A Prostate Cancer Dependency Map to Identify Tumor Subtype-Specific Vulnerabilities

项目摘要/摘要 尽管我们对癌症生物学的知识取得了进步，食品和药物管理局也批准了新的抗癌药物 和药品管理局(FDA)，很少有实体肿瘤扩散到远处的患者 (转移性肿瘤)已治愈。转移性前列腺癌(MPC)也是如此。因此， 大量研究旨在确定新的靶点和治疗方法。 我们和其他人开发的新技术现在提供了前所未有的方法 在全面的范围内深刻地描述肿瘤的特征。使用这些方法的研究已经确定 MPC由多个不同的亚型组成-这些亚型的子集由特定的基因组定义 癌基因和正常作用于抑制肿瘤生长的基因的改变。其他的则由 表型--影响功能和行为的特征。值得注意的是，这些子类型中的许多现在是 已知对特定疗法有不同的脆弱性-知识是更精确的基础 治疗方法。然而，对于大多数亚型，我们目前还不知道它们的具体情况 我们也没有可以阻止它们生长/发展的治疗方法。 强大的高通量方法来剖析特定癌症基因组中每个基因的功能 已被用于在许多癌症类型中构建癌症依赖图(DEPMAP)。这些 这些方法是高度“发现驱动的”，因为它们在处理识别癌症脆弱性的问题时 系统性的，而不是假设驱动的时尚。然而，前列腺癌在很大程度上被排除在这些之外。 国际项目，因为可用于进行这些大规模活动的MPC模型数量非常有限 实验。 在这项提案中，我们的目标是确定晚期致命性前列腺癌的新治疗途径。我们将使用 我们已经开发和表征的多种转移性前列腺癌的新模型来识别PC 使用全基因组功能丧失筛查的特定依赖亚型。同时，我们将评估 经批准的药物以及正在开发的化合物的药库的生长抑制作用。 利用基因组相关性的药物组合将在体内针对一组患者进行测试 衍生异种移植物(PDX)系具有和不具有预测的脆弱性。

PROJECT SUMMARY/ABSTRACT Despite the advances in our knowledge of cancer biology and the approval of new cancer drugs by the Food and Drug Administration (FDA), very few patients with solid tumors that have spread to distant sites (metastases) are cured of their disease. This is true of metastatic prostate cancer (mPC). Consequently, substantial research is directed toward identifying new targets and treatments. New technologies which we and others have developed, now provide unprecedented approaches for deeply characterizing tumors on a comprehensive scale. Studies using these approaches have determined that mPC is comprised of multiple distinct subtypes – a subset of these are defined by specific genomic alterations in oncogenes and genes that normally function to suppress tumor growth. Others are defined by the phenotype – characteristics that influence function and behavior. Notably, a number of these subtypes are now known to have different vulnerabilities to particular therapies – knowledge that underlies a more precision approach for treatment. However, for most subtypes we do not currently have knowledge of their particular vulnerabilities nor do we have therapeutics that can halt their growth/progression. Powerful high-throughput approaches to dissect the function of every gene in a particular cancer genome have been deployed to construct cancer dependency maps (DEPMAP) in many cancer types. These approaches are highly ‘discovery driven’ as they approach the problem of identifying cancer vulnerabilities in a systematic rather than hypothesis-driven fashion. However, prostate cancer is largely excluded from these International projects due to the very limited number of mPC models available to conduct these large scale experiments. In this proposal, we aim to identify new treatment avenues for advanced lethal prostate cancer. We will use multiple new models of metastatic prostate cancer that we have developed and characterized to identify PC subtype specific dependencies using genome-wide loss-of-function screens. In parallel, we will evaluate growth inhibitory effects of drug libraries of approved agents as well as compounds in development. Combinations of agents that exploit genomic dependencies will be tested in vivo against a panel of patient derived xenograft (PDX) lines with and without the predicted vulnerability.