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.

中文翻译：

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基因组改变的条件选择决定了癌症的发展和致癌性的依赖性。

癌症通过分子变化的出现和选择而演变。癌症基因组图谱分析表明，特定事件或多或少地被共同选择，这表明一个事件的选择取决于其他事件。但是，这些进化依赖性的性质及其影响仍然不清楚。在这里，我们设计了SELECT，这是一种从变更模式中系统地识别进化依存关系的算法方法。通过分析来自多种肿瘤类型的6,456个基因组，我们构建了与细胞途径，转录读数和治疗反应相关的致癌依赖性图谱。最后，对癌症进化的建模表明，改变依赖性仅在条件选择下出现。