Overcoming adaptive feedback resistance to KRAS inhibition in colorectal cancer

项目摘要/摘要 尽管KRAS在20%的癌症和40%的结直肠癌(CRC)中发生突变，但长期以来 被认为是不能下药的目标1.最近，对KRASG12C具有选择性的新型共价抑制剂已经进入 该诊所提供了前所未有的机会直接针对KRAS和其他突变特异性KRAS 抑制剂(即G12D)正在开发中2，3。然而，先前针对Ras-MAPK途径的努力已经 受到适应性反馈的阻碍，这导致通路重新激活和抵抗，特别是在结直肠癌中。 例如，在BRAFV600结直肠癌中抑制BRAF会导致ERK依赖的负反馈和RTK- 介导的通路重新激活，导致的应答率仅为~5%，而在肺癌和 -gt；50%在黑色素瘤4，5。类似地，尽管KRASG12C抑制剂的早期临床数据显示有希望的应答率 在肺癌中，结直肠癌的有效率要低得多(~10%)，而且耐受性有限，这表明 类似的适应性抗性模式可能在KRASG12C CRC 2，3中起作用。 初步研究表明，强健的适应性反馈信号导致通路快速重新激活和 在KRASG12C结直肠癌模型6中缺乏反应。然而，之前在BRAFV600结直肠癌中的研究-包括临床前和 Corcoran博士和Kopetz博士之间的临床合作已经证明了联合疗法 靶向适应性反馈信号(例如，EGFR)可以改善临床结果，第一次这样的组合 FDA今年批准(Corcoran等人，癌症发现2018年；Kopetz等人，NEJM，2019年)7-10。同样，我们的 初步数据支持在KRASG12C CRC中针对自适应反馈的重要性，但也表明情况复杂 反馈信号需要超越以EGFR为目标的策略来优化结果。 在这里，我们建议确定结直肠癌抵抗KRAS抑制的关键机制并设计治疗方案。 克服阻力的策略。为了实现这一目标，我们建议利用一个独特的集合~100 患者派生的CRC有机化合物和约300个CRC PDX库，通过MGH/MIT/BRoad U54生成 DrSc和MDACC U54 PDXNet团队。我们将部署这些新工具来全面 使用临床相关的PDX和患者-体内映射对KRASG12C抑制的适应性反馈反应 衍生有机物异种移植(PDOX)结直肠癌模型。同时，我们将模拟体内抗药性的演变 评估RTK可塑性在驱动对特定KRAS抑制剂组合的耐药性中的潜在作用 将通过对一系列肿瘤活检的基因组分析来确定获得性耐药性的候选机制 参加KRAS抑制剂联合试验的结直肠癌患者的cfDNA。利用这种增强的机制 为了理解这一点，我们将在我们的患者衍生模型中设计和测试新的治疗策略。

Project Summary/Abstract Although KRAS is mutated in 20% of all cancers and 40% of colorectal cancer (CRC), it has long been considered an “undruggable” target 1. Recently, novel covalent inhibitors selective for KRASG12C have entered the clinic, offering the unprecedented opportunity to target KRAS directly, and other mutation-specific KRAS inhibitors (i.e. G12D) are under development 2,3. However, prior efforts to target the RAS-MAPK pathway have been hampered by adaptive feedback, which drives pathway reactivation and resistance, particularly in CRC. For example, BRAF inhibition in BRAFV600 CRC leads to loss of ERK-dependent negative feedback and RTK- mediated pathway reactivation, leading to response rates of only ~5%, compared to ~35% in lung cancer and >50% in melanoma 4,5. Similarly, while early clinical data with KRASG12C inhibitors show promising response rates of >35% in lung cancer, response rates in CRC appear much lower (~10%) with limited durability, suggesting a similar mode of adaptive resistance may be operant in KRASG12C CRC 2,3. In support of this hypothesis, our preliminary studies have suggested that robust adaptive feedback signals lead to rapid pathway reactivation and lack of response in KRASG12C CRC models 6. However, prior studies in BRAFV600 CRC—including preclinical and clinical collaborations between Drs. Corcoran and Kopetz—have demonstrated that combination therapies targeting adaptive feedback signaling (e.g. EGFR) can improve clinical outcome, with the first such combination FDA-approved this year (Corcoran et al, Cancer Discovery 2018; Kopetz et al, NEJM, 2019)7-10. Similarly, our preliminary data support the importance of targeting adaptive feedback in KRASG12C CRC, but suggest complex feedback signaling that will require strategies beyond targeting EGFR to optimize outcome. Here, we propose to define the key mechanisms of resistance to KRAS inhibition in CRC and devise therapeutic strategies to overcome resistance. To accomplish this goal, we propose to leverage a unique collection of ~100 patient-derived CRC organoids and a bank of ~300 CRC PDXs, generated through the MGH/MIT/Broad U54 DRSC and the MDACC U54 PDXNet teams, respectively. We will deploy these novel tools to comprehensively map the adaptive feedback response to KRASG12C inhibition in vivo using clinically-relevant PDX and patient- derived organoid xenografts (PDOX) CRC models. In parallel, we will model the evolution of resistance in vivo to evaluate the potential role of RTK plasticity in driving resistance to specific KRAS inhibitor combinations and will identify candidate mechanisms of acquired resistance through genomic analysis of serial tumor biopsies and cfDNA from CRC patients on KRAS inhibitor combination trials. Utilizing this enhanced mechanistic understanding, we will devise and test novel therapeutic strategies in vivo in our patient-derived models.