Unlocking the Chemical Space of Cancer-Associated Perturbations

精准癌症医学的主流方法依赖于患者的基因图谱， 鉴定恶性基因产物，并描述该蛋白质产物引起肿瘤的机制。 疾病因此，精确肿瘤学的未来很大程度上是建立在定制治疗的希望之上的。 基于获取复杂基因组和转录组数据的诊断技术的干预措施。尽管 关注癌症遗传学，肿瘤发生过程中正常细胞获得的独特功能 肿瘤细胞蛋白质组的异常激活不仅导致了基因突变， 而且还来自表观遗传重编程、翻译后改变或信号通路的重新布线。 不幸的是，将反映肿瘤细胞生物学的蛋白质生物化学的传统测量与肿瘤细胞的生物学特性相结合， 肿瘤将对癌症患者的临床决策做出反应的治疗是具有挑战性的， 每种蛋白质的独特性和现有技术的局限性。因此，我们的建议侧重于 在化学和癌症生物学的界面上进行基于机制的癌症研究， 评估蛋白质组动态变化的方法，以表征肿瘤的独特特征 生物学与激励新的靶向治疗的长期目标。具体而言，我们的目标是建立一个 创新的新开发和发现平台，称为肿瘤探针激活活性报告（PEAR） 蛋白质组分析通过利用化学生物学方法来了解分子的复杂性， 肿瘤细胞功能所必需的蛋白质组变化，以及细胞对癌症治疗的适应。的 我们从床边到长凳再回来的方法的基础是基于这样的假设：新的化学物质 探针反应组存在于癌细胞本身中， 治疗将反映驱动癌细胞适应的蛋白质功能的改变， 未来的新治疗模式。在相互关联和跨学科的发现和阐明 模块，我们将利用最先进的患者来源的癌症模型来可视化和识别蛋白质 在治疗前和治疗后的化学生物学探针的目标，假设差异反应组 将指示蛋白质组责任、治疗反应和肿瘤细胞生物学的独特方面。的 投资PEAR进行肿瘤蛋白质组分析以实现治疗开发的主要成果将是 开发可视化反应性靶标的方法，识别治疗诱导的反应性靶标， 建立它们的功能相关性，并基于一种新的肿瘤细胞生物学机制， 分区反应目标法综上所述，我们的建议将建立和验证新的 概念和方法，可以应用于广泛的实体瘤和作为一个扩展， 具有提供肿瘤生物学基本见解和改变精确肿瘤学的潜力， 提供了一个平台来改善现有的药物发现范例。

The prevailing approach to precision cancer medicine relies on genetic profiling of patients, followed by identification of the malignant gene product, and delineation of the mechanisms of that protein product in causing disease. As a result, much of the future of precision oncology is built on the hope of tailoring therapeutic interventions based on diagnostic technologies that acquire complex genomic and transcriptomic data. Despite the focus on cancer genetics, the unique functional capabilities acquired by normal cells during tumor development are driven by the aberrantly activated tumor cell proteome that arises not only from gene mutations but also from epigenetic reprogramming, post-translational alterations, or rewiring of signaling pathways. Unfortunately, integrating traditional measurements of protein biochemistry that reflect tumor cell biology and the therapeutics to which a tumor would respond into clinical decision-making for cancer patients is challenging due to the uniqueness of each protein and limitations in existing technologies. Thus, our proposal focuses on mechanism-based cancer research at the interface of chemistry and cancer biology to develop quantitative approaches that evaluate dynamic changes in the proteome in order to characterize unique features of tumor biology with the long-term goal of motivating novel targeted therapies. Specifically, we aim to establish an innovative new development and discovery platform termed Probe Enabled Activity Reporting (PEAR) for tumor proteome profiling by leveraging chemical biology approaches to understand the molecular complexity of proteomic changes necessary for tumor cell function, as well as cellular adaptations to cancer therapy. The foundation of our bedside-to-bench and back again approach is rooted in the hypothesis that novel chemical probe reactomes exist in cancer cells themselves and changes in the reactome profile in response to cancer therapeutics will reflect alterations in protein function that drive cancer cell adaptations and thus, would be ideal for new treatment modalities in the future. In interconnected and interdisciplinary discovery and elucidation modules, we will utilize state-of-the-art patient derived cancer models to both visualize and identify the protein targets of chemical biology probes in pre- and post-treatment with the hypothesis that the differential reactomes will be indicative of proteomic liabilities, therapeutic response, and unique aspects of tumor cell biology. The major outcomes from investing in PEAR for tumor proteome profiling to enable therapeutic development will be development of methodology to visualize reactive targets, identification of treatment induced reactive targets and establishing their functional relevance, and unraveling unique tumor cell biology based on a novel compartmentalized reactive target method. Taken together, our proposal will establish and validate novel concepts and methodologies that can be applied across the broad spectrum of solid tumors and as an extension, holds the potential to provide fundamental insights into tumor biology and transform precision oncology by providing a platform to improve existing paradigms for drug discovery.