Cellular senescence is a stress response that stably blocks proliferation. In-vivo studies have shown that senescing cells are present in benign or premalignant lesions and are progressively lost as the lesions become malignant. Senescence therefore is as a major physiological barrier of tumor development, making induction of senescence an attractive approach for cancer therapy. Current markers of senescence (e.g. SA-?-gal) identify senescing cells at one static time-point and usually several days after senescence has been established. Such assays do not allow quantification of the history of growth and dynamics of the response prior to the establishment of senescence. My lab?s previous studies on the tumor suppressor protein p53 revealed the importance of looking at the dynamics of signaling pathways at high temporal resolution and in single cells. Here we propose to combine live single cells imaging approaches with bioinformatics & mathematical models to study the temporal behavior of senescence-associated genes in individual cells in culture cells and in vivo in response to DNA damage and oncogene activation and to determine how the dynamics of senescence regulators is controlled and affect the decision whether a cell will senesce or arrest transiently. In our first aim we will use live cell imaging to follow the growth and divisions of individual cells in response to DNA damage and oncogenes for multiple days, and will connect growth trajectories with the establishment of senescence. We will then develop live-cell reporters for cell cycle phase, DNA breaks and oncogene expression levels to determine their effect on a cell?s probability to senesce.
In Aim2 we will quantify the dynamical behavior of senescence-associate genes in individual cultured cells and validate their regulation in- vivo, with the goal of identifying unique temporal patterns of the factors determining whether arrest is transient or permanent. We will also use bioinformatics tools to search for putative new senescence-associate genes and will develop similar live cell reporters for following their dynamics in single cells following DNA damage and oncogenic activation. Lastly, in Aim3 we will investigate the molecular mechanisms connecting internal cellular states (e.g. cell cycle phase, number of DNA breaks, levels of oncogenes) with the unique dynamics of senescence regulators and we will use genetic, chemical and synthetic perturbations to manipulate these dynamics and control the entry and establishment of senescence as well as the escape from arrest. The knowledge gained by our work will be fundamental for understanding the key circuits controlling growth, transient arrest and senescence, and how they change dynamically in individual cells. In addition, understanding the mechanisms that control senescence and the diversity in the behavior of individual cells is critical for developing new strategies for effectively activating cellular senescence in cancer cells.
Permanent arrest of cellular growth (senescence) is an important tumor suppressive mechanism. Our study will provide quantitative understanding of the pathways controlling growth and senescence in individual normal and cancer cells. The knowledge we gain should help us develop novel strategies to selectively push cancer cells toward permanent arrest.
| Reyes, José; Chen, Jia-Yun; Stewart-Ornstein, Jacob et al. (2018) Fluctuations in p53 Signaling Allow Escape from Cell-Cycle Arrest. Mol Cell 71:581-591.e5 |
| Arbelle, Assaf; Reyes, Jose; Chen, Jia-Yun et al. (2018) A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos. Med Image Anal 47:140-152 |
| Reyes, José; Lahav, Galit (2018) Leveraging and coping with uncertainty in the response of individual cells to therapy. Curr Opin Biotechnol 51:109-115 |
| Stewart-Ornstein, Jacob; Cheng, Ho Wa Jacky; Lahav, Galit (2017) Conservation and Divergence of p53 Oscillation Dynamics across Species. Cell Syst 5:410-417.e4 |
| Hafner, Antonina; Stewart-Ornstein, Jacob; Purvis, Jeremy E et al. (2017) p53 pulses lead to distinct patterns of gene expression albeit similar DNA-binding dynamics. Nat Struct Mol Biol 24:840-847 |
