Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.

对数千种肿瘤的基因组测序揭示了许多与特定类型癌症相关的基因。同样，大规模的 CRISPR 功能基因组学工作已经绘制了数百个细胞系中癌细胞增殖或存活所需的基因图谱。尽管如此，对于特定的疾病亚型，例如转移性前列腺癌，可能存在许多未被发现的肿瘤特异性驱动基因，它们可能代表潜在的药物靶点。为了确定这种遗传依赖性，我们在转移性前列腺癌模型中进行了基因组规模的 CRISPRi 筛选。然后，我们创建了一个管道，将泛癌功能基因组学数据与我们的转移性前列腺癌功能和临床基因组学数据相结合，以确定可以驱动侵袭性前列腺癌表型的基因。我们对这些数据的综合分析揭示了已知的前列腺癌特异性驱动基因，例如AR和HOXB13 ，以及一些特征较差的热门基因。在这项研究中，我们强调了综合临床和功能基因组学管道的优势，并重点关注两个热门基因： KIF4A和WDR62 。我们证明，无论 AR 状态如何， KIF4A和WDR62在多种模型的体外和体内均可驱动侵袭性前列腺癌表型，并且还与患者不良预后相关。