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

  1. Norbert Perrimonb,d,1
  1. aLiving Systems Institute, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom EX4 4QD;
  2. bDepartment of Genetics, Harvard Medical School, Boston, MA 02115;
  3. cDepartment of Genetics and Complex Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115;
  4. dHoward Hughes Medical Institute, Boston, MA 02115
  1. Contributed by Norbert Perrimon, November 1, 2017 (sent for review August 1, 2017; reviewed by John G. Doench and Jeffrey P. MacKeigan)

Significance

Synthetic sick or lethal (SS/L) interactions occur when disruption of two genes reduces cell viability to a greater extent than expected based on the individual gene disruptions. SS/L interactions involving tumor suppressors represent candidate drug targets for cancers because treatment is expected to kill tumor cells carrying the tumor suppressor mutation but leave healthy cells unaffected. Identification of SS/L interactions is of vital importance to develop new therapies for tumorigenic disease. We have developed an RNAi-based approach called variable dose analysis, which improves both sensitivity and robustness to noise compared with dsRNA-based methods for screening in Drosophila. Using this method, we identified four Food and Drug Administration-approved drugs with specific effects on cells deficient for the TSC1 and TSC2 tumor suppressor genes.

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.

Footnotes

  • ?1To whom correspondence may be addressed. Email: b.housden{at}exeter.ac.uk or perrimon{at}genetics.med.harvard.edu.

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