Research Papers: Gerotarget (Focus on Aging):
Quantifying signaling pathway activation to monitor the quality of induced pluripotent stem cells
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Eugene Makarev1,2, Kristen Fortney1,3, Maria Litovchenko4, Karl H. Braunewell5, Alex Zhavoronkov2,6, Anthony Atala1,7
1Atlas Regeneration, Inc, Winston-Salem, NC, USA
2Insilico Medicine, Inc, ETC, Johns Hopkins University, Baltimore, MD, USA
3Department of Developmental Biology, Stanford University Medical Center, Stanford, CA, USA
4Department of Computational Genomics, Ludwig Maximilian University of Munich, Germany
5Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Germany
6The Biogerontology Research Foundation, London, UK
7Department of Urology, Wake Forest Institute for Regenerative Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
Eugene Makarev, e-mail: email@example.com
Anthony Atala, e-mail: firstname.lastname@example.org
Keywords: Gerotarget, bioinformatics, algorithm, embryonic stem cells, pathway activation, iPSC
Received: April 27, 2015 Accepted: August 10, 2015 Published: August 22, 2015
Many attempts have been made to evaluate the safety and potency of human induced pluripotent stem cells (iPSCs) for clinical applications using transcriptome data, but results so far have been ambiguous or even contradictory. Here, we characterized stem cells at the pathway level, rather than at the gene level as has been the focus of previous work. We meta-analyzed publically-available gene expression data sets and evaluated signaling and metabolic pathway activation profiles for 20 human embryonic stem cell (ESC) lines, 12 human iPSC lines, five embryonic body lines, and six fibroblast cell lines. We demonstrated the close resemblance of iPSCs with ESCs at the pathway level, and provided examples of how pathway activity can be applied to identify iPSC line abnormalities or to predict in vitro differentiation potential. Our results indicate that pathway activation profiling is a promising strategy for evaluating the safety and potency of iPSC lines in translational medicine applications.
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