CAREER: Defining kinase-driven cellular response networks using single-cell genomics

细胞对压力的反应方式对其在生物医学应用中的表现至关重要。改变反应可以显著改善治疗结果。例如，改变对化疗的反应可以抑制或逆转肿瘤的生长。改变免疫系统的反应可以减少疫苗开发的需要。这些反应的许多关键调节因子是被称为激酶的酶。几种激酶抑制剂已被证明在治疗某些癌症方面取得了成功。利用基因组工具来确定哪些激酶控制特定的细胞应激反应是该项目的核心策略。在不同的学术水平上促进基因组学领域的公平和包容性是另一个主要目标。向纽约生物力量项目的高中生介绍基因组技术和分析是该项目的另一个主要推动力。还将与波多黎各大学合作开发短期课程。该项目的目标是实现对基因如何改变细胞反应的大规模数据驱动预测。为此，将开发将单细胞基因组学扩展到多重平台以绘制扰动影响的分析方法。其目的是确定细胞在应对细胞压力时所经历的分子变化，以及这些反应如何依赖于蛋白激动组中单个激酶的活性。有关激酶调节网络的信息将被用来操纵细胞对感兴趣的表型的反应，例如对治疗敏感的细胞命运。质疑这些细胞反应的方法必须考虑到，即使是看似同质的一组细胞，如何在对细胞压力的反应中表现出实质性的异质性。该项目利用高通量的单细胞基因组技术来获得激酶调节网络，该网络定义了细胞对遗传毒性应激、免疫相关程序和遗传冗余驱动由激酶抑制引起的动态变化的反应。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

How a cell responds to stress is critical to its performance in biomedical applications. Modifying the response can dramatically improve treatment outcomes. For example, altering the response to chemotherapy could inhibit or reverse tumor growth. Altering the immune system response could reduce the need for vaccine development. Many of the key regulators of these responses are enzymes known as kinases. Several kinase inhibitors have proven successful in treating certain cancers. Utilizing genomic tools to identify which kinases control specific cellular stress responses is a core strategy in this project. Advancing equity and inclusion in the genomics field at various academic levels is another major objective. Introducing genomic technologies and analysis to high school students in the NY Bioforce program is another major thrust of this project. Collaboration with the University of Puerto Rico to develop short courses will also be undertaken.The goal of this project is to enable large-scale data-driven prediction of how genes alter cellular response. To this end, assays that extend single-cell genomics to a multiplex platform to map the effects of perturbations will be developed. The objective is to define the molecular changes that cells undergo in response to cellular stress and how those responses depend on the activity of individual kinases in the protein kinome. Information on kinase regulatory networks will be used to manipulate cellular response towards phenotypes of interest, such as treatment-sensitive cell fates. Methods to query these cellular responses must account for how even a seemingly homogeneous group of cells can display substantial heterogeneity in their response to cellular stress. The project leverages high-throughput single-cell genomic techniques to arrive at kinase regulatory networks that define the response of cells to genotoxic stress, immune-associated programs, and genetic redundancy driving dynamic changes induced by kinase inhibition.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.