Publication date: Available online 27 July 2017
Source:Cancer Cell
Author(s): Marco Mina, Franck Raynaud, Daniele Tavernari, Elena Battistello, Stephanie Sungalee, Sadegh Saghafinia, Titouan Laessle, Francisco Sanchez-Vega, Nikolaus Schultz, Elisa Oricchio, Giovanni Ciriello
Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response.
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Using an algorithmic approach that they design, Mina et al. construct a pan-cancer map of oncogenic dependencies and find several co-dependent alterations that modify drug response. These results provide a framework to improve cancer therapy by anticipating drug resistance and proposing alternative strategies.http://ift.tt/2uIrVK1
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