Genome‐wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy. Issue 3 (12th March 2019) - Sahu, Avinash Das; S Lee, Joo; Wang, Zhiyong; Zhang, Gao; Iglesias‐Bartolome, Ramiro; Tian, Tian; Wei, Zhi; Miao, Benchun; Nair, Nishanth Ulhas; Ponomarova, Olga; Friedman, Adam A; Amzallag, Arnaud; et al.
Abstract: Most 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) interac tions, 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. Synopsis: In silico prediction of synthetic rescue genetic interactions identifies gene involved in resistance to targeted immunotherapy, which determines patients' clinical response. Inhibiting predicted genes sensitizes cancer cells to cancer therapies, laying a basis for developing new drug combinations. An in silico method is presented that identifies synthetic rescue genetic interactions whereby the loss of fitness due to the deletion of one gene is compensated by the altered activity of another rescuer gene. Genes are identified that mediate therapy resistance in cancer and that predict clinical response to targeted therapy in patients. Synthetic rescue interactions predict resistance mechanism to immunotherapy and inhibition of rescuer genes sensitizes resistant cancer cells to therapies. Abstract : In silico prediction of synthetic rescue genetic interactions identifies gene involved in resistance to targeted immunotherapy, which determines patients' clinical response. Inhibiting predicted genes sensitizes cancer cells to cancer therapies, laying a basis for developing new drug combinations.