Disease modeling using human induced pluripotent stem cells: lessons from the liver.

Biochim Biophys Acta

Department of Surgery, Anne McLaren Laboratory for Regenerative Medicine, University of Cambridge, Forvie Building, Robinson Way, Cambridge, UK. Electronic address:

Published: January 2015

Human pluripotent stem cells (hPSCs) have the capacity to differentiate into any of the hundreds of distinct cell types that comprise the human body. This unique characteristic has resulted in considerable interest in the field of regenerative medicine, given the potential for these cells to be used to protect, repair, or replace diseased, injured, and aged cells within the human body. In addition to their potential in therapeutics, hPSCs can be used to study the earliest stages of human development and to provide a platform for both drug screening and disease modeling using human cells. Recently, the description of human induced pluripotent stem cells (hIPSCs) has allowed the field of disease modeling to become far more accessible and physiologically relevant, as pluripotent cells can be generated from patients of any genetic background. Disease models derived from hIPSCs that manifest cellular disease phenotypes have been established to study several monogenic diseases; furthermore, hIPSCs can be used for phenotype-based drug screens to investigate complex diseases for which the underlying genetic mechanism is unknown. As a result, the use of stem cells as research tools has seen an unprecedented growth within the last decade as researchers look for in vitro disease models which closely mimic in vivo responses in humans. Here, we discuss the beginnings of hPSCs, starting with isolation of human embryonic stem cells, moving into the development and optimization of hIPSC technology, and ending with the application of hIPSCs towards disease modeling and drug screening applications, with specific examples highlighting the modeling of inherited metabolic disorders of the liver. This article is part of a Special Issue entitled Linking transcription to physiology in lipodomics.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4253054PMC
http://dx.doi.org/10.1016/j.bbalip.2014.05.010DOI Listing

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