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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/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“不可成药”的靶点 1. 最近，针对 KRASG12C 选择性的新型共价抑制剂已进入市场诊所，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，之前针对 RAS-MAPK 通路的努力已经取得进展。受到适应性反馈的阻碍，适应性反馈驱动通路重新激活和抵抗，特别是在结直肠癌中。例如，BRAFV600 CRC 中的 BRAF 抑制导致 ERK 依赖性负反馈和 RTK- 的丧失。介导的通路再激活，导致反应率仅为约 5%，而肺癌和癌症的反应率约为 35% 黑色素瘤 4,5 中的缓解率类似，而 KRASG12C 抑制剂的早期临床数据显示出有希望的缓解率。肺癌的缓解率 >35%，结直肠癌的缓解率似乎低得多（约 10%）且持久性有限，这表明类似的适应性抵抗模式可能在 KRASG12C CRC 2,3 中起作用。为了支持这一假设，我们的研究结果如下：初步研究表明，强大的适应性反馈信号会导致通路快速重新激活，并且 KRASG12C CRC 模型中缺乏反应 6。然而，BRAFV600 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证明了联合疗法针对适应性反馈信号（例如 EGFR）可以改善临床结果，第一个此类组合今年获得 FDA 批准（Corcoran 等人，Cancer Discovery 2018；Kopetz 等人，NEJM，2019）7-10。初步数据支持 KRASG12C CRC 中自适应目标反馈的重要性，但表明其复杂性反馈信号需要除靶向 EGFR 以外的策略来优化结果。在这里，我们建议定义 CRC 中 KRAS 抑制耐药的关键机制，并设计治疗方法为了实现这一目标，我们建议利用约 100 种独特的策略来克服阻力。源自患者的 CRC 类器官和通过 MGH/MIT/Broad U54 生成的约 300 个 CRC PDX 库 DRSC 和 MDACC U54 PDXNet 团队将分别全面部署这些新颖的工具。使用临床相关的 PDX 和患者来绘制体内 KRASG12C 抑制的适应性反馈反应与此同时，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 抑制剂组合的耐药性中的潜在作用，以及将通过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利用这种增强的机制进行 KRAS 抑制剂组合试验中的 CRC 患者的 cfDNA。了解后，我们将在源自患者的模型中设计并测试新的体内治疗策略。