Dynamics, Regulation and Function of p53 in Single Cells

信号系统的动力学对于控制基因表达程序和细胞结果至关重要。 肿瘤抑制蛋白P53是一种转录因子，协调对细胞应激的反应，并且 我们之前发现，DNA损伤后它的动态变化(其蛋白质水平随时间的变化)取决于 并在决定细胞存活或死亡的过程中发挥作用。然而，许多问题仍然存在。 关于不同的细胞环境如何影响P53的动态和最终的细胞结果，P53如何选择 在相互冲突的细胞结果和如何最好地利用P53动态用于治疗目的之间。 我们工作的目标是全面定量地了解P53的动态调控机制 在单个细胞中的细胞结果，并应用我们的发现来满足临床需求。蜂窝环境 可以影响P53的动态，因此我们将首先研究P53的动态是如何受以下因素调节的 在培养的肿瘤球体中和在体内的肿瘤中作为3D细胞构筑。然后我们将调查 在培养和体内环境中癌症相关p53突变体的动力学和细胞结果。其影响 将使用新技术在单细胞中确定P53基因表达的动态模式 支持将P53动态的实时成像数据与单细胞RNA测序相结合。我们还将调查 P53的动态如何在RNA和蛋白质水平上影响基因表达，以及P53的动态 大量种群中的翻译后修饰。这些研究将揭示P53动态变化的影响 模式对其目标基因的RNA和蛋白质的影响，以及这些动态模式的组合是如何 引导蜂窝结果。我们还将使用我们的实时成像系统来确定临床相关性 治疗方法可以被优化，以诱导所需的P53动力学和癌症细胞结果。 我们将确定辐射部分的剂量和时间如何影响P53的动力学和功能，以及 优化通过P53介导的机制诱导肿瘤细胞死亡的组分的时间表。许多癌症 过度表达P53抑制剂MDM2或MDMX，并对它们的抑制敏感。通过量化和 在调控P53的动态过程中，我们将决定如何微调它们的抑制作用以增敏MDM2或MDMX 过度表达细胞造成DNA损伤，而不影响健康细胞。肿瘤细胞可以被免疫清除。 这一过程受到肿瘤基因表达程序的影响。因此，我们将调查 P53动力学如何影响肿瘤细胞和免疫细胞之间的相互作用，并朝着优化方向努力 P53靶向治疗与免疫治疗相结合，最大限度地发挥免疫对肿瘤细胞的杀伤作用 系统。总而言之，这些研究将为p53动态和P53之间的联系提供新的机械性见解。 在控制细胞命运方面的作用，并将为癌症治疗的新组合治疗方法提供信息。

The dynamics of signaling systems are critical for controlling gene expression programs and cellular outcomes. The tumor suppressor protein p53 is a transcription factor orchestrating the response to cellular stresses, and we previously found that its dynamics (changes in its protein levels over time) following DNA damage depend on the stimulus and play a role in determining whether a cell will survive or die. However, many questions remain about how different cellular contexts influence p53 dynamics and ultimate cellular outcomes, how p53 chooses between conflicting cellular outcomes, and how p53 dynamics can best be leveraged for therapeutic purposes. The goals of our work are to obtain a comprehensive quantitative understanding of how p53 dynamics regulate cellular outcomes in single cells and to apply our findings to address clinical needs. The cellular environment can influence p53 dynamics, therefore we will first investigate how p53 dynamics are regulated by factors such as 3D cellular architecture in cultured tumor spheroids and in in vivo tumors. We will then investigate the dynamics and cellular outcomes of cancer-associated p53 mutants in cultured and in vivo settings. The effects of p53 dynamical patterns on gene expression will be determined in single cells by using novel technology that supports integrating live imaging data of p53 dynamics with single-cell RNA sequencing. We will also investigate how p53 dynamics influence gene expression at the RNA and protein levels, as well as the dynamics of p53 post-translational modifications in bulk populations. These studies will reveal the impact that p53 dynamical patterns have on the RNA and protein of its target genes, and how the combinations of these dynamical patterns guide cellular outcomes. We will also use our live-imaging systems to determine how clinically-relevant therapeutic approaches can be optimized to induce the desired p53 dynamics and cellular outcomes in cancer. We will determine how the doses and timings of radiation fractions affect p53 dynamics and function, and optimize the schedule of fractions for inducing tumor cell death via p53-mediated mechanisms. Many cancers overexpress the p53 inhibitors Mdm2 or Mdmx and are susceptible to their inhibition. Through quantifying and modulating p53 dynamics we will determine how to fine-tune their inhibition to sensitize Mdm2 or Mdmx overexpressing cells to DNA damage while sparing healthy cells. Tumor cells can be cleared by the immune system, and this process is influenced by the tumors' gene expression programs. Therefore, we will investigate how p53 dynamics influence interactions between tumor cells and immune cells, and work towards optimizing combinations of p53-targeting therapeutics with immunotherapies to maximize tumor cell killing by the immune system. In total, these studies will provide new mechanistic insights into the links between p53 dynamics and function in controlling cell fates, and will inform novel combinatorial therapeutic approaches to cancer treatments.