Using Protein Interaction Networks and Combinatorial Screens to target KRAS driven cancer

 描述（由申请人提供）：肺癌是全球癌症死亡的主要原因。非小细胞肺癌（NSCLC）是肺癌最常见的类型.在NSCLC中，KRAS是最常突变的癌基因之一，但目前尚无KRAS特异性治疗方法。本申请的目标是实施涉及蛋白质组学、组合遗传学（CRISPR/CAS9筛选）和小鼠建模（基因工程和人鼠模型）的合作努力，以确定和验证在NSCLC中特异性靶向KRAS的新策略。我们假设，根据致癌KRAS活性的背景（起源组织和继发性遗传变化）进行集中筛选可能会产生新的KRAS漏洞。鉴于KRAS通过多个平行的下游效应器发挥作用，我们还假设对漏洞的搜索应该强调（1）组合效应，以及（2）对Ras途径中蛋白质-蛋白质相互作用的仔细分析。这里提出的蛋白质组学分析将使用先前确定和验证的KRAS合成漏洞作为起点。在目标1中，我们将利用亲和纯化/质谱（AP/MS），系统地鉴定接种在先前合成致死相互作用筛选所定义的靶标上的致癌KRAS蛋白网络。新的蛋白质组学技术也将允许高分辨率鉴定KRAS特异性翻译后修饰（PTM）。这项工作将定义一组高价值的KSL候选人。在目标2中，我们部署了一种新的遗传相互作用图谱方法来创建组合敲除文库。这种方法利用了CRISPR-CAS 9系统的独特版本，该系统从单个慢病毒表达两种指导RNA（sgRNA）。sgRNA对的深度测序将鉴定与致癌KRAS或与KRAS相互作用网络的组分在遗传上相互作用的关键基因。最后，在目标3中，我们将使用两种方法测试组合合成致死相互作用的功能意义。首先，我们使用了3种人类癌症小鼠模型，这些模型将KRAS激活与关键肿瘤抑制因子（LKB 1，p53或Keap 1）的丢失相结合，因此占实际人类肿瘤中KRAS活性“多样性”的很大一部分。其次，将使用一组充分表征的患者来源的异种移植物来确定进一步的验证和人类相关性。我们预计我们的研究将确定针对KRAS突变肺癌和可能普遍存在KRAS突变的其他癌症的新策略。

 DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer deaths worldwide. The most prevalent type of lung cancer is Non- Small Cell Lung Cancer (NSCLC). In NSCLC, KRAS is one of the most frequently mutated oncogenes and yet there are currently no KRAS specific therapeutic approaches. The goal of this application is to implement a collaborative effort involving proteomics, combinatorial genetics (CRISPR/CAS9 screens), and mouse modeling (genetically engineered and human-in-mouse models) to identify and validate novel strategies to target KRAS specifically in NSCLC. We hypothesize that focused screens informed by the context (tissue of origin and secondary genetic changes) of oncogenic KRAS activity are likely to yield novel KRAS vulnerabilities. Given that KRAS acts through multiple, parallel downstream effectors, we also hypothesize that the search for vulnerabilities should emphasize (1) combinatorial effects, and (2) a careful analysis of protein-protein interactions in the Ras pathway. The proteomic analysis proposed here will use as a starting point previously identified and validated KRAS synthetic vulnerabilities. In Aim 1, we will utilize affinity purification/ mass spectrometry (AP/MS), to systematically identify oncogenic KRAS protein networks seeded on targets defined by previous synthetic lethal interaction screens. New proteomic technologies will also permit high-resolution identification of KRAS-specific post-translational modifications (PTMs). This work will define a set of high value KSL candidates. In Aim 2, we deploy a novel genetic interaction map approach to create combinatorial knockout libraries. This approach utilizes a unique version of the CRISPR-CAS9 system that expresses two guide RNAs (sgRNAs) from a single lentivirus. Deep sequencing of sgRNA pairs will identify critical genes that genetically interact with oncogenic KRAS or with components of the KRAS interaction network. Lastly, in Aim 3, we will test the functional significance of combinatorial synthetic lethal interactions using two approaches. First, we use 3 mouse models of human cancer that combine KRAS activation with loss of key tumor suppressors (LKB1, p53 or Keap1), thus accounting for a significant fraction of the "varieties" of KRAS activity in actual human tumors. Second, further validation and human relevance will be determined using a set of well-characterized patient-derived xenografts. We anticipate that our studies will identify novel strategies for targeting KRAS mutant lung cancer and potentially other cancers in which KRAS mutations are prevalent.