dosage lethality to screen for novel anti-tumor targets

描述(由申请人提供)： 癌症治疗中的重大挑战是选择性地杀死癌细胞，同时不伤害正常细胞。需要新的治疗靶点来开发新的癌症药物来实现这一目标。由于易位或基因扩增等机制，癌细胞经常增加特定基因的表达。通过识别只有在特定基因过度表达时才需要功能的基因，可以发现新的治疗靶点。在酵母中，当第二个基因过度表达时，非必需基因变得必不可少的这种相互作用类型被称为合成剂量致死性(SDL)。涉及在癌细胞中过度表达的基因的SDL相互作用可以识别仅在特定癌细胞中必不可少的伴侣基因。然后，用来抑制正常非必需基因功能的药物应该选择性地杀死癌细胞，而不是正常组织中的细胞。因此，识别与癌症相关的SDL相互作用就成了一个问题。 为了加快识别这种SDL相互作用，我们建议使用酵母作为模型系统。在我们的方法中，我们创造了一个酵母细胞，它过度表达人类癌症中过度表达的基因的酵母同源基因。由于许多基本功能在酵母和人类之间是保守的，我们选择了在酿酒酵母中具有功能同源的基因，从一系列在肿瘤细胞中过度表达的有趣的候选基因开始。为了寻找SDL非必需基因，我们使用了4827个成员的酵母基因中断文库。我们已经开发了一种新的方法，通过我们称之为等离子体诱导的过程将任何感兴趣的质粒引入到这个文库中。我们已经证明，这种方法可以用来筛选整个文库，并发现新的遗传相互作用。我们将开发这项技术，以提高鉴定酵母SDL相互作用的吞吐量。然后，我们将展示这些相互作用基因的人类同源基因在人类细胞中定义了类似的相互作用。最后，我们将确定是否可以利用这些相互作用选择性地杀死癌细胞。 这项申请可分为以下具体目标： 1.我们将增加用于测量SDL交互作用的吞吐量，最终允许每年筛选大约125个基因(&gt；600,000个交互作用/年)。首先，我们将集中在与细胞周期调节、检查点、DNA复制和重组有关的基因上，这些基因在肿瘤中过度表达。通过过度表达这些基因的酵母同源基因并筛选酵母缺失文库，我们将确定4827株非必需基因中断菌株中所有潜在的SDL相互作用。然后，来自该屏幕的候选人将被用于目标2和3中描述的实验。 2.在人类细胞中具有明确的同源基因的酵母SDL伙伴将通过建立过度表达人类同源基因的细胞系进行测试。查询基因的。为了验证SDL的相互作用，将通过siRNA降低目的基因在这些细胞系中的表达，并检测细胞的存活率。 3.在人类细胞系中验证的SDL相互作用随后将在查询基因过度表达的癌细胞系中进行测试。目的基因的表达将被siRNA下调，以确定对细胞活力的影响。

DESCRIPTION (provided by applicant): The significant challenge in cancer therapy is to selectively kill cancer cells while not harming normal cells. Novel therapeutic targets are needed to develop new cancer drugs that will achieve this goal. Cancer cells often increase expression of specific genes due to mechanisms such as translocations or gene amplification. New therapeutic targets could be found by identifying genes whose function is required only when a specific gene is over-expressed. In yeast this type of interaction where a non-essential gene becomes essential when a second gene is over-expressed is termed synthetic dosage lethality (SDL). SDL interactions involving genes over-expressed in cancer cells could identify partner genes that are only essential in specific cancer cells. Drugs developed to inhibit function of the normally non-essential genes should then selectively kill cancer cells and not cells from normal tissue. Thus the problem becomes one of identifying cancer-related SDL interactions. To speed the identification of such SDL interactions, we propose to use yeast as a model system. In our approach, we create a yeast cell that over-expresses the yeast ortholog of a gene that is over-expressed in human cancer. Since many essential functions are conserved between yeast and humans, we select genes that have a functional ortholog in Saccharomyces cerevisiae starting from a list of interesting candidate genes that are over-expressed in tumor cells. To search for the SDL non-essential gene, we are using the 4827-member yeast gene disruption library. We have developed a novel method to introduce any plasmid of interest into this library via a process we term plasmoduction. We have shown that this method can be used to screen the entire library and uncover new genetic interactions. We will develop this technology to increase the throughput for identifying yeast SDL interactions. We will then show that human orthologs of these interacting genes define a similar interaction in human cells. Finally, we will determine if these interactions can be exploited to selectively kill cancer cells. The application can be divided into the following specific aims: 1. We will increase the throughput for measuring SDL interactions eventually permitting the screening of approximately 125 genes/year (>600,000 interactions/year). At first we will concentrate on genes that are involved in cell cycle regulation, checkpoints, DNA replication and recombination that are over-expressed in tumors. By over-expressing the yeast orthologs of these genes and screening the yeast deletion library, we will define all potential SDL interactions within the set of 4827 non-essential gene disruption strains. Candidates from this screen will then be used for experiments described in Aims 2 and 3. 2. Yeast SDL partners that have clear orthologs in human cells will be tested by establishing cell lines that over-express the human ortholog. of the query gene. To validate the SDL interaction, expression of the target gene will be reduced by siRNA in these cell lines and cell survival will be assayed. 3. SDL interactions that are validated in human cell lines will then be tested in cancer cell lines that exhibit over-expression of the query gene. Expression of the target gene will be knocked down by siRNA to determine the effect on cell viability.