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Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA)
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 detectabl...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740648/ https://www.ncbi.nlm.nih.gov/pubmed/29183982 http://dx.doi.org/10.1073/pnas.1713362114 |
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author | Housden, Benjamin E. Li, Zhongchi Kelley, Colleen Wang, Yuanli Hu, Yanhui Valvezan, Alexander J. Manning, Brendan D. Perrimon, Norbert |
author_facet | Housden, Benjamin E. Li, Zhongchi Kelley, Colleen Wang, Yuanli Hu, Yanhui Valvezan, Alexander J. Manning, Brendan D. Perrimon, Norbert |
author_sort | Housden, Benjamin E. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5740648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-57406482018-01-22 Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) Housden, Benjamin E. Li, Zhongchi Kelley, Colleen Wang, Yuanli Hu, Yanhui Valvezan, Alexander J. Manning, Brendan D. Perrimon, Norbert Proc Natl Acad Sci U S A PNAS Plus 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. National Academy of Sciences 2017-12-12 2017-11-28 /pmc/articles/PMC5740648/ /pubmed/29183982 http://dx.doi.org/10.1073/pnas.1713362114 Text en Copyright © 2017 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | PNAS Plus Housden, Benjamin E. Li, Zhongchi Kelley, Colleen Wang, Yuanli Hu, Yanhui Valvezan, Alexander J. Manning, Brendan D. Perrimon, Norbert Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) |
title | Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) |
title_full | Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) |
title_fullStr | Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) |
title_full_unstemmed | Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) |
title_short | Improved detection of synthetic lethal interactions in Drosophila cells using variable dose analysis (VDA) |
title_sort | improved detection of synthetic lethal interactions in drosophila cells using variable dose analysis (vda) |
topic | PNAS Plus |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740648/ https://www.ncbi.nlm.nih.gov/pubmed/29183982 http://dx.doi.org/10.1073/pnas.1713362114 |
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