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Updated: May 8, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
A comparative genomic approach for identifying synthetic lethal interactions in human cancer
Raamesh Deshpande1, Michael K Asiedu, Mitchell Klebig
1Authors' Affiliations: Department of Computer Science and Engineering; Program in Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis; Department of Surgery, Mayo Clinic, Rochester, Minnesota; Department of Laboratory Medicine & Pathology, Molecular Genetics Lab, Mayo Clinic, Rochester, Minnesota; Department of Molecular Genetics, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Ontario, Canada; Chemical Genomics Research Group, RIKEN Advance Science Institute, Saitama, Japan; and Great Lakes Bioenergy Research Center, University of Wisconsin, Madison, Wisconsin.
Abstract:
Synthetic lethal interactions enable a novel approach for discovering specific genetic vulnerabilities in cancer cells that can be exploited for the development of therapeutics. Despite successes in model organisms such as yeast, discovering synthetic lethal interactions on a large scale in human cells remains a significant challenge. We describe a comparative genomic strategy for identifying cancer-relevant synthetic lethal interactions whereby candidate interactions are prioritized on the basis of genetic interaction data available in yeast, followed by targeted testing of candidate interactions in human cell lines. As a proof of principle, we describe two novel synthetic lethal interactions in human cells discovered by this approach, one between the tumor suppressor gene SMARCB1 and PSMA4, and another between alveolar soft-part sarcoma-associated ASPSCR1 and PSMC2. These results suggest therapeutic targets for cancers harboring mutations in SMARCB1 or ASPSCR1 and highlight the potential of a targeted, cross-species strategy for identifying synthetic lethal interactions relevant to human cancer.
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