Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

中文翻译：

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癌细胞依赖性的全面临床知情图谱和目标优先顺序框架

癌细胞系中的遗传筛选为基因功能和药物发现提供信息。需要更全面的多组学数据筛选数据集，以增强功能性绘制遗传漏洞图谱的机会。在这里，我们通过用多组学数据注释 930 个癌细胞系，构建了第二代癌症依赖性图谱，并分析了来自 CRISPR-Cas9 筛选的分子标记与癌症依赖性之间的关系。我们识别了驱动基因之外的与依赖性相关的基因表达标记，并观察到许多由功能获得而不是合成致死效应驱动的基因成瘾关系。通过将临床知情的依赖性标记关联与蛋白质-蛋白质相互作用网络相结合，我们确定了 27 种癌症类型的 370 个抗癌优先靶点，其中许多靶点具有基于网络的证据，表明与癌症类型中的标记存在功能联系。将这些靶点映射到已测序的肿瘤队列，可以识别不同癌症类型中可处理的靶点。该目标优先顺序图增强了对基因依赖性的理解，并确定了药物开发的候选抗癌目标。