Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy
UMass Chan AffiliationsProgram in Systems Biology
Immunology and Infectious Disease
Immunoprophylaxis and Therapy
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AbstractMost patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here, we perform a genome-wide in silico prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients' response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.
Mol Syst Biol. 2019 Mar 11;15(3):e8323. doi: 10.15252/msb.20188323. Link to article on publisher's site
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/41008
Full author list omitted for brevity. For the full list of authors, see article.
RightsCopyright 2019 The Authors. Published under the terms of the CC BY 4.0 license. License: This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as Copyright 2019 The Authors. Published under the terms of the CC BY 4.0 license. License: This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.