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Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA)

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2017

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National Academy of Sciences
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Housden, Benjamin E., Zhongchi Li, Colleen Kelley, Yuanli Wang, Yanhui Hu, Alexander J. Valvezan, Brendan D. Manning, and Norbert Perrimon. 2017. “Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA).” Proceedings of the National Academy of Sciences of the United States of America 114 (50): E10755-E10762. doi:10.1073/pnas.1713362114. http://dx.doi.org/10.1073/pnas.1713362114.

Abstract

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 TSC1 and TSC2, 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.

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Genetics, synthetic lethality, , RNAi, high-throughput screening, drug target discovery

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