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

利用合成剂量致死率筛选新型抗肿瘤靶点

• 批准号: 7414719
• 负责人: Rodney J. ROTHSTEIN
• 金额: $ 38.19万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-05-01 至 2010-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7414719
• 关键词: Antineoplastic Agents; Biological Assay; Biological Models; Cancer cell line; Candidate Disease Gene; Cell Cycle Regulation; Cell Line; Cell Survival; Cells; DNA biosynthesis; Disruption; Essential Genes; Exhibits; Gene Amplification; Gene Targeting; Genes; Genetic; Genetic Recombination; Goals; Human; Human Cell Line; Libraries; Malignant Neoplasms; Measures; Methods; Normal Cell; Normal tissue morphology; Orthologous Gene; Pharmaceutical Preparations; Plasmids; Process; Saccharomyces cerevisiae; Screening procedure; Small Interfering RNA; Speed; Technology; Testing; Yeasts; cancer cell; cancer therapy; deletion library; dosage; established cell line; interest; killings; knock-down; member; neoplastic cell; novel; novel therapeutics; research study; therapeutic target; tumor

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.

描述（由申请人提供）： 癌症治疗的重大挑战是选择性地杀死癌细胞，而不损害正常细胞。需要新的治疗靶标以开发将实现这一目标的新癌症药物。由于易位或基因扩增等机制，癌细胞通常会增加特定基因的表达。只有在特定基因过表达时，才能通过识别其功能需要的基因来找到新的治疗靶标。在酵母中，这种类型的相互作用，当第二个基因过表达时，非必需的基因被称为合成剂量致死性（SDL）。涉及在癌细胞中过表达基因的SDL相互作用可以鉴定仅在特定癌细胞中必不可少的伴侣基因。然后，为抑制正常非必需基因的功能而开发的药物应有选择地杀死癌细胞，而不是正常组织中的细胞。因此，问题成为鉴定与癌症相关的SDL相互作用之一。 为了加快这种SDL相互作用的识别，我们建议将酵母用作模型系统。在我们的方法中，我们创建了一个酵母细胞，该细胞过表达了在人类癌症中过表达的基因的酵母直系同源物。由于酵母和人类之间的许多基本功能是保守的，因此我们选择在酿酒酵母中具有功能性直系同源物的基因，从在肿瘤细胞中过表达的有趣候选基因列表开始。为了搜索SDL非必需基因，我们使用了4827成员的酵母基因破坏库。我们已经开发了一种新颖的方法，可以通过我们称量质量量的过程将任何感兴趣的质粒引入该库中。我们已经表明，该方法可用于筛选整个库并发现新的遗传相互作用。我们将开发这项技术，以增加鉴定酵母SDL相互作用的吞吐量。然后，我们将证明这些相互作用基因的人类直系同源物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来选择性地杀死癌细胞。 该应用程序可以分为以下特定目的： 1。我们将增加测量SDL相互作用的吞吐量最终允许筛选约125个基因/年（> 600,000个相互作用/年）。首先，我们将集中于与细胞周期调节，检查点，DNA复制和重组中涉及的基因，这些基因在肿瘤中过表达。通过过度表达这些基因的酵母直系同源物并筛选酵母缺失库，我们将在4827个非必需基因破坏菌株集中定义所有潜在的SDL相互作用。然后，该屏幕的候选物将用于AIM 2和3中描述的实验。 2.在人类细胞中具有清晰直系同源物的酵母SDL伴侣将通过建立过表达人类直系同源物的细胞系进行测试。查询基因。为了验证SDL相互作用，将在这些细胞系中siRNA降低靶基因的表达，并将分析细胞存活。 3。在人类细胞系中验证的SDL相互作用将在表现出过表达的疑问基因的癌细胞系中进行测试。靶基因的表达将被siRNA击倒，以确定对细胞活力的影响。