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

项目摘要 细胞的命运取决于有机体的发育。在人类发育过程中，多能干细胞 分化为外胚层、中胚层和内胚层三层。这些类别的组织进一步 分化为具有特定功能的特定细胞类型，包括神经元、免疫细胞和皮肤细胞。这些 身份是稳定的；一旦细胞分化到其最终状态，它将不会恢复到干细胞状态，也不会 它会转化为另一种细胞类型。皮肤细胞不会自发地成为神经元，即使神经元 损坏了。然而，Takahashi和Yamanaka证明了细胞有可能回复到 强迫将小鼠成纤维细胞重新编程为诱导多能干细胞时干细胞的命运 干细胞特异性转录因子的过度表达。2010年，维尔布钦和他的同事们展示了 成纤维细胞可以使用神经元特异性转录因子直接重新编程为神经元，绕过 对IPSC中间体的需求。然而，这些系统的重新编程效率都很低；非常 很少有细胞能够真正改变它们的细胞身份。 2019年，Babos和Gloway极大地提高了直接运动神经元的重新编程效率 重新编程，证明改进的重新编程产生的产量是原始工艺的100倍。 他们利用了促进另一种细胞命运转变的因素：癌症。促进健康细胞的基因 转变为癌症也提高了细胞改变其细胞类型的能力。因此，重新编程可以作为 一个癌症启动的模型。通过了解这些癌基因促进的分子机制 通过重新编程，我们可以理解癌基因是如何逃避癌症的细胞屏障并建立肿瘤的。 在拟议的研究的F99阶段，我将研究肿瘤抑制蛋白P53在 癌基因介导的重编程。P53是癌症中最常见的突变基因。而不是P53 在癌症中失去表达，最常见的是突变，产生一种无法执行其指定功能的蛋白质 起作用并累积到异常高的水平。作为一名合成生物学家，我将设计合成基因电路 在重新编程期间跟踪和报告P53水平。我将分离积累P53的细胞并研究 它们重新编程的能力。 在拟议研究的K00阶段，我将把我对P53的研究扩展到三维 卵巢癌的模型。卵巢癌通常在晚期确诊，在癌症转移后， 导致患者预后不佳。肿瘤起始的三维模型可以揭示卵巢的早期阶段 并使临床医生能够在疾病最容易治疗的时候及早发现癌症。通过诱导 卵巢癌3D模型中的癌症起始和使用P53传感器跟踪癌症进展，我将识别 肿瘤形成的驱动因素和与早期疾病相关的因素。

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.