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中文摘要
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人类基因组包含556个激酶基因,通常称为激酶组。激酶是调节细胞信号传导的几乎所有方面的酶,它们的失调导致细胞过度增殖,这是癌症的标志。激酶是精准肿瘤学中最重要的靶点之一,但目前大多数癌症的理想激酶靶点或激酶药物组合尚未建立。确定关闭激酶的细胞后果具有巨大的潜力,可以改变我们对激酶和激酶抑制剂的理解。在这个新的创新者奖申请中,我试图通过使用尖端的碱基编辑工具来关闭激酶组中每个人类激酶的酶活性,来破译激酶催化如何调节癌细胞功能。这种方法将识别用于治疗靶向的新型激酶,并将作为小分子抑制的替代物,以使药物发现成为可能。干扰细胞中激酶组的现有方法使用敲除或敲低,这是去除整个基因的原始工具,并且不一定转化为小分子抑制剂的作用。我的碱基编辑方法来抑制激酶催化将解决两个主要问题,防止现有的诱变和敲入方法,以跨激酶组的规模和在生理水平上进行突变。碱基编辑由于其高编辑效率,可以在汇集实验中在生理水平上突变数百个基因。在这里,我提出了一个碱基编辑平台,用于关闭癌细胞中556种激酶的催化作用,以进行汇总功能研究。作为一个案例研究,我将研究乳腺癌,其中多种激酶抑制剂是标准疗法,但迫切需要新的治疗方法。我已经开发了一套新技术,能够在细胞中编辑整个kinome碱基,并得到初步数据的支持。我将使用这个平台来研究激酶活性如何调节1)癌细胞生长,2)对靶向治疗的敏感性,以及3)可药用基因表达。该平台将通过确定抑制激酶的最佳机制,改变药物开发和组合疗法的设计,将激酶组命中和铅发现之间的间隔从几十年压缩到几年。这个建议集中在癌症中的人类激酶,但是一旦我们建立了这个框架,它将适用于研究哺乳动物任何生理过程中的任何酶类。这个提议在概念上、技术上和物质上都是创新的,是第一个以全面的方式精确、外科手术抑制一个大而多样的酶家族的实验。我学习结构生物学、蛋白质生物化学和激酶信号传导的背景;我作为乳腺肿瘤学家的临床经验;以及哥伦比亚大学欧文医学中心强大的机构环境,使我具备进行这些研究的独特条件。
英文摘要
The human genome contains 556 kinase genes, commonly called the kinome. Kinases are enzymes that regulate nearly all aspects of cell signaling and their dysregulation leads to excess cell proliferation, a hallmark of cancer. Kinases are one of the most important targets in precision oncology, but the ideal kinase targets or kinase drug combinations for most cancers have not been established. Determining the cellular consequences of turning off kinase enzymes has immense potential to transform our understanding of kinases and kinase inhibitors. In this New Innovator Award application, I seek to decipher how kinase catalysis regulates cancer cell function by using cutting-edge base editing tools to turn off the enzyme activity in every human kinase across the kinome. This approach will identify novel kinases for therapeutic targeting and will act as a surrogate for small-molecule inhibition to enable drug discovery. Prior methods to perturb the kinome in cells use knock-out or knock-down, which are crude tools that remove the entire gene and do not necessarily translate to the effects of a small-molecule inhibitor. My base editing approach to inactivate kinase catalysis will solve two major issues that prevent existing mutagenesis and knock-in methods to both scale across the kinome and perform mutations at physiologic levels. Base editing can mutate hundreds of genes at physiologic levels in a pooled experiment due to its high editing efficiency. Here, I propose a base editing platform to turn off catalysis in in 556 kinases in cancer cells for pooled functional studies. As a case study, I will investigate breast cancer, where multiple kinase inhibitors are standard therapies but where new treatments are urgently needed. I have developed a suite of new technologies enabling whole kinome base editing in cells, supported by preliminary data. I will use this platform to interrogate how kinase activity regulates 1) cancer cell growth, 2) sensitivity to targeted therapies, and 3) druggable gene expression. This platform will compress the interval between kinome hit and lead discovery from decades to years by identifying the optimal mechanisms to inhibit kinases, transforming drug development and design of combination therapies. This proposal focuses on human kinases in cancer but once we establish this framework it will be applicable to studying any enzyme class in any physiologic process in mammals. This proposal is innovative conceptually, technically, and materially as the first experiment for precise, surgical inhibition of a large and diverse family of enzymes in a comprehensive fashion. My background studying structural biology, protein biochemistry, and kinase signaling; my clinical experience as a breast oncologist; and the strong institutional environment at Columbia University Irving Medical Center make me uniquely well-equipped to perform these investigations.
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Investigating a hierarchical model for PI3K activation and inhibition in breast cancer by double PIK3CA mutations in cis
Investigating a hierarchical model for PI3K activation and inhibition in breast cancer by double PIK3CA mutations in cis
Investigating a hierarchical model for PI3K activation and inhibition in breast cancer by double PIK3CA mutations in cis
Investigating a hierarchical model for PI3K activation and inhibition in breast cancer by double PIK3CA mutations in cis
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