Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies
A l'aide de données portant sur 6 456 génomes de divers types de tumeurs et à l'aide d'un algorithme appelé SELECT, cette étude dresse une cartographie des anomalies génomiques pour lesquelles, au cours de l'évolution tumorale, la sélection de l'une dépend de l'apparition d'une autre
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.