Quantifying signaling pathway activation to monitor the quality of induced pluripotent stem cells.
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.
Atlas Regeneration, Inc, Winston-Salem, NC, USA.|Insilico Medicine, Inc, ETC, Johns Hopkins University, Baltimore, MD, USA.
Eugene
E
Makarev
Atlas Regeneration, Inc, Winston-Salem, NC, USA.|Department of Developmental Biology, Stanford University Medical Center, Stanford, CA, USA.
Kristen
K
Fortney
Department of Computational Genomics, Ludwig Maximilian University of Munich, Germany.
Maria
M
Litovchenko
Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Germany.
Karl H
KH
Braunewell
Insilico Medicine, Inc, ETC, Johns Hopkins University, Baltimore, MD, USA.|The Biogerontology Research Foundation, London, UK.
Alex
A
Zhavoronkov
Atlas Regeneration, Inc, Winston-Salem, NC, USA.|Department of Urology, Wake Forest Institute for Regenerative Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Anthony
A
Atala
D000465:Algorithms; D002454:Cell Differentiation; D002460:Cell Line; D019295:Computational Biology; D030541:Databases, Genetic; D053595:Embryonic Stem Cells / Q000166:cytology; D005347:Fibroblasts / Q000378:metabolism; D020869:Gene Expression Profiling; D006801:Humans; D057026:Induced Pluripotent Stem Cells / Q000166:cytology*; D020411:Oligonucleotide Array Sequence Analysis; D011786:Quality Control; D015398:Signal Transduction; D059467:Transcriptome; D057170:Translational Research, Biomedical
Gerotarget; algorithm; bioinformatics; embryonic stem cells; iPSC; pathway activation