A Chemical Genetic Approach to Exploring Novel Therapeutic Space for Colorectal Cancer

探索结直肠癌新治疗空间的化学遗传学方法

• 批准号: 10359839
• 负责人: Ross Leigh Cagan
• 金额: $ 60.42万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10359839
• 关键词: Animals; Apoptosis; BRAF gene; Benchmarking; Biological Assay; Biology; Cancer Etiology; Cancer Model; Cells; Cessation of life; Chemical Modifier; Chemicals; Chemistry; Clinical; Colorectal Cancer; Complex; Computer Models; Data; Development; Diagnosis; Disease; Drosophila genus; Drug Design; Drug Kinetics; Epidermal Growth Factor Receptor; Excretory function; FDA approved; Genetic; Genetic Screening; Goals; Half-Life; Human; Immunotherapy; In Vitro; KRAS2 gene; Lead; Libraries; Malignant Neoplasms; Maps; Mediating; Metabolism; Modeling; Modification; Monomeric GTP-Binding Proteins; Mus; Nature; Neoplasm Metastasis; Oncogenic; Patients; Pharmaceutical Preparations; Pharmacotherapy; Phosphotransferases; Primary carcinoma of the liver cells; Property; Protein Isoforms; RAF1 gene; Refractory; Series; Signal Transduction; Structure; Structure-Activity Relationship; Survival Rate; TP53 gene; Testing; Therapeutic; Therapeutic Index; Toxic effect; Treatment Efficacy; United States; Variant; Xenograft Model; Xenograft procedure; absorption; analog; aurora kinase A; base; chemical genetics; colon cancer cell line; colon cancer patients; comparative; cost; design; drug development; fly; gastrointestinal; genetic analysis; genetic approach; improved; in vivo; inhibitor; innovation; insight; interdisciplinary approach; kinase inhibitor; metastatic colorectal; mortality; mutant; neoplastic cell; network attack; novel; novel therapeutic intervention; novel therapeutics; patient derived xenograft model; side effect; small molecule; structural biology; tumor; tumor growth

Project Summary Metastatic colorectal cancer (mCRC) is the second leading cause of cancer-related mortality in the United States, and annually accounts for nearly 500,000 deaths worldwide. Currently, the small molecule kinase inhibitor (KI) regorafenib is the primary second line therapy for metastatic CRC that is not treatable with immunotherapy or anti-EGFR therapies. However, regorafenib generally provides only modest improvements in survival— typically months—and often at the cost of significant side effects. Proposed targets for regorafenib include kinases that act within tumor cells as well as non-autonomously; however, with over 500 possible targets in the human kinome, the exact mechanism by which this compound operates remains controversial and not fully known. This presents a daunting challenge; without a verifiable target or mechanism, no clear path exists to guide the development of improved therapies for mCRC. Here, we propose an alternative approach to drug development that focuses on kinase networks in the context of the whole animal. Specifically, we will take a multidisciplinary approach to define kinases that are beneficial to inhibit (‘pro-targets’) or avoid (‘anti-targets’) in the context of KRAS-variant CRC. Using Drosophila and mammalian models, we will identify kinases that—when reduced—alter the efficacy of regorafenib and similar compounds. We will also conduct extensive structure-activity relationship analyses, evaluating how modifications in already identified lead compounds impact changes in efficacy and therapeutic index. Finally, we will use computational structural biology to convert our chemical genetic insights into highly optimized and precise polypharmacological leads. In this final step, we generate new analogs to selectively eliminate putative anti-target activity while maintaining or increasing inhibitory activity against other beneficial targets. We have used our chemical genetic platform to identify a promising lead compound, APS5-86-2, that demonstrates significant activity relative to regorafenib in several mCRC models, including human patient derived xenografts (PDX). Comparative analysis suggests that the improved activity of APS5-86-2 relative to regorafenib derives from distinct polypharmacology on several RTKs and critical cancer drivers, including CDK9, AURKA, EGFR, BRAF, and RAF1. In this proposal, we examine the mechanism and importance of these and other putative pro- and anti-target kinases using genetic analysis and in vivo target engagement. The objective is to identify the kinase networks that mediate KRAS-variant mCRC by combining chemical biology with genetics, and to then derive inhibitors that best attack these networks through structure-based drug design. We have been successful previously with a similar approach, but in less complex tumor models (Dar et al., Nature, 2012; Sonoshita et al., Nature Chem. Bio., 2018); here we seek to extend our platform to a more prevalent disease with the goal of directly impacting mCRC by creating new, highly differentiated, and improved drugs.

项目摘要 转移性结直肠癌（mCRC）是美国癌症相关死亡率的第二大原因。 每年全世界有近50万人死亡。目前，小分子激酶 抑制剂（KI）瑞戈非尼是转移性CRC的主要二线治疗， 免疫疗法或抗EGFR疗法。然而，瑞戈非尼通常仅提供适度的改善， 生存期--通常是几个月--而且往往以显著的副作用为代价。Regorafenib的拟定目标 包括在肿瘤细胞内以及非自主地起作用激酶;然而，具有超过500种可能的靶点 在人类激酶组中，这种化合物的确切作用机制仍然存在争议， 全知。这是一项艰巨的挑战;没有可核查的目标或机制，就没有明确的道路 以指导改进mCRC疗法的开发。 在这里，我们提出了一种药物开发的替代方法，该方法侧重于激酶网络， 整个动物的背景。具体来说，我们将采取多学科的方法来定义激酶， 在KRAS变异型CRC的情况下，抑制（“前靶标”）或避免（“抗靶标”）是有益的。利用果蝇 和哺乳动物模型，我们将确定激酶，当减少，改变瑞格非尼的疗效， 类似的化合物。我们还将进行广泛的结构-活性关系分析，评估如何 已经鉴定的先导化合物的修饰影响功效和治疗指数的变化。最后我们 将使用计算结构生物学将我们的化学遗传见解转化为高度优化的， 精确的多药治疗线索在这最后一步，我们产生新的类似物，以选择性地消除推定的 抗靶标活性，同时维持或增加对其它有益靶标的抑制活性。 我们已经使用我们的化学遗传平台来鉴定一种有希望的先导化合物APS 5 -86-2， 在包括人类患者在内的几种mCRC模型中显示出相对于瑞戈非尼的显著活性 衍生的异种移植物（PDX）。比较分析表明，APS 5 -86-2相对于 瑞戈非尼来源于对几种RTK和关键癌症驱动因子的不同多药理学，包括CDK 9， AURKA、EGFR、BRAF和RAF 1。在本提案中，我们研究了这些机制和重要性， 使用遗传分析和体内靶点接合来确定其他推定的前靶点激酶和抗靶点激酶。客观 是通过结合化学生物学和遗传学来鉴定介导KRAS变体mCRC的激酶网络， 然后通过基于结构的药物设计来获得最好地攻击这些网络的抑制剂。我们一直 以前用类似的方法成功，但在不太复杂的肿瘤模型中（Dar等人，《自然》，2012年; Sonoshita等人，Nature Chem. Bio.，2018）;在这里，我们寻求将我们的平台扩展到更流行的疾病 其目标是通过创造新的、高度分化的和改进的药物来直接影响mCRC。