Overcoming adaptive feedback resistance to KRAS inhibition in colorectal cancer

克服结直肠癌中 KRAS 抑制的适应性反馈抵抗

• 批准号: 10594497
• 负责人: Ryan Bruce Corcoran
• 金额: $ 69.78万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10594497
• 关键词: Antibodies; Automobile Driving; BRAF gene; Biological Assay; Biopsy; Cancer Model; Clinic; Clinical; Clinical Data; Clinical Trials; Collaborations; Collection; Colorectal Cancer; Combined Modality Therapy; Complex; Data; Development; Epidermal Growth Factor Receptor; Evolution; FDA approved; Feedback; Genomics; Goals; Grant; Heterogeneity; Immunofluorescence Immunologic; KRAS2 gene; KRASG12D; Lead; MAP Kinase Gene; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Mediating; Mediator; Methods; Modeling; Mutate; Mutation; Organoids; Outcome; PTPN11 gene; Pathway interactions; Patients; Pharmacodynamics; Proteomics; Resistance; Role; Signal Transduction; Testing; Therapeutic; Time; Translations; University of Texas M D Anderson Cancer Center; Xenograft Model; Xenograft procedure; candidate identification; clinically relevant; colon cancer patients; efficacy evaluation; improved; in vitro Model; in vivo; in vivo Model; in vivo evaluation; inhibitor; melanoma; mutant; novel; novel therapeutic intervention; pre-clinical; resistance mechanism; response; single cell analysis; single-cell RNA sequencing; targeted treatment; tool; transcriptomics; tumor; tumor progression

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.

项目总结/摘要 尽管KRAS在20%的所有癌症和40%的结直肠癌（CRC）中发生突变，但长期以来， 被认为是一个“不可拒绝的”目标1。最近，对KRASG 12 C具有选择性的新型共价抑制剂已经进入 临床，提供了前所未有的机会，直接靶向KRAS和其他突变特异性KRAS 抑制剂（即G12 D）正在开发中2，3。然而，靶向RAS-MAPK通路的先前努力已经被证明是有效的。 受到适应性反馈的阻碍，这会驱动通路的重新激活和抵抗，特别是在CRC中。 例如，BRAFV 600 CRC中的BRAF抑制导致ERK依赖性负反馈和RTK-1的丧失。 介导的通路再激活，导致反应率仅为~ 5%，而肺癌中的反应率为~35%， >50%的黑色素瘤4，5.类似地，虽然KRASG 12 C抑制剂的早期临床数据显示有希望的缓解率， 肺癌的缓解率>35%，CRC的缓解率似乎低得多（~10%），且持久性有限，这表明 在KRASG 12 C CRC 2，3中可以操作类似自适应电阻模式。为了支持这一假设，我们 初步研究表明，强适应性反馈信号导致快速通路再激活， 在KRASG 12 C CRC模型中缺乏响应6.然而，BRAFV 600 CRC的先前研究-包括临床前和 Corcoran博士和Kopetz博士之间的临床合作已经证明， 靶向适应性反馈信号传导（例如EGFR）可以改善临床结果， FDA今年批准（Corcoran et al，Cancer Discovery 2018; Kopetz et al，NEJM，2019）7-10。同样，我们的 初步数据支持在KRASG 12 C CRC中靶向自适应反馈的重要性，但建议复杂的 反馈信号，这将需要超越靶向EGFR的策略，以优化结果。 在这里，我们建议定义CRC中KRAS抑制耐药的关键机制，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收集约100 患者来源的CRC类器官和通过MGH/MIT/Broad U 54生成的约300个CRC PDX库 DRSC和MDACC U 54 PDXNet团队。我们将部署这些新工具， 使用临床相关的PDX和患者- 衍生的类器官异种移植物（PDOX）CRC模型。与此同时，我们将模拟体内耐药性的演变 评估RTK可塑性在驱动对特定KRAS抑制剂组合的抗性中的潜在作用， 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的候选机制， 来自KRAS抑制剂组合试验的CRC患者的cfDNA。利用这种增强的机制 了解，我们将设计和测试新的治疗策略在体内在我们的患者来源的模型。