Mapping p53 dynamics to cell-fate outcomes in reprogramming and oncogenesis

点击翻译按钮获取中文摘要

Project Summary Cell fates are decided as an organism develops. In human development, pluripotent stem cells differentiate into the three layers of ectoderm, mesoderm, and endoderm. These classes of tissue further differentiate into specific cell types with specific functions including neurons, immune cells, and skin cells. These identities are stable; once a cell differentiates into its final state, it will not revert back to a stem cell state, nor will it transform into another cell type. A skin cell will not spontaneously become a neuron, even if the neuron is damaged. However, Takahashi and Yamanaka demonstrated that cells have the potential to revert back to a stem cell fate when they reprogrammed mouse fibroblasts into induced pluripotent stem cells (iPSCs) by forced overexpression of stem cell-specifying transcription factors. In 2010, Vierbuchen and colleagues demonstrated that fibroblasts could be reprogrammed directly to neurons using neuron-specific transcription factors, bypassing the need for an iPSC-intermediate. However, reprogramming efficiencies in each of these systems was low; very few cells are actually capable of changing their cellular identity. In 2019, Babos and Galloway greatly improve reprogramming efficiencies in direct motor neuron reprogramming, demonstrating improved reprogramming yields 100 times greater than the original process. They drew upon factors that enhanced another cell fate transition: cancer. Genes that promote a healthy cell’s transition to cancer also improved the ability of a cell to change its cell type. Thus, reprogramming can serve as a model of cancer initiation. By understanding the molecular mechanisms by which these oncogenes promote reprogramming, we can understand how oncogenes evade cellular barriers to cancer and establish tumors. In the F99-phase of the proposed research, I will investigate the role of the tumor suppressor protein p53 in oncogene-mediated reprogramming. p53 is the most frequently mutated gene in cancer. Rather than p53 expression being lost in cancer, it is most often mutated to create a protein unable to perform its designated functions and accumulates to abnormally high levels. As a synthetic biologist, I will design synthetic gene circuits that track and report p53 levels during reprogramming. I will isolate cells that accumulate p53 and investigate their ability to reprogram. In the K00-phase of the proposed research, I will extend my investigations of p53 to three-dimensional models of ovarian cancer. Ovarian cancer is often diagnosed at late stages, after the cancer has metastasized, leading to poor patient outcomes. 3D models of tumor initiation can shed light on the early stages of ovarian cancer and enable clinicians to catch the cancer early, when the disease is most easily treated. By inducing cancer initiation in 3D models of ovarian cancer and tracking cancer progression using p53-sensors, I will identify the drivers of tumor establishment and factors associated with early-stage disease.