Human Embryonic Stem Cell-Derived Wilson’s Disease Model for Screening Drug Efficacy

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Abstract
Human pluripotent stem cells (hPSCs) including human embryonic stem cells (hESCs) and human-induced pluripotent stem cells (hiPSCs) have been extensively studied as an alternative cellular model for recapitulating phenotypic and pathophysiologic characters of human diseases. Particularly, hiPSCs generated from the genetic disease somatic cells could provide a good cellular model to screen potential drugs for treating human genetic disorders. However, the patient-derived cellular model has a limitation when the patient samples bearing genetic mutations are difficult to obtain due to their rarity. Thus, in this study, we explored the potential use of hPSC-derived Wilson’s disease model generated without a patient sample to provide an alternative approach for modeling human genetic disease by applying gene editing technology. Wilson’s disease hPSCs were generated by introducing a R778L mutation in the ATP7B gene (c.2333G>T) using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system into wildtype hESCs. Established Wilson’s disease hESCs were further differentiated into hepatocyte-like cells (HLCs) and analyzed for disease phenotypes and responses against therapeutic agent treatment. R778L mutation in the ATP7B gene was successfully introduced into wildtype hESCs, and the introduction of the mutation neither altered the self-renewal ability of hESCs nor the differentiation capability into HLCs. However, R778L mutation-introduced HLCs exhibited higher vulnerability against excessive copper supplementation than wildtype HLCs. Finally, the applicability of the R778L mutation introduced HLCs in drug screening was further demonstrated using therapeutic agents against the Wilson’s diseases. Therefore, the established model in this study could effectively mimic the Wilson’s disease without patient’s somatic cells and could provide a reliable alternative model for studying and drug screening of Wilson’s disease.
Funding Information
  • National Research Foundation funded by the Ministry of Science and ICT of Korea (NRF-2017R1C1B2001891)

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