Reprogramming cellular identity for regenerative medicine.
Reprogramming cellular identity for regenerative medicine.
复制标题
DOI：
10.1016/j.cell.2012.02.031
复制
发表时间：
2012-03-16
期刊：
影响因子：
64.5
通讯作者：
Daley GQ
中科院分区：
文献类型：
--
作者：
Cherry AB;Daley GQ
从一个受精卵到超过200种不同分化细胞类型的精心设计的发育是一个复杂且知之甚少的过程。尽管发展单向地导致更受限制的细胞命运，但最近在细胞重编程方面的工作已经证明，可以将一种细胞身份转化为另一种细胞身份，这在生物医学研究中有着无数的应用前景，并为用患者来源的干细胞建模疾病铺平了道路。到目前为止，几乎没有讨论哪些疾病模型可能是最有用的。我们在这里回顾的证据表明，由于环境影响和表观遗传特征在重编程过程中基本上被消除，因此具有强遗传基础和高外显率的患者特定疾病模型可能在短期内被证明是最有信息量的。然而，操纵体外培养条件可能最终使基于细胞的模型重演基因-环境相互作用。在这里，我们讨论了新的重编程范式在生物医学中的影响，并概述了细胞身份的重编程如何增强我们对细胞分化的理解，以及细胞疗法和体内再生的前景。
The choreographed development of over 200 distinct differentiated cell types from a single zygote is a complex and poorly understood process. Whereas development leads unidirectionally towards more restricted cell fates, recent work in cellular reprogramming has proven that striking conversions of one cellular identity into another can be engineered, promising countless applications in biomedical research and paving the way for modeling disease with patient-derived stem cells. To date, there has been little discussion of which disease models are likely to be most informative. We here review evidence demonstrating that because environmental influences and epigenetic signatures are largely erased during reprogramming, patient-specific models of diseases with strong genetic bases and high penetrance are likely to prove most informative in the near term. However, manipulating in vitro culture conditions may ultimately enable cell-based models to recapitulate gene-environment interactions. Here, we discuss the implications of the new reprogramming paradigm in biomedicine and outline how reprogramming of cell identities is enhancing our understanding of cell differentiation and prospects for cellular therapies and in vivo regeneration.
登录
查看更多内容
影响因子：
4.5
作者：
Do CB;Tung JY;Dorfman E;Kiefer AK;Drabant EM;Francke U;Mountain JL;Goldman SM;Tanner CM;Langston JW;Wojcicki A;Eriksson N
通讯作者：
Eriksson N
影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1073/pnas.0906183107
发表时间：
2010-01-26
影响因子：
11.1
作者：
Feinberg, Andrew P.;Irizarry, Rafael A.
通讯作者：
Irizarry, Rafael A.
影响因子：
4.8
作者：
Ghodsizadeh, Arefeh;Taei, Adeleh;Baharvand, Hossein
通讯作者：
Baharvand, Hossein
影响因子：
120.7
作者：
Bjornsson, Hans T.;Sigurdsson, Martin I.;Feinberg, Andrew P.
通讯作者：
Feinberg, Andrew P.