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.

Public Health Relevance

Our study will provide new insights into the control and manipulation of the p53 pathway, one of the most important pathway protecting human cells against the development of cancer. Specifically, it will give a quantitative understanding of how p53 is controlled in individual cells; how it turns appropriate genes on and off, how this control is misregulated in cancers; and how therapeutic strategies to manipulate p53 activity can be combined with other cancer treatments to eliminate tumor cells. The knowledge gained from these studies will advance our understanding of how p53 operates in normal and cancer cells and help translate our insights to address important clinical needs.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
1R35GM139572-01
Application #
10086147
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Koduri, Sailaja
Project Start
2021-01-01
Project End
2025-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Biology
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115