Despite the revolutionary biotechnological advancements of the last few decades, an ideal anti-cancer treatment — one that is immediately lethal to cancer cells, harmless to healthy cells, and resistant to cancer's relapse — is still a dream. But a concept called "synthetic lethality" holds great promise for researchers. Two genes are considered synthetically lethal when their combined inactivation is lethal to cells, while inhibiting just one of them is not. Synthetic lethality promises to deliver personalized, more effective, and less toxic therapy. If a particular gene is found to be inactive in a tumor, then inhibiting its synthetic lethal partner with a drug is likely to kill only the cancer cells, causing little damage to healthy cells. While this promising approach has been widely anticipated for almost two decades, its potential could not be realized due to the difficulty of experimentally identifying synthetic lethal pairs in cancer. Now new research published in the August 28, 2014 issue of Cell overcomes this fundamental hurdle and presents a novel strategy for identifying synthetic lethal pairs in cancer with the potential to bust cancer cells. Tel Aviv University (TAU) researchers, together with collaborators at The Beatson Institute for Cancer Research (Cancer Research UK) and the Broad Institute of Harvard and MIT, have developed a computational data-driven algorithm, which identifies synthetic lethal interactions. In their comprehensive, multidisciplinary study, Dr. Eytan Ruppin of TAU's Blavatnik School of Computer Science and the Sackler School of Medicine and Ms. Livnat Jerby-Arnon of TAU's Blavatnik School of Computer Science worked together with other researchers from TAU, The Beatson Institute for Cancer Research (Cancer Research UK), and the Broad Institute of Harvard and MIT.
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