Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) hold great promise for biomedicine as an unlimited source of cells for generating differentiated progenies for transplantation-based therapies, studying the etiology of various diseases, and developing new drug treatments. In my previous work published in Cell Stem Cell and Nature Protocols, I discovered a novel role for the Aurka-p53 signaling pathway in regulating ESC/iPSC identity and somatic cell programming. A single phosphorylation event mediated by Aurka on p53 shifts ESCs from differentiating to a self-renewal state. Through genome-wide analysis of direct p53 binding target genes in ESCs, I revealed a unique p53 function in negatively controlling ESC self-renewal by regulating mesodermal and ectodermal lineage gene expression and functioning as a differentiation activator. Collectively recent studies, including my own, revealed the unappreciated role of p53 in regulating cell differentiation instead of cell apoptosis and cell cycle. To build on my previous finding that p53 serves as a guardian of differentiation and expand our knowledge into the critical role of p53 as a both tumor suppressor and differentiation activator, I propose to establish the first cancer-related Li-Fraumeni Syndrome (LFS) iPSC model to study this p53 mutation-associated disorder. LFS is a genetically heterogeneous inherited cancer syndrome characterized by Mendelian autosomal dominant inheritance of germline p53 mutations that cause early onset of multiple tumors in individual patients. In contrast to other inherited cancers that are predominantly tissue-specific, LFS patients present with a variety of tumors. The p53 protein plays critical roles in regulating normal physiological homeostasis and mutations in p53 not only abolish its normal tumor suppressor activity but convert this function to oncogenic potential. The objectives of this proposal are first to model human LFS-associated osteosarcomas by using osteoblasts derived from patient-specific iPSCs and creating a """"""""disease in a dish"""""""" platform to elucidate the underlying pathogenesis caused by these p53 mutations. Correction of the LFS-linked mutation in LFS patient-derived iPSCs by Transcription Activation-Like Effector Nuclease (TALEN)-mediated precise gene targeting is expected to reverse the disease-associated dedifferentiation phenotype. The following proposal will use systematical analyses to identify the molecular mechanisms involved in p53 mutant-associated osteosarcoma and further provide therapeutic targets for treating future osteosarcomas or other cancers with p53 mutations. Successful completion of the proposed experiment will significantly advance our understanding of the role of mutant p53 in osteosarcoma development. In addition, these proposed studies will potentially lead to identifying novel therapeutic targets to improve clinical outcomes for osteosarcoma patients.
Modeling human disease in vitro has become possible due to induced pluripotent stem cell (iPSC) technology. We propose a Li-Fraumeni Syndrome (LFS) iPSC model to study osteosarcoma, one type of bone cancer, caused by p53 mutation. The results may not only provide a new experimental approach to study cancer disease but also help us to better understand the relationship between dysregulation of p53 signals and cancer development.
|Lin, Yu-Hsuan; Jewell, Brittany E; Gingold, Julian et al. (2017) Osteosarcoma: Molecular Pathogenesis and iPSC Modeling. Trends Mol Med 23:737-755|
|Zhou, Ruoji; Xu, An; Gingold, Julian et al. (2017) Li-Fraumeni Syndrome Disease Model: A Platform to Develop Precision Cancer Therapy Targeting Oncogenic p53. Trends Pharmacol Sci 38:908-927|
|Gingold, Julian; Zhou, Ruoji; Lemischka, Ihor R et al. (2016) Modeling Cancer with Pluripotent Stem Cells. Trends Cancer 2:485-494|
|Lee, Dung-Fang; Su, Jie; Kim, Huen Suk et al. (2015) Modeling familial cancer with induced pluripotent stem cells. Cell 161:240-54|
|Gingold, Julian A; Coakley, Ed S; Su, Jie et al. (2015) Distribution Analyzer, a methodology for identifying and clustering outlier conditions from single-cell distributions, and its application to a Nanog reporter RNAi screen. BMC Bioinformatics 16:225|
|Kim, Huen Suk; Bernitz, Jeffrey M; Lee, Dung-Fang et al. (2014) Genomic editing tools to model human diseases with isogenic pluripotent stem cells. Stem Cells Dev 23:2673-86|