Living Systems Institute, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom EX4 4QD;
Department of Genetics, Harvard Medical School, Boston, MA 02115.
Proc Natl Acad Sci U S A. 2017 Dec 12;114(50):E10755-E10762. doi: 10.1073/pnas.1713362114. Epub 2017 Nov 28.
Synthetic sick or synthetic lethal (SS/L) screens are a powerful way to identify candidate drug targets to specifically kill tumor cells, but this approach generally suffers from low consistency between screens. We found that many SS/L interactions involve essential genes and are therefore detectable within a limited range of knockdown efficiency. Such interactions are often missed by overly efficient RNAi reagents. We therefore developed an assay that measures viability over a range of knockdown efficiency within a cell population. This method, called Variable Dose Analysis (VDA), is highly sensitive to viability phenotypes and reproducibly detects SS/L interactions. We applied the VDA method to search for SS/L interactions with and , the two tumor suppressors underlying tuberous sclerosis complex (TSC), and generated a SS/L network for TSC. Using this network, we identified four Food and Drug Administration-approved drugs that selectively affect viability of TSC-deficient cells, representing promising candidates for repurposing to treat TSC-related tumors.
合成性疾病或合成致死(SS/L)筛选是一种识别候选药物靶点以特异性杀死肿瘤细胞的有效方法,但这种方法通常在筛选结果之间一致性较差。我们发现,许多 SS/L 相互作用涉及必需基因,因此在有限的敲低效率范围内可检测到。这种相互作用通常会被效率过高的 RNAi 试剂所忽略。因此,我们开发了一种在细胞群中测量一系列敲低效率下的存活能力的测定方法。这种方法称为可变剂量分析(VDA),对存活能力表型非常敏感,可重复性地检测 SS/L 相互作用。我们将 VDA 方法应用于搜索 和 ,即结节性硬化症(TSC)的两个肿瘤抑制因子,以生成 TSC 的 SS/L 网络。使用这个网络,我们鉴定出四种经美国食品和药物管理局批准的药物,它们选择性地影响 TSC 缺陷细胞的活力,这代表了重新用于治疗 TSC 相关肿瘤的有希望的候选药物。