Multiplex FRET Imaging of Kinase-Epigenome Interregulations in Live Cancer Cells

活癌细胞中激酶-表观基因组相互调节的多重 FRET 成像

• 批准号: 9281530
• 负责人: Yingxiao Wang
• 金额: $ 37.68万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-10 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9281530
• 关键词: Adenocarcinoma Cell; Antineoplastic Agents; Binding; Biosensor; Calibration; Cancer Biology; Cell Line; Cells; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Code; Color; Coupled; Cultured Cells; Detection; Development; Directed Molecular Evolution; Drug resistance; Engineering; Epigenetic Process; Event; Fluorescence Resonance Energy Transfer; Focal Adhesion Kinase 1; Foundations; Gene Expression; Genetic Engineering; Genome; Genome engineering; Goals; Heterogeneity; Histones; Image; Image Analysis; Imagery; Imaging Device; Individual; Lead; Libraries; Life; Malignant Neoplasms; Malignant neoplasm of pancreas; Maps; Mediating; Methods; Modeling; Modification; Molecular; Molecular Profiling; Monitor; Organoids; Outcome; Pancreatic Ductal Adenocarcinoma; Pharmaceutical Preparations; Pharmacology; Pharmacotherapy; Pharmacy (field); Phosphotransferases; Preclinical Drug Evaluation; Protamine Kinase; Protein Engineering; Protein Tyrosine Kinase; Reagent; Recurrent disease; Regulation; Resistance; Signal Transduction; Technology; Therapeutic; Tyrosine Kinase Inhibitor; Work; anticancer research; base; cancer cell; cancer therapy; cancer type; cellular imaging; chemotherapy; clinical application; design; dosage; drug efficacy; epigenome; experience; gemcitabine; histone methylation; imaging modality; imaging system; indexing; inhibitor/antagonist; kinase inhibitor; live cell imaging; novel therapeutics; pancreatic cancer cells; response; screening; spatiotemporal; success; therapy outcome; tool; tumor progression

Multiplex FRET Imaging of Kinase-Epigenome Interregulations in Live Cancer Cells Kinase inhibitors have been applied to mitigate pancreatic cancer development. However, adaptive epigenetic responses including histone modulations can lead to the alteration of large scale gene expressions which can ultimately result in heterogeneous drug resistant responses of cancer cells and life-threatening relapse of diseases. At the current stage, it remains unclear how tyrosine kinase activities are dynamically coupled with epigenetic histone modulations to determine cancer cell responses upon drug treatment. Therefore, investigating and manipulating the regulation of histone modulations and codes have crucial implications in cancer treatment and drug screening. In this proposal, we will harness the power of directed evolution and high-content screening methods to systematically develop fluorescence resonance energy transfer (FRET) biosensors for the dynamic monitoring and quantification of crucial histone methylations (H3K4, H3K9, H3K27) in single cells. We will also apply this approach to optimize a focal adhesion kinase (FAK) FRET biosensor for the visualization of FAK kinase activity. Together with an existing Src FRET biosensor optimized by us, these biosensors will be incorporated into the genome of pancreatic cancer cells using CRIPSR to minimize the heterogeneity of signals across different individual cells. We will further incorporate new FRET pairs emitting colors distinct from the popular FRET pair (CFP and YFP) to simultaneously monitor two different signals in the same live cell, e.g. one histone methylation and one kinase activation. Using a common molecular signal as a reference across different individual cells, these crucial molecular events will be mapped together with correlative FRET imaging method (CFIM) developed in our labs to generate dynamic landscapes of kinome-epigenome interactions. Pharmacological reagents will be applied to study their impact on these dynamic landscape of molecular interactions and adaptive epigenetic responses. We will then correlate these multiplex molecular profiles to cancer outcomes under these pharmacological reagents, and hence provide quantified multiplex indices to evaluate drug efficacy at the single-cell level with the goal of minimizing drug resistance. Three specific aims are accordingly proposed: (1) Develop and optimize histone methylation and tyrosine kinase FRET biosensors; (2) Apply CRISPR to genetically engineer FRET biosensors into pancreatic cancer cell lines for the calibration of inhibitor efficacy in single cells; (3) Multiplex imaging of histone methylations and kinase activities in the same PDAC cells for assessing adaptive epigenetic responses upon kinase inhibition. Given the importance and critical needs of new imaging tools to investigate the kinome-epigenome connection in cancer cells, developed FRET biosensors and imaging system should provide powerful means to unravel the molecular network for cancer biology, and allow multiplex and high throughput platform for drug screening with minimal resistance. As such, the success of the project will contribute transformative enabling technologies to the field of cancer research and pharmaceutics, toward an ultimate goal of eradicating pancreatic cancers.

活癌细胞中激酶-表观基因组相互调节的多重 FRET 成像 激酶抑制剂已被用于减轻胰腺癌的发展。然而，适应性表观遗传 包括组蛋白调节在内的反应可以导致大规模基因表达的改变，从而可以 最终导致癌细胞的异质耐药反应和危及生命的复发 疾病。目前阶段，尚不清楚酪氨酸激酶活性如何与 表观遗传组蛋白调节以确定癌细胞对药物治疗的反应。因此，调查 操纵组蛋白调制和编码的调节对癌症治疗具有重要意义 和药物筛选。在这个提案中，我们将利用定向进化和高内涵筛选的力量 系统地开发动态荧光共振能量转移（FRET）生物传感器的方法 单细胞中关键组蛋白甲基化（H3K4、H3K9、H3K27）的监测和定量。我们还将 应用这种方法来优化粘着斑激酶 (FAK) FRET 生物传感器，以实现 FAK 的可视化 激酶活性。与我们优化的现有 Src FRET 生物传感器一起，这些生物传感器将 使用 CRIPSR 整合到胰腺癌细胞的基因组中，以最大限度地减少信号的异质性 跨越不同的个体细胞。我们将进一步结合新的 FRET 对，其发出的颜色不同于 流行的 FRET 对（CFP 和 YFP）可同时监测同一活细胞中的两个不同信号，例如一 组蛋白甲基化和一种激酶激活。使用共同的分子信号作为不同的参考 单个细胞，这些关键的分子事件将通过相关的 FRET 成像方法一起绘制 （CFIM）是我们实验室开发的，用于生成激酶组-表观基因组相互作用的动态景观。 药理学试剂将用于研究它们对这些分子动态景观的影响 相互作用和适应性表观遗传反应。然后我们将这些多重分子谱关联起来 这些药理学试剂下的癌症结果，因此提供量化的多重指数 在单细胞水平评估药物疗效，以尽量减少耐药性。三个具体目标是 据此提出：（1）开发并优化组蛋白甲基化和酪氨酸激酶FRET生物传感器； (2) 应用 CRISPR 将 FRET 生物传感器基因改造到胰腺癌细胞系中，以校准 单细胞抑制剂功效； (3) 组蛋白甲基化和激酶活性的多重成像 PDAC 细胞用于评估激酶抑制后的适应性表观遗传反应。鉴于其重要性和关键性 需要新的成像工具来研究癌细胞中的激酶组-表观基因组联系，开发了 FRET 生物传感器和成像系统应提供强大的手段来解开癌症的分子网络 生物学，并允许多重和高通量平台以最小的阻力进行药物筛选。像这样， 该项目的成功将为癌症研究领域贡献变革性的使能技术 药剂学，以实现根除胰腺癌的最终目标。